WO2019136918A1

WO2019136918A1 - Indoor positioning method, server and positioning system

Info

Publication number: WO2019136918A1
Application number: PCT/CN2018/090238
Authority: WO
Inventors: 郑德舜; 陈鼐
Original assignee: 华为技术有限公司
Priority date: 2018-01-11
Filing date: 2018-06-07
Publication date: 2019-07-18
Also published as: CN111919476B; CN111919476A

Abstract

Provided in an embodiment of the present invention are a method, server, and positioning system for indoor positioning; the method comprises: receiving environment information sent by a terminal to be positioned within a positioning area; acquiring an environment fingerprint database corresponding to the positioning area, the environment fingerprint database comprising at least one target positioning fingerprint, and the target positioning fingerprint comprising target environment information and target location information; and acquiring positioning location coordinates corresponding to the environment information in the environment fingerprint database. Hence, a reference point does not need to be calibrated in advance for the positioning area during indoor positioning, surveying personnel need only walk freely within the positioning area carrying an intelligent terminal and an ultra wide band (UWB) positioning terminal, and the speed, posture and walking trajectory of the surveying personnel are not required, thereby reducing the difficulty of implementing the indoor positioning method shown in the embodiment and improving the ease of use of the indoor positioning method.

Description

Indoor positioning method, server and positioning system

This application is required to be submitted to the Chinese Patent Office on January 11, 2018, the application number is 201810025177.5, the invention name is "an indoor positioning system and method", and submitted to the Chinese Patent Office on June 4, 2018, the application number is 201810564917.2 The priority of the Chinese patent application, which is incorporated herein by reference in its entirety in its entirety in its entirety herein in its entirety in its entirety in its entirety in

Technical field

The present application relates to the field of positioning technologies, and in particular, to a method, a server, and a positioning system for indoor positioning.

Background technique

Continuous and reliable location-based services (LBS) provide a good experience for users in both indoor and outdoor environments. Outdoor positioning and its LBS are very mature, and location services based on global positioning system (GPS) have been widely used. In recent years, related technologies and industries for location services are developing indoors.

Since the GPS signal is not received indoors, the positioning technology commonly used in the industry is a fingerprint matching technology. The technology needs to manually collect the indoor environment information by manually carrying the intelligent terminal, and establish a location fingerprint database. The intelligent terminal senses the environmental data information and the location fingerprint. The library is matched and the most likely position is calculated.

The process of manually collecting indoor environmental information by point-by-point is very time-consuming and laborious, and also has high requirements for surveyors. For example, it is only possible to collect environmental information for a period of time at each reference point that has been previously calibrated, and it is not possible to collect environmental information under the free motion state of the surveyor, and it is also impossible to collect specific behavior patterns (such as walking at different speeds, turning or The environmental information under the walking of the head, the hand-held terminal equipment moving the arm, the terminal equipment being placed in a pocket or a backpack, etc., and the surveying personnel's judgment on the reference point and the operation of the equipment will introduce errors, resulting in the collected data. The quality is not high, and the final positioning accuracy is not high.

Summary of the invention

The embodiment of the present application provides a method, a server, and a positioning system for indoor positioning capable of improving positioning accuracy and positioning efficiency.

A first aspect of the embodiments of the present invention provides an indoor positioning method, including:

Step A: The server receives environment information sent by the terminal to be located in the location area.

The environment information is the information that is detected by the terminal to be located, and the environment information that is detected by the terminal to be located is different when the terminal to be located is in different locations in the location area, and the specific The environmental information includes Bluetooth, a base station, a GPS, a WiFi, and data collected by some sensors, etc., wherein the sensor includes an accelerometer, a gravity sensor, a gyroscope, a magnetometer, a direction sensor, a pedometer, and the like.

Step B: The server acquires an environment fingerprint database corresponding to the location area.

The server shown in this embodiment may pre-create an environment fingerprint database corresponding to the positioning area, the environment fingerprint library includes at least one positioning fingerprint, the positioning area includes at least one area unit, and the server may create different positioning. a one-to-one correspondence between the fingerprint and the different area units. Specifically, the target positioning fingerprint corresponds to the first area unit, and the target positioning fingerprint is one of the at least one positioning fingerprint, and the first area unit is One of the at least one area unit.

More specifically, the target location fingerprint includes target environment information and target location information, the target environment information is environment information transmitted to the smart terminal in the first area unit, and the target location information is ultra-wideband UWB And a location coordinate sent by the positioning system to indicate that the smart terminal sends the target environment information.

Step C: The server acquires positioning location coordinates corresponding to the environment information in the environment fingerprint database.

The positioning position coordinate is a position coordinate of the to-be-positioned terminal in the positioning area.

The advantage of the indoor positioning method shown in the aspect is that the reference point does not need to be calibrated in advance, and the surveying personnel carry the intelligent terminal and the UWB positioning terminal can walk freely in the positioning area, and the speed, posture and walking of the surveying personnel The trajectory is not required, thereby reducing the difficulty of implementing the indoor positioning method shown in this embodiment, improving the ease of use of the indoor positioning method, and in the process of creating the environmental fingerprint database, the server can simultaneously obtain the location. The environment information and the location information enable the server to directly calibrate the actual location of the location area based on the location information, thereby realizing synchronous calibration of the environment information and the actual location, thereby greatly reducing the labor and time cost of creating the environment fingerprint database. And improve the accuracy of the environmental fingerprint library to provide positioning services to the positioning terminal.

With reference to the first aspect of the embodiments of the present invention, in an optional implementation manner of the first aspect of the embodiments, the indoor positioning method shown in the foregoing aspect further includes the process of creating the environment fingerprint database, where the environment is The specific creation process of the fingerprint library is:

Step A01: The server obtains all environmental information and information scanned by the smart terminal during the preset period, which is reported by the smart terminal in the preset period, in the process of the mobile terminal moving in the positioning area. All location information reported by the UWB positioning system.

One of the location information is used to indicate location coordinates when the smart terminal sends one of the environmental information, and the environment information includes wireless fidelity WiFi information and/or sensor information. The WiFi information includes a media medium control MAC address and a received signal strength indicator RSSI data of each wireless network access point AP scanned by the smart terminal, and the sensor information is information collected by a sensor of the smart terminal.

Step A02: The server determines the target location information according to all the location information reported by the UWB positioning system.

The location coordinates indicated by the target location information are located in the first regional unit.

Step A03: The server determines the target environment information according to all the environment information reported by the smart terminal.

The target environment information is environment information reported by the smart terminal in the first area unit;

Step A04: The server determines that the target positioning fingerprint is a positioning fingerprint that includes the target location information and the target environment information.

In the process of creating the environmental fingerprint database shown in the present aspect, the surveying personnel simultaneously wear the smart terminal and the UWB positioning terminal, so that the server can simultaneously obtain the same in the case that the surveying personnel's walking trajectory and the walking manner are not required. The environment information and the location information enable the environmental data server to directly calibrate the actual location of the location area based on the location information, thereby realizing synchronous calibration of the environment information and the actual location, thereby greatly reducing the manpower for creating the environment fingerprint database. And time cost.

With reference to the first aspect of the embodiments of the present invention, in an optional implementation manner of the first aspect of the embodiments of the present disclosure, in the implementation manner, where the target environment information includes the WiFi information, the step A04 specifically includes :

Step A041: The server counts the total number of samples of all APs scanned by the smart terminal in the first area unit.

And the number of samples N _{i of the} first target AP.

The first target AP is the i-th AP scanned by the smart terminal in the first area unit, and the number of APs scanned by the smart terminal in the first area unit Is n, the i and the n are positive integers greater than or equal to 1, and the i is less than or equal to the n.

Step A042: The server calculates an appearance probability (PerformanceP(MAC _i ) of the first target AP by using the following formula.

Step A043: The server determines that the target positioning fingerprint includes a first positioning fingerprint, where the first positioning fingerprint includes an appearance probability earthquake(MAC _i ) of the first target AP.

Step A111: The server acquires a target RSSI sequence of the first target AP.

The target RSSI sequence includes an RSSI scanned by the first target AP by the smart terminal each time;

Step A112: The server calculates a probability density function Norm (RSSI) of a single target Gaussian distribution model GSM according to the following formula;

Wherein, the μ is the mean of the target RSSI sequence, and σ is the standard deviation of the target RSSI sequence;

Step A113: The server calculates a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP according to the following formula;

Where π _k is a preset weighting coefficient, and the K is a positive integer greater than or equal to 1;

Step A114: The server determines that the first positioning fingerprint includes a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP.

With reference to the first aspect of the embodiments of the present invention, in an optional implementation manner of the first aspect of the embodiments, the step A04 specifically includes:

Step A121: The server determines location coordinates of a target location, where the target location is any location located in the first regional unit;

Step A122: The server determines that the first positioning fingerprint includes location coordinates of the target location.

Based on the implementation manner, the environment fingerprint database is created based on the WiFi information detected by the smart terminal, and the environment fingerprint database created based on the WiFi information can accurately locate the terminal to be located, and is collected by the terminal to be located. The WiFi information can realize the indoor positioning process without installing a new device on the terminal to be positioned, saving the cost of indoor positioning and improving the ease of use of the indoor positioning method shown in this aspect.

With reference to the first aspect of the embodiments of the present invention, in an optional implementation manner of the first aspect of the embodiments of the present disclosure, the indoor positioning method further includes:

Step C01, the server calculates the first target sub-matching value Px by the following formula;

Px=log ₁₀ (occurenceP(MAC _i ).gmNorm(RSSI));

Specifically, the environment information is WiFi information scanned by the to-be-positioned terminal in a target time period, and the server determines, at the server, a MAC address of any AP included in the environment information, and the first location If the MAC address of one AP included in the fingerprint is the same, step C01 is triggered.

Step C02: The server calculates a matching value corresponding to the first area unit according to the following formula.

Matching value

Step C11, the server calculates the second target sub-matching value Py by the following formula;

Py=log ₁₀ (1-occurenceP(MAC _i ));

Specifically, if the server determines that the MAC address of any AP included in the environment information is different from the MAC address of any AP included in the first positioning fingerprint, the step C11 is triggered.

Step C12: The server calculates a matching value corresponding to the first area unit according to the following formula;

Matching value

With reference to the first aspect of the embodiments of the present invention, in an optional implementation manner of the first aspect of the present disclosure, the step C includes:

Step C21: The server obtains a matching list.

The matching list includes all the area units included in the positioning area, and all the area units included in the matching list are sorted in descending order of the matching values.

Step C22: The server acquires, in the matching list, the location coordinates wi of the target location corresponding to any regional unit in the first N-bit regional unit.

Step C23, the server calculates the first positioning position coordinate Dx by the following formula;

Step C24: The server determines that the positioning position coordinate is the first positioning position coordinate Dx.

In the implementation manner, the server is based on the created environment fingerprint database. After the WiFi information is collected by the terminal to be located, the server may perform indoor positioning based on the WiFi information collected by the terminal to be located. Due to the creation of an environmental fingerprint library, the accuracy and efficiency of indoor positioning are improved.

With reference to the first aspect of the embodiments of the present invention, in an optional implementation manner of the first aspect of the embodiment, the target environment information includes the WiFi information and the sensor information, where the step A04 specifically includes:

Step A31: The server determines that the target positioning fingerprint includes the first positioning fingerprint and the second positioning fingerprint, and the second positioning fingerprint is a positioning fingerprint of the hidden Markov model HMM acquired according to the sensor information.

With reference to the first aspect of the embodiments of the present invention, in an optional implementation manner of the first aspect of the embodiments of the present disclosure, the implementation manner includes the following steps:

Step E11: The server calculates a transition probability transitionP(STEP _i ) of the first area unit by using a formula, where the transition probability transitionP(STEP _i ) is used for training to obtain the second positioning fingerprint;

Wherein, the numerator is transferred to the i-th second area unit in a process of moving the kth step of the movement of the surveyor carrying the smart terminal in the first area unit, wherein the smart terminal is in the first The number of times the sensor information reported in the area unit is sampled, the second location area is a area unit adjacent to the first area unit in the location area, and the number of the second area unit is n And the n and the k are positive integers greater than or equal to 1, and the denominator is a process in which the smart terminal located in the first area unit moves to all the second area units, the smart terminal The total number of times the sensor information reported in the first area unit is sampled.

Step E21: The server calculates a target traveling direction matching degree azimuthMatch _m in the first area unit according to the following formula, where the azimuthMatch _m is a surveying personnel carrying the smart terminal in the first area unit, along a target traveling direction m a direction of travel matching when moving, the target traveling direction m being any direction in which the smart terminal moves within the first area unit;

Wherein the minDiff is a deviation angle formed between any direction included in the target direction sequence midAzi and the target heading Azimuth, and the target heading Azimuth is a k-1 step step for the surveyor carrying the intelligent terminal a probability of moving into the first area unit, the target direction sequence midAzi including the target traveling direction and a target time period, wherein the target time period is that the smart terminal is within the first area unit a period of time during which the target travel direction moves;

In step E22, the server acquires the target geomagnetic information, and the target geomagnetic information is the k-th step of the movement of the surveying personnel carrying the smart terminal, and the smart terminal reports the sensor information in the first regional unit. The geomagnetic information included, the target geomagnetism information includes a first component value magE, a second component value magN, a third component value magU, and a geomagnetism precision value magVal, wherein the first component value magE is at a center coordinate In the ENU, along the X-direction component value parallel to the horizontal plane, the second component value magN is the Y-direction component value parallel to the horizontal plane under the ENU, and the third component value magU is under the ENU, perpendicular to the horizontal plane. The Z-direction vertical component value; the geomagnetic accuracy value magVal represents the measurement accuracy;

Step E23: The server determines, according to the target geomagnetic information, a preset input set X, where X={X ₁ =1, X ₂ =magE, X ₃ =magN, X ₄ =magU, X ₅ =magVal, X ₆ =azimthMatch _m };

Calculating a target history matching degree matchHistory _m corresponding to the target traveling direction in the first area unit by using a formula;

among them,

Representing an S-type growth curve sigmoid function for the six target parameter sets X _i W _i , the target parameter set X _i W _i comprising a first parameter X _i and a second parameter W _i , wherein the first parameter X _i is Any parameter included in the preset input set, the second parameter W _i being a weight value corresponding to the first parameter X _i ;

Step E24: The server calculates an output probability matchValue(grld _j ) of the first area unit according to the following formula;

Wherein, grld _j represents the first regional unit, M represents the number of historical matching degrees of the first regional unit, and the target historical matching degree matchHistory _m represents any historical matching degree of the M historical matching degrees. ;

Step E25: The server creates a second positioning fingerprint that is a hidden Markov model HMM based on the transition probability of the first regional unit and the output probability.

The data server shown in this embodiment may construct the second fingerprint library in the form of a search tree based on the output probability sequence and the transition probability sequence, wherein the server passes according to a process that the surveyor travels. The output probability and transition probability of any regional unit can construct a layer in the search tree, which further improves the accuracy and efficiency of positioning the terminal to be located.

Step F11: The server determines an area to be located.

The coordinate of a position included in the to-be-positioned area is the first positioning position coordinate Dx, and the area of the to-be-positioned area is smaller than the area of the positioning area;

Step F12: The server acquires a sequence of sensor information sent by the terminal to be located, where the sensor information sequence includes target sensor information and a target reporting time point, where the target sensor information is that the to-be-located terminal is in the to-be-positioned area, and reported Any one of the at least one sensor information, the target reporting time point is a time point at which the to-be-targeted terminal reports the target sensor information;

Step F13: The server determines, according to the Viterbi algorithm, a set of positioning area units corresponding to the sensor information sequence and having different probability values, where the positioning area unit set includes the smart terminal moving process. Passing at least one area unit in order from the front to the back in the chronological order;

Step F14: The server determines a second positioning position, where the second positioning position is the positioning area unit having the highest probability value, and is sorted at any position included in the last area unit;

Step F15: The server determines that the positioning position coordinate is the second positioning position coordinate.

The method for implementing the indoor positioning method by the server may include a first positioning phase and a second positioning phase, where the first positioning phase is referred to as “rough positioning” and the second positioning phase is referred to as “fine positioning”, ie, In the first positioning phase (shown in step F11), an initial indoor location (first positioning location) of the object to be located is determined by a WiFi matching positioning technique, and the first positioning location is used as a center in the second positioning phase. Frame a to-be-positioned area in the shape of a circle, a positive direction, etc., and then use the geomagnetic matching technique to further calculate the precise position of the object to be positioned in the to-be-positioned area, thereby improving the speed and accuracy of the indoor positioning, and improving the HMM. The positioning service of the Viterbi algorithm can effectively reduce the complexity and calculation of geomagnetic matching, and improve the efficiency and accuracy of positioning the terminal to be positioned.

Step F21: The server uses the second positioning position coordinate as a starting position, and determines a movement trajectory of the to-be-positioned terminal at a future time according to the pedestrian dead reckoning PDR.

According to the aspect, the server can predict the movement trajectory of the user carrying the terminal to be located at a future time based on the second positioning position, and can provide the user with better efficiency and better accuracy based on the predicted movement trajectory. The indoor positioning service reduces the amount of calculations that the server provides to the indoor positioning service for users in the future.

A second aspect of the embodiments of the present invention provides a server, including:

a receiving unit, configured to receive environment information that is sent by the terminal to be located in the location area, where the environment information is information detected by the terminal to be located, and when the location of the terminal to be located is different, the terminal to be located is The detected environmental information is different;

An acquiring unit, configured to acquire an environment fingerprint database corresponding to the positioning area, where the environment fingerprint database includes at least one positioning fingerprint, the positioning area includes at least one area unit, wherein the target positioning fingerprint corresponds to the first area unit, The target location fingerprint is one of the at least one location fingerprint, the first area unit is one of the at least one area unit, and the target location fingerprint includes target environment information and target location information. The target environment information is environment information that is sent to the smart terminal in the first area unit, where the target location information is sent by the ultra-wideband UWB positioning system to instruct the smart terminal to send the target environment information. Position coordinates

And a matching unit, configured to acquire a positioning location coordinate corresponding to the environment information in the environment fingerprint database, where the positioning location coordinate is a location coordinate of the terminal to be located in the positioning area.

The server shown in this aspect is used to perform the indoor positioning method shown in the first aspect, and the specific execution process and the description of the beneficial effects are shown in the above first aspect, and details are not described herein.

In an optional implementation manner of the second aspect of the embodiments of the present disclosure, the acquiring unit includes:

a first acquiring module, configured to acquire, in a process of moving the smart terminal in the positioning area, all environments scanned by the smart terminal in the preset period reported by the smart terminal every preset period Information and all location information reported by the UWB positioning system, wherein one of the location information is used to indicate location coordinates when the smart terminal sends one of the environmental information, the environmental information Included with wireless fidelity WiFi information and/or sensor information, the WiFi information including a media medium control MAC address and received signal strength indicator RSSI data of each wireless network access point AP scanned by the smart terminal, the sensor information Information collected by the sensor of the smart terminal;

a first processing module, configured to determine target location information according to all the location information reported by the UWB positioning system, where location coordinates indicated by the target location information are located in the first regional unit;

a second processing module, configured to determine target environment information according to the all the environment information reported by the smart terminal, where the target environment information is environment information reported by the smart terminal in the first area unit;

And a third processing module, configured to determine that the target positioning fingerprint is a positioning fingerprint that includes the target location information and the target environment information.

According to a second aspect of the embodiments of the present invention, in an optional implementation manner of the second aspect of the embodiments, the target environment information includes the WiFi information, and the third processing module includes:

a first calculation submodule, configured to count the total number of samples of all APs scanned by the smart terminal in the first area unit

And a sampling number N _i of the first target AP, where the first target AP is the i-th AP scanned by the smart terminal in the first area unit, and the first area unit is The number of APs scanned by the smart terminal is n, the i and the n are positive integers greater than or equal to 1, and the i is less than or equal to the n;

a second calculation submodule, configured to calculate an occurrence probability of the first target AP, chanceP(MAC _i ), by using the following formula;

And a first determining submodule, configured to determine that the target positioning fingerprint includes a first positioning fingerprint, where the first positioning fingerprint includes an appearance probability earthquake(MAC _i ) of the first target AP.

According to a second aspect of the embodiments of the present invention, in an optional implementation manner of the second aspect of the embodiments, the third processing module includes:

a first acquisition sub-module, configured to acquire a target RSSI sequence of the first target AP, where the target RSSI sequence includes an RSSI scanned by the first target AP by the smart terminal;

a third calculation submodule, configured to calculate a probability density function Norm (RSSI) of a single target Gaussian distribution model GSM according to the following formula;

a fourth calculation submodule, configured to calculate a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP according to the following formula;

And a second determining submodule, configured to determine that the first positioning fingerprint includes a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP.

a third determining submodule, configured to determine a location coordinate of the target location, where the target location is located at any location within the first regional unit;

And a fourth determining submodule, configured to determine that the first positioning fingerprint includes location coordinates of the target location.

According to a second aspect of the embodiments of the present invention, in an optional implementation manner of the second aspect of the embodiments of the present disclosure, the environment information is the WiFi information scanned by the to-be-positioned terminal within a target time period, The server also includes:

a first calculating unit, configured to: if the MAC address of any AP included in the environment information is the same as the MAC address of an AP included in the first positioning fingerprint, calculate the first target sub-match value Px by using the following formula ;

Px=log ₁₀ (occurenceP(MAC _i ).gmNorm(RSSI));

a second calculating unit, configured to calculate a matching value corresponding to the first area unit according to the following formula;

Matching value

In an optional implementation manner of the second aspect of the embodiments of the present invention, the server further includes:

a third calculating unit, configured to: if the MAC address of any AP included in the environment information is different from the MAC address of any AP included in the first positioning fingerprint, calculate the second target by using the following formula Matching value Py;

Py=log ₁₀ (1-occurenceP(MAC _i ));

a fourth calculating unit, configured to calculate a matching value corresponding to the first area unit according to the following formula;

Matching value

In an optional implementation manner of the second aspect of the embodiments of the present disclosure, the matching unit includes:

a second obtaining module, configured to obtain a matching list, where the matching list includes all the regional units included in the positioning area, and all the regional units included in the matching list are in descending order of the matching value put in order;

a third obtaining module, configured to acquire, in the matching list, a position coordinate wi of the target position corresponding to any one of the regional units in the first N-bit area unit;

a fourth obtaining module, configured to calculate a first positioning position coordinate Dx by the following formula;

And a determining module, configured to determine that the positioning position coordinate is the first positioning position coordinate Dx.

In an optional implementation manner of the second aspect of the embodiments of the present disclosure, the target environment information includes the WiFi information and the sensor information, and the third processing module further And determining, by the target positioning fingerprint, the first positioning fingerprint and the second positioning fingerprint, wherein the second positioning fingerprint is a positioning fingerprint of the hidden Markov model HMM acquired according to the sensor information.

a fifth calculating unit, configured to calculate a transition probability transitionP(STEP _i ) of the first area unit by using a formula, the transition probability transitionP(STEP _i ) is used for training to obtain the second positioning fingerprint;

a sixth calculating unit, configured to calculate a target traveling direction matching degree azimuthMatch _m in the first area unit according to the following formula, wherein the azimuthMatch _m is a surveying personnel carrying the smart terminal in the first area unit, along the target a traveling direction matching degree when the traveling direction m is moved, wherein the target traveling direction m is any direction in which the smart terminal moves in the first area unit;

a first processing unit, configured to acquire target geomagnetic information, wherein the target geomagnetic information is in a process of moving the kth step of the surveying personnel of the smart terminal, where the smart terminal is located in the first regional unit And reporting the geomagnetism information included in the sensor information, the target geomagnetism information including a first component value magE, a second component value magN, a third component value magU, and a geomagnetism precision value magVal, wherein the first component value magE is In the center coordinate system ENU, along the X-direction component value parallel to the horizontal plane, the second component value magN is a value of the Y-direction component parallel to the horizontal plane under the ENU, and the third component value magU is under the ENU. a vertical component value in the Z direction perpendicular to the horizontal plane; the geomagnetic accuracy value magVal represents the measurement accuracy;

a second processing unit, configured to determine a preset input set X according to the target geomagnetic information, where X={X ₁ =1, X ₂ =magE, X ₃ =magN, X ₄ =magU, X ₅ =magVal,X ₆ =azimthMatch _m };

a third processing unit, configured to calculate, by using the following formula, a target history matching degree matchHistory _m corresponding to the target traveling direction in the first area unit;

among them,

a fourth processing unit, configured to calculate an output probability matchValue(grld _j ) of the first area unit according to the following formula

And a fifth processing unit, configured to create a second positioning fingerprint that is a hidden Markov model HMM based on the transition probability of the first regional unit and the output probability.

In an optional implementation manner of the second aspect of the embodiments of the present disclosure, the matching unit further includes:

a first determining module, configured to determine an area to be located, where a coordinate of a position included in the to-be-positioned area is the first positioning position coordinate Dx, and an area of the to-be-positioned area is smaller than an area of the positioning area;

a second determining module, configured to acquire a sequence of sensor information sent by the terminal to be located, where the sensor information sequence includes target sensor information and a target reporting time point, where the target sensor information is that the terminal to be located is in the to-be-positioned area And any one of the reported at least one sensor information, where the target reporting time point is a time point at which the to-be-targeted terminal reports the target sensor information;

a third determining module, configured to determine, according to a Viterbi algorithm, a set of positioning area units corresponding to the sensor information sequence and having different probability values, where the positioning area unit set includes the smart During the moving of the terminal, at least one area unit passes through the chronological order in order from the front to the back;

a fourth determining module, configured to determine a second positioning position, where the second positioning position is the positioning area unit having the highest probability value, and is sorted at any position included in the last area unit;

And a fifth determining module, configured to determine that the positioning position coordinate is the second positioning position coordinate.

And a prediction unit, configured to use the second positioning position coordinate as a starting position, and determine, according to the pedestrian dead reckoning PDR, a movement trajectory of the to-be-positioned terminal at a future time.

A third aspect of the embodiments of the present invention provides a positioning system, including a server, a terminal to be located, an intelligent terminal, and an ultra-wideband UWB positioning system. The server is not shown in the second embodiment of the present invention;

The to-be-located terminal is used to send the environment information to the server in the location area, where the environment information is the information detected by the terminal to be located, and the location to be located is different when the location of the to-be-located terminal is different. The environmental information detected by the terminal is different;

The server is configured to acquire an environment fingerprint database corresponding to the location area, where the environment fingerprint database includes at least one location fingerprint, the location area includes at least one area unit, where the target location fingerprint corresponds to the first area unit, The target location fingerprint is one of the at least one location fingerprint, the first area unit is one of the at least one area unit, and the target location fingerprint includes target environment information and target location information. The target environment information is environment information that is sent to the smart terminal in the first area unit, where the target location information is sent by the UWB positioning system to instruct the smart terminal to send the target. Position coordinates when environmental information;

The server is further configured to acquire, in the environment fingerprint database, location location coordinates corresponding to the environment information, where the location location coordinates are location coordinates of the to-be-positioned terminal in the location area.

A fourth aspect of the embodiments of the present invention provides a server, including:

One or more processors, memories, bus systems, and one or more programs, the processors and the memory being coupled by the bus system;

Wherein the one or more programs are stored in the memory, the one or more programs comprising instructions that, when executed by the server, cause the server to perform the first aspect of the embodiments of the present invention as described above The method of indoor positioning shown in the figure, the specific implementation process will not be described.

A fifth aspect of an embodiment of the present invention provides a computer readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a server, cause the server to execute as described above The method for indoor positioning shown in the first aspect of the present invention is not described in detail.

The embodiment of the invention provides a method, a server and a positioning system for indoor positioning. In the process of performing indoor positioning, the server receives the environment information sent by the terminal to be located in the positioning area, and the server may also acquire the corresponding area corresponding to the positioning area. An environmental fingerprint database, the environment fingerprint database includes at least one target positioning fingerprint, the target positioning fingerprint includes target environment information and target location information, and the server acquires positioning location coordinates corresponding to the environment information in the environment fingerprint database. The positioning position coordinate is a position coordinate of the to-be-positioned terminal in the positioning area. It can be seen that in the process of indoor positioning, the reference area does not need to be calibrated in advance, and the surveying personnel carry the intelligent terminal and the UWB positioning terminal can walk freely in the positioning area, and the speed, posture and walking trajectory of the surveying personnel are not The requirements are reduced, thereby reducing the implementation difficulty of the indoor positioning method shown in this embodiment, improving the ease of use of the indoor positioning method, and in the process of creating the environmental fingerprint database, the server can simultaneously obtain the environmental information. And the location information, so that the server can directly calibrate the actual location of the location area based on the location information, thereby realizing synchronous calibration of the environment information and the actual location, thereby greatly reducing the labor and time cost of creating the environment fingerprint database, and improving The environmental fingerprint library provides the accuracy of the positioning service to the positioning terminal.

DRAWINGS

1 is a schematic structural view of an embodiment of a positioning system provided by the present invention;

2 is a flow chart of steps of an embodiment of an indoor positioning method provided by the present invention;

3 is a flow chart of steps of another embodiment of an indoor positioning method provided by the present invention;

4 is a flow chart showing steps of another embodiment of the indoor positioning method provided by the present invention;

FIG. 5 is a flow chart showing steps of another embodiment of an indoor positioning method according to the present invention; FIG.

FIG. 6 is a schematic diagram of an application scenario of an indoor positioning method according to the present invention; FIG.

FIG. 7 is a schematic diagram of another application scenario of the indoor positioning method provided by the present invention; FIG.

Figure 8 is a schematic diagram of a sigmoid function;

9 is a flow chart of steps of another embodiment of an indoor positioning method provided by the present invention;

FIG. 10 is a schematic diagram of another application scenario of the indoor positioning method provided by the present invention; FIG.

11 is a schematic structural diagram of an embodiment of a server provided by the present invention;

12 is a schematic structural diagram of another embodiment of a server provided by the present invention;

FIG. 13 is a schematic structural diagram of another embodiment of a server provided by the present invention.

Detailed ways

The embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

The terms "first", "second", "third", "fourth", etc. (if present) in the specification and claims of the present application and the above figures are used to distinguish similar objects without having to use To describe a specific order or order. It is to be understood that the data so used may be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than what is illustrated or described herein. In addition, the term "comprises" or "comprises" or any variations thereof, is intended to cover a non-exclusive inclusion, for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to those that are clearly listed Steps or units, but may include other steps or units not explicitly listed or inherent to such processes, methods, products or devices.

In order to describe the embodiment of the present application more accurately, some indoor positioning technologies that may be involved in the embodiments of the present application and the advantages and disadvantages of the technology are described below. The following two types are introduced, one is a GPS-like technology, and the other is a GPS-like technology. One type is fingerprint matching positioning technology. GPS-like technologies can usually have the following types:

1. Radio frequency positioning, radio frequency is an electromagnetic wave with a certain wavelength. Radio frequency identification (RFID) utilizes the transmission characteristics of inductance and electromagnetic coupling or radar reflection to realize automatic recognition of objects. The positioning system usually consists of electronic tags, RF readers, middleware and computer databases; real-time positioning is not possible, positioning accuracy is low, and anti-interference ability is poor.

2. Ultrasonic positioning, ultrasonic positioning mostly adopts reflective ranging method. The positioning system consists of a main range finder and several electronic tags. The main range finder is placed on the mobile robot, and the electronic tag is placed in a fixed position in the indoor space. . The positioning process is as follows: the main range finder sends the same frequency signal to each electronic tag, and the electronic tag receives the signal and then reflects and transmits it to the main range finder, thereby determining the distance between each electronic tag and the main range finder. coordinate. The positioning accuracy can reach centimeter level, and the defect is that the ultrasonic wave attenuates significantly during the transmission process and affects the effective range of its positioning.

3. Infrared positioning, infrared is an electromagnetic wave with a wavelength between radio waves and visible light, so that the object to be tested is attached with an electronic identification, and the identification is periodically sent to the infrared receiver fixedly placed indoors by the infrared transmitter. The object's ID is measured and the receiver transmits the data to the database over a wired network. The positioning accuracy is 5 to 10 meters. The defect is that the infrared light is easily blocked by the object or the wall during the transmission process, and the transmission distance is short, the system structure is complicated, and the effectiveness and practicability are insufficient.

4. ZigBee, the positioning system passes through a number of blind nodes to be located and a reference node of a known location and a gateway network, and the blind nodes coordinate and communicate with each other to achieve positioning. Signal transmission is greatly affected by multipath effects and motion, and the positioning accuracy depends on the channel physical quality, signal source density, environment and algorithm accuracy, resulting in higher cost of positioning software.

5, iBeacon positioning, iBeacon is a 2.4G radio frequency technology based on low-power Bluetooth technology, model ranging positioning according to RF field strength with distance attenuation. The propagation of RF signals is susceptible to environmental interference and is unstable, with a positioning accuracy of 3 meters.

6, Ultra Wide Band (UWB) positioning, UWB uses a very short time interval (less than 1 nanosecond), 1GHz or more bandwidth for communication, no carrier, also known as pulse radio communication. UWB can achieve data transmission rates of hundreds of Mbps to several Gbps in a range of 10 meters by transmitting extremely low power signals over a wide spectrum. It has strong anti-interference, high transmission rate, wide bandwidth, and transmission power. Small and many other advantages. By arranging a plurality of positioning base stations with known coordinates in the room, the positioning tag carried by the positioning personnel is freely movable in the reachable area included in the positioning base station, and the tag transmits a pulse signal to the positioning base station according to a certain frequency, and the positioning tag is calculated by the TDOA algorithm. The location, the positioning base station returns the result to the location server. Each tag has a unique ID that associates the object (or person) to be located with the tag by ID, supporting thousands of tags to be positioned simultaneously.

In the fingerprint matching and positioning technology, manual surveying is the basis and premise of fingerprint matching and positioning, and this part requires a lot of manpower and time cost. The traditional manual survey method is to mark the reference point in the indoor positioning area in advance, and the surveying personnel carry the intelligent terminal to stay at each reference point for a period of time to collect environmental information. Or the reference line is marked in the indoor positioning area in advance, and the surveying personnel carry the intelligent terminal to move around on each reference line to collect environmental information. This method is time consuming and laborious, because the size of the positioning area, the density of the reference point, and the acquisition time of each reference point determine the workload of the survey task and the accuracy of the positioning. In addition, this method can only collect the environmental information of the surveyor at the reference point stationary state or the reference line moving at a constant speed. The requirements of the surveyer's motion mode are relatively high, and the environmental information under the free motion state cannot be collected. Position-related behavioral modes (such as walking speed, heading direction, turning information, etc.); Finally, due to the judgment of the surveying personnel on the reference position and the operation of the intelligent terminal, errors are introduced, and the collected environmental data information and the real position have a certain degree. The deviation affects the accuracy of the positioning.

It should be noted that the traditional fingerprint matching positioning method relies on manual site survey to construct a fingerprint database, that is, a professional engineering personnel is arranged to carry professional equipment to the site to carry out professional position measurement and environmental data collection work, for each piece of positioning area, It takes a period of time to survey each of these reference locations, which is time consuming, financial and manpower. Therefore, no matter what kind of signal fingerprint is used, manual surveying is once the most difficult task of fingerprint matching and positioning, and it is also the biggest bottleneck that hinders the actual promotion of fingerprint positioning.

Fingerprint matching positioning technology can include the following:

1. Geomagnetic localization, particle filtering is one of the most commonly used algorithms in geolocation matching based on geomagnetic matching. It is used to solve geomagnetic fingerprint discrimination, sensor deviation and noise, and improve positioning accuracy. . However, particle filtering is susceptible to user behavior models (such as walking speed) on the one hand, and positioning errors usually accumulate over time. Once lost, it is difficult to keep up, the system is not robust; on the other hand, the algorithm usually has very strict restrictions on the posture of the mobile phone. For example, the direction of the mobile phone must always be consistent with the user's heading direction, and there is no universality.

2, WiFi positioning, based on WiFi matching positioning technology, you need to set the reference location in advance. The collected environmental information includes a MAC address of a wireless network access point (AP) and a received signal strength indication (RSSI) value. Then, the fingerprint database is established according to the method, and the received AP is matched with the fingerprint in the database to obtain a most suitable location. Commonly used matching algorithms include nearest neighbor (NN), k nearest neighbor (KNN), weighted k nearest neighbor (WKNN), and neural network.

Based on the characteristics and limitations of the above various positioning technologies, in order to enable the user to carry only terminals having environmental data information collection capabilities such as mobile phones, accurate indoor positioning can be achieved. In the embodiment of the present application, UWB technology is combined with manual surveying and fingerprint matching positioning technology to achieve accurate positioning in the room. The environmental data information in the embodiment of the present application includes Bluetooth, a base station, a GPS, a sensor detected data, and WiFi information, wherein the sensor includes an accelerometer, a gravity sensor, a gyroscope, a magnetometer, a direction sensor, a pedometer, and the like. At least one of them may be used separately or in combination depending on the data used for the fingerprint.

The specific structure of the positioning system used in the embodiment of the present application is described. Referring to FIG. 1 , FIG. 1 is a schematic structural diagram of a positioning system applied to an indoor positioning method according to an embodiment of the present application. As shown in FIG. 1 , the implementation is as shown in FIG. 1 . The positioning system shown in the example includes a smart terminal 101, a UWB positioning system, and an environmental data server 104, wherein the UWB positioning system includes a UWB positioning terminal 102 and a positioning base station 103.

The smart terminal 101 shown in this embodiment refers to a type of embedded computer system device capable of intelligently sensing, storing, and processing environment information, and generally refers to a smart phone, a tablet, and the like. The environment information shown in this embodiment refers to environment data information that can be used by the smart terminal 101, including Bluetooth, base station, WiFi, GPS, data detected by sensors of the smart terminal 101, and the like. The sensor of the smart terminal 101 includes an accelerometer, a gravity sensor, a gyroscope, a magnetometer, a direction sensor, a pedometer, and the like, and the smart terminal 101 can report the collected environment information to the environment data server 104.

In this embodiment, the UWB positioning terminal 102 is a UWB positioning tag fixed on the object or on the body of the surveying person, and has a unique ID. The surveying personnel carry the positioning tag to walk at a normal speed in the reachable area in the positioning area. The type of the UWB positioning terminal 102 is not limited. For example, the type of the UWB positioning terminal 102 can be a card type, a wristband type, a helmet type, etc.; The surveying personnel of the UWB positioning terminal 102 walk at a normal speed in the reachable area in the positioning area, the positioning base station 103 calculates the position of the positioning terminal 102 in real time, and the positioning base station 103 can go to the environmental data server at a fixed period. The location information of the UWB positioning terminal 102 is reported, and the location information includes, but is not limited to, a timestamp and a current coordinate, etc., wherein the fixed period may be set by a staff member, for example, the fixed period may be 100 milliseconds. 1 second, 3 seconds, etc., in the embodiment, the fixed period is 100 milliseconds as an example for exemplary description.

In this embodiment, the number of servers that execute the environment data server 104 is not limited. To implement indoor positioning, the embodiment may implement the function of the environment data server 104 by using at least one server.

Based on the positioning system shown in FIG. 1 , the present application can implement an indoor positioning method. The specific implementation process of the indoor positioning method provided by the present application is described below with reference to FIG. 2 :

Step 201: The intelligent terminal sends the collected environment information to the environmental data server.

Step 202: The UWB positioning system sends the collected location information to the environmental data server.

Specifically, the execution timings of step 201 and step 202 shown in this embodiment are performed simultaneously. Specifically, in the survey stage, the survey personnel can carry the intelligent terminal and the UWB positioning terminal at the same time, and the survey personnel continuously in the positioning area. During a certain period of time, the trajectory, speed, direction, and manner of carrying the smart terminal of the surveying personnel are not limited in this embodiment, as long as the moving trajectory of the surveying personnel satisfies the preset condition. The preset condition shown in this embodiment is that the trajectory of the surveying personnel covers the area that all surveyors in the positioning area can reach, and the number of times covered by all the reachable surveyors is greater than or equal to the preset number of times. This embodiment is exemplified by taking the preset number of times as two examples.

It can be seen that, by using the method shown in this embodiment, as long as the moving trajectory of the surveying person satisfies the preset condition, the surveying personnel can walk freely within the positioning area, thereby reducing restrictions on the surveying personnel, thereby improving the manual. The ease of use of the survey.

Because the surveying personnel carry the smart terminal and the UWB positioning terminal at the same time, the smart terminal and the UWB positioning terminal are located at the same position at the same time during the walking of the surveying personnel in the positioning area.

In this embodiment, the UWB positioning terminal is a UWB positioning tag fixed on the object or on the body of the surveying person, and has a unique ID, and the surveying personnel carries the positioning tag to walk at a normal speed in the reachable area in the positioning area. The type of the setting of the UWB positioning terminal is not limited in this embodiment. For example, the type of the UWB positioning terminal may be a card type, a wristband type, a helmet type, etc.; and the UWB positioning terminal is carried. The surveying personnel walks at a normal speed in the reachable area in the positioning area. During the walking process, the UWB positioning terminal transmits a pulse signal to the positioning base station according to a certain frequency, and the positioning base station calculates the UWB positioning in real time through the time difference of arrival (TDOA) algorithm. a location coordinate of the terminal, the positioning base station may report the location information of the UWB positioning terminal to the environmental data server according to a fixed period, where the location information includes, but is not limited to, a time stamp and a location coordinate, etc., wherein the fixed period It can be set by a staff member, for example, the fixed period can be 100 milliseconds, 1 second, 3 seconds, etc., this embodiment The example is described by taking the fixed period as 100 milliseconds as an example.

The environment information shown in this embodiment is that the smart terminal can be perceived by the smart terminal in the process of moving the positioning area, and the surveying personnel carrying the smart terminal move to the When the location of the location is different, the environment information detected by the smart terminal is different. The environment information in this embodiment includes Bluetooth, a base station, a GPS, a WiFi, and data collected by some sensors, where the sensor includes an acceleration. Meters, gravity sensors, gyroscopes, magnetometers, direction sensors, pedometers, etc.

Step 203: The environment data server receives the environment information and the location information.

Step 204: The environment data server creates an environment fingerprint database.

Specifically, the environment data server is configured to create the environment fingerprint database, and the environment data server needs to obtain all environment information sent by the smart terminal in the location area, and the environment data server further needs Acquiring all the location information sent by the UWB positioning terminal in the positioning area, the environment data server may create an environment fingerprint database according to all the environment information and all the location information that have been obtained, wherein The location information and the location information are mutually corresponding information, and the location information is used to indicate location coordinates in the location area when the smart terminal sends the corresponding environment information.

For a better understanding, the positioning area shown in this embodiment is located on the 15th floor of the A building as an example. The environment data server is summarized in the 15th floor of the A building. All the environmental information received and all the location information, so that the environmental data server creates an environmental fingerprint database corresponding to the 15th floor (ie, the positioning area) of the A building according to all the environmental data and the location information.

The environment data server shown in this embodiment is to create the environment fingerprint database, and the environment data server first needs to acquire when the time system of the smart terminal and the time system of the UWB positioning terminal are synchronized. a correspondence between the target environment information and the target position coordinates, wherein the target position coordinate is a coordinate of the target position in the positioning area, and the target position is any position in the positioning area, specifically, The environment information reported by the smart terminal to the environmental data server at the target location is the target environment information, and the UWB positioning terminal reports the target location coordinates to the environmental data at the target location a server, such that the environment data server obtains the correspondence between the target environment information and the target location coordinates.

Optionally, in the case that the smart terminal reports the environmental information to the environmental data server in real time, and the UWB positioning system reports the location information to the environmental data server in real time, the environmental data is The server can directly obtain the correspondence between the target environment information and the target location coordinates according to the environment information reported by the smart terminal and the location information reported by the UWB positioning system.

Optionally, the smart terminal periodically reports the environmental information to the environmental data server, and the UWB positioning terminal periodically reports the location information to the environmental data server, and the smart information How the environment data server creates the target environment information when the period in which the terminal reports the environment information to the environment data server and the period in which the UWB positioning terminal reports the location information to the environment data server is different And the specific process of the correspondence of the coordinates of the target position is explained:

For example, the first period in which the smart terminal reports the environmental information to the environmental data server is 10 milliseconds, and the second period in which the UWB positioning terminal reports the location information to the environmental data server is 100 milliseconds. The environmental data server needs to acquire the position coordinates of the first period in the second period, that is, the environment data server needs to acquire the position coordinates of each 10 milliseconds in each 100 milliseconds. The obtaining manner is that the environment data server receives the location coordinates reported by the UWB positioning terminal at the end time of the second period, and the environment data server connects the UWB positioning terminal to the end time of the second period. Performing interpolation calculation on the reported position coordinates to obtain the position coordinates of the first period in the second period, so that the environment data server can obtain the second period, the smart terminal is The environmental information reported in each first cycle and the corresponding position coordinates.

In the case that the environment data server obtains the correspondence between the target environment information and the target location coordinates, the environment data server may create an environment fingerprint database. Specifically, the environment data server creates the In the environmental fingerprint database, the environment data server needs to divide the positioning area in advance, so that the divided positioning area includes X*Y area units, and each of the area units corresponds to one positioning fingerprint. All the positioning fingerprints corresponding to the area unit constitute the environmental fingerprint library.

Specifically, the X and Y are integers greater than 0. The size of the area unit can be set, for example 0.3 m by 0.3 m, 1 m by 1 m, 1 m 5 by 1 m 5, 2 m by 2 m, 2 m by 3 m and 3 m by 3 m The environment data server can be flexibly set according to the requirements of the positioning accuracy, which is not limited in this embodiment, and the accuracy of the positioning shown in this embodiment is inversely proportional to the size of the area unit.

It can be understood that the positioning area is divided into X*Y area units, and the area unit is the smallest unit of division; then, for each area unit, one positioning fingerprint is corresponding, and the following describes the creation process of the environment fingerprint library:

For example, the first location fingerprint corresponding to the first area unit is used as an example, wherein the first area unit is any one of the plurality of area units included in the location area, and the The first positioning fingerprint is a positioning fingerprint corresponding to the first area unit in the environmental fingerprint database.

The location fingerprint corresponding to the first area unit refers to the first environment information and the first location coordinates corresponding to the first environment information. Specifically, the environment data server is configured according to the determined target environment information and Corresponding relationship of the target position coordinates, the first environment information corresponding to the first position coordinate is determined, wherein the first position coordinate is carried by the surveyor when the surveyor moves to the inside of the first area unit The location information included in the location information reported by the UWB positioning terminal, and the first environment information is environment information reported by the smart terminal carried by the surveyor when the surveyor moves to the first location coordinate.

Because of the existing solution, the survey personnel need to arrange professional positioning equipment to carry out professional position measurement and environmental data collection work on the spot. For each positioning area, it is necessary to carry out a survey for each time in each of the reference positions. Very time consuming, financial and manpower. Therefore, no matter what kind of signal fingerprint is used, manual surveying is once the most difficult task of fingerprint matching and positioning, and it is also the biggest bottleneck that hinders the actual promotion of fingerprint positioning.

The environment data server shown in this embodiment can provide a location service to the to-be-located terminal located in the location area based on the created environment fingerprint database, and the environment fingerprint database creation process shown in this embodiment is used. The advantage is that the positioning area does not need to be calibrated in advance, and the surveying personnel carry the intelligent terminal and the UWB positioning terminal can walk freely in the positioning area, and the speed, posture and walking trajectory of the surveying personnel are not required, thereby reducing the requirement. The difficulty of implementing the indoor positioning method shown in this embodiment improves the ease of use of the indoor positioning method, and in the process of creating the environmental fingerprint database, the environmental data server can simultaneously acquire the environmental information and the The location information is such that the environmental data server can directly calibrate the actual location of the location area based on the location information, thereby realizing synchronous calibration of the environment information and the actual location, thereby greatly reducing the labor and time cost of creating an environment fingerprint database. And improve the accuracy of the environmental fingerprint library to provide positioning services to the positioning terminal

The following describes several cases of the environmental fingerprint library shown in this embodiment:

In the first case of the environment fingerprint database, the environment fingerprint library includes a first fingerprint database. The specific process of creating the first fingerprint database is described in detail below with reference to FIG. 3:

Step 301: The intelligent terminal sends the collected environmental information to the environmental data server.

The environment information shown in this embodiment is the WiFi information collected by the smart terminal. In this embodiment, the environment information is exemplified as the WiFi information. In other embodiments, the WiFi information may also be The Bluetooth information and the like are not limited in this embodiment.

The following describes the specific content included in the WiFi information:

Specifically, the smart terminal may collect and report the WiFi information of the indoor environment according to the WiFi scanning period of the smart terminal, where the WiFi information refers to the smart terminal moving in the positioning area. During the process, the smart terminal scans the AP data list, and the AP data list includes the AP data scanned in one or more scan cycles, and each AP data scans the AP's MAC address and RSSI data for the smart terminal. The MAC address and the RSSI data are reported once every other WIFI scan period, and the period may be, for example, 2.3 seconds. Each AP has a unique MAC address. For RSSI, the RSSI data varies according to the distance from the AP and whether there is an obstacle between the distances. It should be noted that the WiFi information obtained in one scanning cycle can be represented by the following two groups:

{MAC ₁ , RSSI ₁ }, {MAC ₂ , RSSI ₂ }, ..., {MAC _n , RSSI _n };

Where n is the number of APs scanned in the period, and depends on the distribution of the current location AP of the smart terminal and the WiFi scanning mechanism of the smart terminal, and the RSSI indicates the signal strength of any AP scanned by the smart terminal.

For a specific process of the smart terminal sending the WiFi information to the server, refer to the specific process of the smart terminal sending the environment information to the server, as shown in FIG. 2 , and details are not described herein.

Step 302: The UWB positioning system sends the collected location information to the environmental data server.

For the specific implementation process of the step 302 shown in this embodiment, please refer to the step 202 shown in FIG. 2, which is not specifically described in this embodiment.

Step 303: The environment data server receives the environment information and the location information.

Step 304: The environment data server creates a first fingerprint database.

Specifically, the environment data server may collect the collected WiFi information, and the environment data server counts, in a first area unit, a total number of sampling times of all APs and each AP in the first area unit. The number of times of sampling, the number of times of sampling of each AP is represented by N _i , so that the probability of occurrence of each AP can be counted, since the MAC address can uniquely identify an AP, and thus belongs to any AP in the first area unit. The probability of occurrence can be calculated by the following formula (1):

The occurrence _P (MAC _i ) indicates the probability of occurrence of the AP having the MAC address MAC _i in the first area unit, and the denominator in the formula is the total of all the collected APs in the first area unit. frequency.

That is, the first positioning fingerprint shown in this embodiment includes an appearance probability (MAC _i ) of any AP included in the first area unit. Specifically, the first positioning fingerprint further includes the A Gaussian mixture distribution function gmNorm (RSSI) of the RSSI sequence possessed by any of the APs included in the first area unit.

The following is a detailed description of the acquisition process of the Gaussian mixture distribution function gmNorm (RSSI) of the RSSI sequence:

The RSSI sequence of any AP in the first area unit is an RSSI sequence that is sampled by the AP in a preset time period and includes at least one RSSI; for the RSSI sequence, it can be regarded as a hybrid. Gaussian model, which is composed of K single gaussian single model (GSM) linear, each GSM is called a component in the mixed Gaussian model. Therefore, the RSSI value in the RSSI sequence of an AP obeys the following probability distribution function (PDF), that is, the Gaussian mixture distribution function gmNorm (RSSI) satisfies the following formula (2):

Where π _k is a weighting coefficient, indicating the probability of selecting the Kth GSM, the probability can be calculated according to the expectation maximization (EM) algorithm; the Kth GSM Norm (RSSI) is the probability of the Kth GSM The density function, that is, the Gaussian mixture distribution function gmNorm (RSSI) is obtained by multiplying K norm (RSSI) by respective weighting coefficients and accumulating them.

Among them, a single GSM Norm (RSSI) satisfies the following formula (3):

Wherein μ is the mean of the RSSI sequence and σ is the standard deviation of the RSSI sequence.

The first positioning fingerprint shown in this embodiment includes a probability P (PerformanceP(MAC _i ) of any AP included in the first area unit, and a Gaussian mixture distribution function gmNorm (RSSI) of an RSSI sequence of any AP. In addition, the first positioning fingerprint further includes actual position coordinates of the first area unit.

Optionally, the actual position coordinate of the first area unit may be an actual position coordinate of a positive center of the first area unit in a GPS coordinate system.

Optionally, the actual location coordinates of the first area unit are not necessarily in the center of the first area unit, and the actual location coordinates of each area unit may be according to the AP set corresponding to the first area unit. The RSSI sequence of each of the APs is calculated, wherein the AP set corresponding to the first area unit includes all APs detected during the movement of the smart terminal in the first area unit, Since the RSSI is characterized by the closer the distance, the stronger the signal, the farther the distance is, the weaker the signal is, and the actual position of each AP is fixed, so it can be based on the RSSI sequence corresponding to each AP in the AP set. The actual location is estimated such that the RSSI sequence corresponding to each AP in the AP set is obtained from the actual location measurement.

Optionally, in the process of moving the smart terminal in the first area unit, the environment data server obtains the location information reported by the UWB positioning system, where the smart terminal is in the first Each time the location coordinates of the environment information are reported in the area unit, the environment data server may calculate an average value of all position coordinates reported by the smart terminal in the first area unit as the first area unit. Actual location.

The foregoing description of the process of determining the actual location of the first area unit is an optional example, which is not limited. Alternatively, the environment data server shown in this embodiment may also be determined in the first area unit. The target location, where the target location is any location within the first regional unit, the environmental data server may determine that the location coordinate of the target location is the actual location coordinate of the first regional unit.

For example, the positioning area shown in this embodiment is located on the 15th floor of the A building, for example, in units of 15 floors, the environmental data server summarizes all the WiFi received on the 15th floor of the A building. The information and all the location information further cause the environmental data server to create a first fingerprint library corresponding to the 15th floor (ie, the location area) of the A building based on all the WiFi information and the location information.

Based on the first fingerprint database shown in FIG. 3, the specific process of how the positioning engine implements the positioning of the terminal to be located through the first fingerprint database is described below with reference to FIG. 4:

Step 401: The terminal to be located sends the target WiFi information to the positioning engine.

The positioning engine shown in this embodiment may be operated by a positioning engine capable of performing positioning services on the terminal to be located. The positioning engine shown in this embodiment may be run on the environment data server shown in the foregoing embodiment, or may be operated. On a server different from the environment data server, in a case where the positioning engine runs on a server different from the environment data server, the positioning engine may receive an environmental fingerprint created by the environment data server. Library.

Specifically, the to-be-located terminal that needs to perform the positioning service may send the target WiFi information collected in units of the scanning period to the environmental data server.

For the specific structure of the terminal to be located, refer to the specific structure of the smart terminal shown in FIG. 1 , which is not described in detail in this embodiment. The positioning engine shown in this embodiment may be used for the terminal to be located. The current location is positioned.

The target WiFi information shown in this embodiment is the WiFi information collected by the terminal to be located in the target time period. The target WiFi information shown in this embodiment is information for performing indoor positioning, and the specific collection process of the target WiFi information is shown in the foregoing embodiment, and details are not described herein.

Specifically, in order to locate the terminal to be located, the terminal to be located transmits the WiFi information collected in the target time period to the positioning engine, and the end time point of the target time segment shown in this embodiment is the target to be sent by the terminal to be located. At the time of the WiFi information, the start time period of the target time period is any time point before the time when the target WiFi information is transmitted, that is, the duration of the target time period is not limited in this embodiment.

Step 402: The positioning engine receives the target WiFi information.

The positioning engine may receive the target WiFi information, and locate the to-be-located terminal according to the target WiFi information.

Step 403: The positioning engine calculates a target matching value of the positioning area unit.

According to the above process of creating the first fingerprint database, the environment data server shown in this embodiment can create a first fingerprint database corresponding to different floors, and the positioning engine shown in this embodiment can pass the building. The identification module determines a specific target floor in the building where the terminal to be located is located. If the positioning area shown in this embodiment is located in the target floor, the positioning engine can dynamically load the location corresponding to the target floor. The first fingerprint database is described to achieve positioning of the terminal to be located.

As shown in FIG. 3, the first fingerprint database created by the environment data server is a fingerprint database corresponding to the 15th floor of the A building, and the positioning engine shown in this embodiment is identified. When the terminal to be located is located on the 15th floor of the A building, the positioning engine can dynamically load the first fingerprint library corresponding to the 15th floor of the A building.

Specifically, after the location engine shown in this embodiment receives the target WiFi information, the positioning engine may match the target WiFi information with the first fingerprint database that the positioning engine has created.

The specific process of the matching of the target WiFi information with the first fingerprint database is described in the following steps. The specific description of the first fingerprint database is shown in the embodiment shown in FIG. 3 . Specifically, it will not be described in detail in this embodiment.

The positioning area unit shown in this embodiment is any one of the plurality of area units included in the positioning area. The specific process of calculating the target matching value by the positioning engine is described in detail below:

The positioning engine shown in this embodiment needs to determine whether the MAC address of the AP included in the target WiFi information is the same as the MAC address of one of the plurality of APs corresponding to the location area unit in the first fingerprint database. the same;

If yes, the positioning engine may calculate the target matching value by using a first matching value algorithm, and if not, the positioning engine may calculate the target matching value by using a second matching value algorithm.

The following describes the specific execution process of the positioning engine through the first algorithm for matching values:

Specifically, the positioning engine acquires an appearance probabilityoc (MAC _i ) of any AP in the positioning area unit, a Gaussian mixture distribution function gmNorm (RSSI) of the RSSI sequence, and an actual location of the positioning area unit, and specifically acquires For the process, please refer to the embodiment shown in FIG. 3, which is not limited in this embodiment.

The positioning engine may calculate the target matching value Pa of the positioning area unit based on the formula (4) shown below;

The Px is a first target sub-matching value, and the first target sub-matching value is a sub-matching value of any one of the plurality of APs detected by the to-be-located terminal in the positioning area unit, where n is The total number of APs detected by the smart terminal in the location area unit. It can be seen that the target matching value Pa of the positioning area unit shown in this embodiment is the sum of the sub-matching values of all APs corresponding to the positioning area unit.

The positioning engine may calculate the first target sub-matching value Px by formula (5);

Px=log ₁₀ (occurenceP(MAC _i ).gmNorm(RSSI))················ (5);

The MAC _i is a surveying phase, the MAC address of the second target AP, and the second target AP is a surveying phase, and any one of the plurality of APs detected by the smart terminal in the positioning area unit, The occurrenceence _P (MAC _i ) is an appearance probability of the second target AP, and the gmNorm (RSSI) is a Gaussian mixture distribution function obeyed by the RSSI sequence of the second target AP, the occurrenceP(MAC _i ) and the For the specific acquisition process of the gmNorm (RSSI), please refer to the embodiment shown in FIG. 3, which is not specifically described in this embodiment.

It can be seen that the positioning engine shown in this embodiment may multiply the occurrence probabilityocenceP(MAC _i ) of the second target AP by the mixed Gaussian distribution function gmNorm (RSSI) obeyed by the RSSI sequence of the second target AP, The product takes a base 10 logarithm to obtain the first target submatch value.

The following describes the specific execution process of the positioning engine through the second matching value algorithm:

Specifically, the positioning engine may calculate the target matching value Pb of the positioning area unit based on the formula (6) shown below;

Wherein, Py is a second target sub-matching value, and the second target sub-matching value is a sub-matching value of any one of the plurality of APs detected by the to-be-located terminal in the positioning area unit, where n is The total number of APs detected by the smart terminal in the location area unit. It can be seen that the target matching value Pb of the positioning area unit shown in this embodiment is the sum of the sub-matching values of all APs corresponding to the positioning area unit.

The positioning engine may calculate the second target sub-matching value Py by formula (7);

Py=log ₁₀ (1-occurenceP(MAC _i ))······································· (7);

The MAC _i is a surveying phase, the MAC address of the second target AP, and the second target AP is a surveying phase, and the AP to be located is any AP of the multiple APs detected by the positioning area unit. , occurenceP (MAC _i) is the probability of occurrence of the second target AP, the occurenceP (MAC _i) acquisition process in particular, please refer to the embodiment shown in FIG. 3, the specific embodiment is not repeated in the present embodiment.

It can be seen that the positioning engine shown in this embodiment can subtract the occurrence of the chanceP(MAC _i ) by 1 to obtain the second target sub-matching value Py.

Optionally, if the positioning engine shown in this embodiment determines that the positioning area unit is an edge area located in the positioning area, acquiring, by the positioning engine, an area unit located at an edge position in the positioning area. In the case of the target matching value, the positioning engine may subtract the preset parameter from the target matching value of the area unit located at the edge position in the positioning area, and the size of the preset parameter is not limited in this embodiment. The target matching value of the area unit minus the size of the preset parameter may be inversely proportional to the distance of the area unit from the center of the positioning area.

Step 404: The positioning engine obtains a matching list.

In the case that the positioning engine can obtain the target matching value corresponding to all the regional units in the positioning area, the positioning engine may perform the numerical values of all the target matching values in descending order. Sorting to get the matching list.

Step 405: The positioning engine acquires the first positioning position coordinate according to the WiFi fingerprint matching algorithm.

The positioning engine may obtain the actual position coordinates Wi of any one of the first N regional units in the matching list. Specifically, the positioning engine may obtain the ranking by querying the first fingerprint database. For the specific process of setting the actual position of the area unit in the first N zone unit, the specific process of setting the actual location of the area unit in the first fingerprint library is shown in the embodiment shown in FIG. 3 , and details are not described herein.

The positioning engine may calculate the first positioning position coordinate Dx based on the formula (8) shown below.

It can be seen that the positioning engine shown in this embodiment may select, as the first positioning position coordinate Dx, an average value of actual position coordinates of the area units ranked in the first N bits in the matching list.

In the case that the positioning engine acquires the coordinates of the first positioning position, the positioning engine may determine the actual position of the terminal to be positioned in the positioning area according to the first positioning position coordinate, thereby The positioning engine is capable of providing a positioning service to the to-be-located terminal based on the first positioning location coordinate.

In the second case of the environment fingerprint database, the environment fingerprint library includes a first fingerprint library and a second fingerprint library, and the first fingerprint library and the second fingerprint database are created as shown in FIG. 5 below. The specific process is described in detail:

Step 501: The intelligent terminal sends the environment information to the environmental data server.

The environment information shown in this embodiment includes the WiFi information and the sensor information. The specific process of the smart terminal collecting the WiFi information, as shown in the embodiment shown in FIG. 3, is not described in this embodiment. .

The following describes the specific process of collecting sensor information by the smart terminal shown in this embodiment:

The sensor information shown in this embodiment is information collected by the sensor of the smart terminal and can be used for positioning. The sensor shown in this embodiment includes an accelerometer, a gravity sensor, a gyroscope, a magnetometer, a direction sensor, At least one of the pedometers and the like is not limited in this embodiment, and the smart terminal shown in this embodiment is specifically referred to as the structure of the smart terminal shown in FIG. 1 , and details are not described herein.

Step 502: The UWB positioning system sends the collected location information to the environmental data server.

For the specific implementation process of step 502 shown in this embodiment, please refer to step 302 shown in FIG. 3, and the specific implementation process is not described herein.

Step 503: The environment data server receives the environment information and the location information.

Step 504: The environment data server simultaneously creates a first fingerprint library and a second fingerprint database.

Specifically, the positioning area shown in this embodiment is located on the 15th floor of the A building as an example. The environment data server is collected on the 15th floor of the A building. All the WiFi information, the sensor information, and all the location information, so that the environmental data server creates a first fingerprint database corresponding to the 15th floor (ie, the location area) of the A building according to all the WiFi information and the location information. The environmental data server creates a second fingerprint database corresponding to the 15th floor (ie, the positioning area) of the A building according to all the sensor information and the location information, and the specific process of the environmental data server to create the first fingerprint database, please For details, refer to the embodiment shown in FIG. 3, which is not specifically described in this embodiment.

The following describes the specific process of creating the second fingerprint database by the environment data server shown in this embodiment:

First, the environmental data server obtains a sequence of transition probabilities.

Specifically, the environment data server shown in this embodiment creates the transition probability sequence by using a floor unit. For example, if the environment data server creates a transition probability sequence corresponding to the 15th floor of the room, the environment data server may The sensor information reported by all the smart terminals located on the 15th floor is counted, so that the environmental data server can create a transition probability sequence corresponding to the 15th floor according to the sensor information reported by all the smart terminals located on the 15th floor.

The transition probability sequence shown in this embodiment includes a transition probability corresponding to any area unit of the location area, and the following is an example of calculating, by using an environment data server, a transition probability of the first area unit, where The first area unit is any area unit included in the positioning area, and the calculation process of the transition probability corresponding to other area units included in the positioning area is as follows: The specific process of the transfer probability of the regional unit:

In this embodiment, after the environmental data server obtains the sensor information, if the surveying personnel carry the smart terminal to move in the positioning area, the moved moving trajectory satisfies a preset condition. For details of the preset conditions, please refer to the embodiment shown in FIG. 2 . Specifically, in the embodiment, the environmental data server may obtain the transition probability of the smart terminal moving in the positioning area.

In the positioning area, after the surveying personnel carry the smart terminal to move a target step size, the surveying unit can move from the first area unit to the ith second area unit, where the target step size is For the specific description of the first area unit, please refer to the embodiment shown in FIG. 3 for details of the movement of the first area unit in the positioning area, which is not described in detail in this embodiment. In an embodiment, the first area unit is a regional unit that passes through the target step size and is counted by the environment data server, and the second area unit is a unit that is counted by the environment data server. The area unit in which the end position of the target step is located.

Wherein the plurality of area units formed by the environmental data server dividing the positioning area, a plurality of second area units adjacent to the first area unit, and the target is traveling in different directions in the surveying personnel In the case of a step size, the end position of the target step may be located in a different second area unit of the plurality of second area units.

During the surveying process, during the surveying process, the surveying personnel move the target step length from the first regional unit. Because the surveying personnel move in different directions, the surveying personnel may directly have different trajectories in the surveying process. FIG. 6 is an example, wherein FIG. 6 shows each area unit formed by the environment data server dividing the positioning area.

After the surveyer is in the first region 601 and travels the target step in the first direction 602, the smart terminal can move to the inside of the second region unit 603. As another example, after the surveyer is in the first region 601 and travels the target step in the second direction 604, the smart terminal can move to the inside of the second region unit 605. For another example, after the surveyer is located in the first area 601 and travels the target step in the third direction 606, the smart terminal can move to the inside of the second area unit 607. By analogy, the smart terminal can also travel the target step size in the fourth direction 608, the fifth direction 609, the sixth direction 610, the seventh direction 611, and the eighth direction 612 as shown in FIG. 6.

It can be seen that, in the case that no obstacle blocking the surveying person is disposed in the area unit, in the process of traveling the target step in the first area unit, the possible traveling direction of the smart terminal is 8 If the area unit is provided with an obstacle that forms an occlusion on the surveying unit, for example, the smart terminal travels in the direction 609 along the trajectory of the target step size, and if a wall or the like is provided, the survey can be performed. If the person forms an occluded obstacle, the surveyor will not be able to travel the target step size in direction 609.

The target step size of the smart terminal movement shown in this embodiment is not greater than the side length of the positioning area, and the transition probability transitionP(STEP _i ) is a quotient of the first sub-sensor information and the target sensor information.

Specifically, the first sub-sensor information is in a process in which the smart terminal moves the target step size in any direction to transfer to the i-th second area unit, where the smart terminal is in the first area The number of times the sensor information reported in the unit is sampled N _i .

For example, as shown in FIG. 6 , when the smart terminal moves the target step, the direction along which the direction is 612 is taken as an example, and the smart terminal needs to collect the smart terminal to move the target step in the direction 612. long process, the intelligent terminal in the first unit region information is reported by the sensor sampled the number of times N _i said intelligent terminals to the number of times N _i said sampled data reported to the environment server .

The target sensor information is the smart terminal located in the first area unit, and the target step size is moved in all directions that can be traveled to transfer the smart terminal to the second area unit. The total number of times all sensor information reported by the smart terminal in the first area unit is sampled during the process

Where n is the number of the second area units.

Continuing with the example shown in FIG. 6 , when the smart terminal travels the target step in the first direction 602, the number of times the sensor information reported by the smart terminal in the first area unit 601 is sampled by the smart terminal is continued. N _1, when the intelligent terminal 604 in a second direction of travel of the target step size, said intelligent terminal unit in the first region 601 is reported by the sensor information sampled frequency intelligent terminal N _2, the smart When the terminal travels the target step in the third direction 606, the number of times the sensor information reported by the smart terminal in the first area unit 601 is sampled by the smart terminal N ₃ , and the smart terminal is in the fourth direction 608 When the target step size is advanced, the sensor information reported by the smart terminal in the first area unit 601 is sampled by the smart terminal N ₄ , and the smart terminal travels in the fifth direction 609 to the target step size when said intelligent terminal unit in the first region 601 is reported by the sensor information sampled frequency intelligent terminal N _5, when the intelligent terminal 610 in the direction of travel of the sixth step of the target, Said intelligent terminal unit in the first region 601 is reported by the sensor information sampled N times intelligent terminals _6, the intelligent terminal 611 when the traveling direction of the target in the seventh step, the intelligent terminal in the The number N ₇ of the sensor information reported by the first area unit 601 is sampled by the smart terminal. When the smart terminal travels the target step in the eighth direction 612, the smart terminal is in the first area unit 601. If the reported sensor information is sampled by the intelligent terminal N ₈ , the environmental data server can obtain the target sensor information as N ₁ +N ₂ +N ₃ +N ₄ +N ₅ +N ₆ +N ₇ + N ₈ .

It can be seen that the environmental data server can calculate the transition probability transitionP(STEP _i ) of the first regional unit by using the following formula (9):

Wherein, the numerator is the sensor information reported by the smart terminal in the first area unit during the process of moving to the ith second area unit when the smart terminal of the first area unit moves by one target step The number of times of sampling, the denominator is a process in which the smart terminal located in the first area unit moves to all the second area units, and the total information of the sensor information reported by the smart terminal in the first area unit is sampled frequency. Through the formula, the environmental data server can calculate the transition probability of the intelligent terminal from one regional unit to another regional unit. This process completes the preparation of the transition probability in the hidden Markov model.

In the case that the environmental data server acquires the transition probability of the first regional unit, and so on, the environmental data server may acquire the transition probability of any regional unit included in the positioning region, and the environmental data server The created transition probability sequence includes transition probabilities for all of the regional units included in the location area.

In the case that the environmental data server acquires a transition probability sequence, the environmental data server may acquire an output probability sequence.

Specifically, the environment data server shown in this embodiment creates the output probability sequence in units of floors. For example, if the environment data server creates an output probability sequence corresponding to the 15th floor of the room, the environment data server may The sensor information reported by all the smart terminals located on the 15th floor is counted, so that the environmental data server can create an output probability sequence corresponding to the 15th floor according to the sensor information reported by all the smart terminals located on the 15th floor.

The output probability sequence shown in this embodiment includes an output probability corresponding to any area unit of the positioning area, and the following is an example of calculating an output probability of the first area unit by the environment data server, where The first area unit is any area unit included in the positioning area, and the calculation process of the output probability corresponding to other area units included in the positioning area is as follows: The specific process of the output probability of the regional unit:

The output probability of the first area unit is the matching degree between the sensor information reported by the smart terminal collected by the environmental data server in the first area unit and the first area unit, In the case of a regional unit, the surveying personnel can calculate the historical matching degree of the first regional unit every time the first regional unit is passed during the surveying phase, for example, if in the surveying stage, the survey is performed. The person in the travel trajectory passes through the first area unit M times, and the environmental data server can acquire the M historical matching degrees of the first area unit, that is, the historical matching degree of the first area unit. The number of times is equal to the number of times the surveyor passes through the first area unit.

Specifically, the environment data server determines an average value of all the historical matching degrees of the first area unit as an output probability of the first area unit.

More specifically, the environmental data server may calculate the output probability matchValue(grld _j ) of the first regional unit based on formula (10):

Grld _j in the formula (10) represents the first area unit, M represents the number of historical matching degrees of the first area unit calculated by the environmental data server, and the matchHistory _m represents M pieces of the history. The matchHistory _m value range is [0, 1] for any historical match in the match.

How the history matching degree calculating a target matchHistory _m region of the first unit of the server process environmental data will be described, wherein the target history matching degree matchHistory _m is the M history matching unit first region Any historical match in degrees.

First, as shown in FIG. 7 , if the target step size 703 shown in this embodiment is the Kth step size in the moving track of the smart terminal, the environment data server reports from the smart terminal. Obtaining the second sub-sensor information in the K-1th step of the environment, the environmental data server may obtain the smart terminal in the K-1th step according to the second sub-sensor information. The target heading Azimuth at the last moment; wherein the smart terminal is located at the last moment of the K-1th step is a reference position 702 as shown in FIG. 7, and the K is an integer greater than or equal to 1; The target heading is the direction of travel of the K-1th step.

The environmental data server may calculate, according to the angular velocity reported by the gyroscope set by the smart terminal or the magnetic field strength reported by the magnetometer, to obtain the target heading. The target heading refers to a probability that the smart terminal moves into the first area unit after the K-1 step according to the target heading.

Then, the environmental data server statistic surveyer moves to the direction sequence midAzi in the first area unit in the location area, and specifically, the smart terminal can be transferred to the first area unit in different directions, The environment data server may count the direction in which the smart terminal moves within the positioning area and the time period in which the smart terminal is located in the first area unit, and the direction constructed by the environment data server The sequence includes a direction in which the smart terminal moves within the positioning area and a corresponding time period.

Then, the environmental data server counts a deviation angle minDiff formed between any direction included in the direction sequence midAzi and the target heading Azimuth, the unit of the deviation angle minDiff is an angle, and is located in the interval [-180 Within °, 180 °].

The environmental data server may perform normalization processing as shown in the following formula (11) on the deviation angle minDiff to obtain a traveling direction matching degree azimuthMatch _m :

As shown in the formula (11), the environmental data server may determine that the deviation formed between the first direction included in the direction sequence midAzi and the target heading is determined by the environmental data server If the angle minDiff is less than 10 degrees, the environmental data server may determine the traveling direction matching degree azimuthMatch _m =1 in the first direction, and determine, by the environmental data server, the direction sequence midAzi When the deviation angle minDiff formed between the second direction and the target heading is greater than 30 degrees, the environmental data server may determine the traveling direction matching degree azimuthMatch _m =0 in the second direction, And the environment data server determines that the deviation angle minDiff formed between the third direction included in the direction sequence midAzi and the target heading is greater than or equal to 10 and less than or equal to 30, then the environment The data server can determine the direction of travel matching azimuthMatch _m = 1.5-0.05·min Diff in the third direction.

The following describes how the environmental data server calculates the output probability based on the obtained traveling direction matching degree matchHistory _m :

The environmental data server may calculate the target geomagnetism information, the matching degree of the traveling direction matching degree matchHistory _m and the first positioning area as the output probability by logistic regression.

The target geomagnetic information is obtained by the environmental data server, in the process of moving the target step by the smart terminal, the sensor information reported by the smart terminal in the first area unit, and from the Geomagnetic information extracted from sensor information.

The target geomagnetism information includes a first component value magE, a second component value magN, a third component value magU, and a geomagnetism precision value magVal, wherein the first component value magE is in a local cartes coordinate system (local cartesian coordinates coordinate Under the system, ENU), the X-direction component value parallel to the horizontal plane; the second component value magN is the Y-direction component value parallel to the horizontal plane under the ENU; the third component value magU is under the ENU, The vertical component of the Z direction perpendicular to the horizontal plane; the geomagnetic accuracy value magVal represents the measurement accuracy of the component values of the respective directions.

The environmental data server may calculate the target historical match degree matchHistory _m based on logistic regression.

First, explain the logistic regression:

Suppose there are some discrete data points, and these points are fitted with a straight line. The process of this fitting is regression. Logistic regression is a kind of linear regression, which is based on linear regression and a sigmoid function. The expression is as shown in formula (12):

Specifically, the logistic regression is to adapt the probability of occurrence of an event to a logical curve. The logical curve is an S-shaped curve. As shown in the sigmoid function in this embodiment, the sigmoid function is characterized by a quick change and a gradual decrease. Slow, finally saturated, the sigmoid function can be seen in Figure 8:

As shown in Figure 8, the advantage of the sigmoid function is that its variable is from negative infinity to positive infinity, while the range of values is [0,1], and since the sigmoid function between [0,1] can be a probability function. So that the logistic regression function can be associated with the matchHistory _m distribution.

The environment data server shown in this embodiment may calculate the target history matching degree matchHistory _{m of} the first area unit based on the formula (13), and the calculation formula is as follows:

among them,

Representing a sigmoid function for the six target parameter sets X _i W _i , the target parameter set X _i W _i comprising a first parameter X _i and a second parameter W _i , wherein the first parameter X _i is a preset input set Any of the parameters included, the preset input set:

X={X ₁ =1, X ₂ =magE, X ₃ =magN, X ₄ =magU, X ₅ =magVal,X ₆ =azimthMatch _m }, the second parameter W _i is the first parameter X _{For the} weight value corresponding to _i , the specific value range of the second parameter W _i is not limited in this embodiment, and the experience value obtained by the surveying personnel in the process of surveying and determining the training based on the collected data may be obtained, for example, In this embodiment, the weight value corresponding to X ₁ is W ₁ =-2.995624, the weight value corresponding to X ₂ is W ₂ =−0.050082, and the weight value corresponding to X ₃ is W ₃ =−0.184297, and the weight value corresponding to X ₄ W ₄ = -0.117742, the weight value corresponding to X ₅ is W ₅ = -0.045686, and the weight value corresponding to X ₆ is W ₆ = 1.053176.

The environment data server shown in this embodiment creates a second fingerprint database based on the acquired output probability and the transition probability. Specifically, the environment data server shown in this embodiment creates a transition probability sequence and the Outputting a probability sequence, the environmental data server may create a second fingerprint database corresponding to the transition probability sequence and the output probability sequence floor. In the above example, the transition probability sequence and the output probability sequence are corresponding to the 15th floor. The sequence of the second fingerprint created is also corresponding to the 15th floor.

Specifically, in this embodiment, the environment data server uses the sensor information to obtain the second fingerprint database as an example for example. In other embodiments, the smart terminal may also obtain the acquired location. The second fingerprint database is sent to the environment data server, which is not limited in this embodiment.

More specifically, the environmental data server creates a second fingerprint library in a hidden markov model (HMM) based on the transition probability sequence acquired by the above steps and the output probability.

More specifically, the environmental data server shown in this embodiment may construct the second fingerprint database in the form of a search tree based on the output probability sequence and the transition probability sequence, wherein the environmental data server is based on a surveyor During the process of travel, the output probability of any zone unit passing through and the transition probability can construct a layer in the search tree.

Based on the first fingerprint database and the second fingerprint database shown in FIG. 5, the specific process of how the positioning engine implements the positioning of the terminal to be located through the first fingerprint database is described below with reference to FIG. 9 :

Step 901: The terminal to be located sends the target WiFi information to the positioning engine.

Step 902: The positioning engine receives the target WiFi information.

Step 903: The positioning engine calculates a target matching value of the positioning area unit.

Step 904: The positioning engine obtains a matching list.

Step 905: The positioning engine acquires the first positioning location according to the WiFi fingerprint matching algorithm.

The specific implementation process of the step 901 to the step 905 shown in this embodiment is shown in the step 401 to the step 405 as shown in FIG. 4, and the specific execution process is not described in this embodiment.

The indoor positioning method shown in this embodiment includes a first positioning phase and a second positioning phase. The first positioning phase is referred to as “rough positioning” and the second positioning phase is referred to as “fine positioning”. That is, in the first positioning phase (shown in steps 901 to 905), the initial indoor location (first positioning location) of the object to be located is determined by the WiFi matching positioning technique, and the first positioning phase is first. The positioning position is used as a center to define a to-be-positioned area in a circular shape, a positive direction, and the like, and then the geomagnetic matching technology is used to further calculate the precise position of the object to be positioned in the to-be-positioned area, and the second positioning stage is described by the following steps. The specific implementation process is described:

Step 906: The positioning engine determines an area to be located.

The area to be located is a frame to be positioned in a circular shape, a positive direction, or the like, as shown in the embodiment, and the area of the to-be-positioned area is relative to the above-mentioned positioning area. The area is reduced, and the positioning of the to-be-positioned area based on the reduced area is performed in the second positioning stage, thereby improving the accuracy of positioning.

In the case that the positioning engine determines the first positioning position, the positioning engine may determine the to-be-positioned area based on the first positioning position, which may be determined by the positioning engine. The shape of the to-be-positioned area is not limited in this embodiment. For example, the to-be-positioned area may be in the shape of a circle, a direction, or the like.

Continuing with the example shown in FIG. 7 , the location point 700 is the first positioning location Dx determined by the positioning engine via step 905, and the positioning engine may determine the to-be-positioned area 704. The center of the locating area 704 is the area to be located.

Step 907: The positioning engine acquires a sequence of sensor information.

After receiving the sensor information uploaded by the terminal to be located, the positioning engine shown in this embodiment may determine the sensor information sequence, where the sensor information sequence is that the to-be-positioned terminal is in the to-be-positioned area. The sensor information reported by the terminal to be located at the time of collecting the sensor information in units of the step size of the user.

Step 908: The positioning engine acquires the target area unit set by using the sensor information sequence.

Specifically, after the positioning engine acquires the sensor information sequence, the location information obtained in step 906 is geomagnetically matched with respect to the area to be located with the reduced area of the positioning area, thereby calculating the sensor information sequence and the location. The matching degree of all the positioning area units included in the positioning area is described.

More specifically, after the positioning engine acquires the sensor information sequence, the positioning engine determines, based on the Viterbi Algorithm, the second fingerprint database in the HMM, and the sensor information. a sequence of hidden states corresponding to the sequence, and the sequence of hidden states shown in this embodiment is the set of location area units, where the set of location area units is included in the positioning phase, and the user carrying the smart terminal sequentially For all the area units that have passed, it can be seen that the set of positioning area units shown in this embodiment includes the area units that pass through the front-to-back order in the chronological order of the smart terminal movement trajectories.

The positioning engine may determine, by using the sensor information sequence, a plurality of the positioning area unit sets having different probability values, and the positioning area unit set having different probability values represents a user carrying the smart terminal in a positioning stage. A plurality of possible travel trajectories are traveled, and the positioning engine shown in this embodiment can determine the set of locating area units having the largest probability value for positioning.

Step 909: The positioning engine determines a second positioning position.

After the positioning engine acquires the set of positioning area units, the positioning engine may determine that the actual position of the last area unit is the positioning position according to the time sequence elapsed by the user. Specifically, the positioning engine shown in this embodiment may determine the actual location of the last regional unit by querying the first fingerprint database.

Step 910: The positioning engine acquires a movement trajectory of the to-be-positioned terminal at a future time according to the second positioning position.

Specifically, the positioning engine shown in this embodiment uses the second positioning position as a starting position, and derives a moving trajectory of the to-be-positioned terminal at a future time according to a Pedestrian Dead Reckoning (PDR).

More specifically, the positioning engine may acquire data such as acceleration, angular velocity, magnetic force, and pressure during the traveling of the user carrying the terminal to be located based on the PDR algorithm, and the positioning engine may use the acquired data to the user. The calculation of the step size and the direction of the movement, so as to predict the movement trajectory of the user carrying the terminal to be located at a future time, the positioning engine can locate the to-be-positioned based on the movement trajectory of the terminal to be positioned at a future time The terminal provides location services.

By adopting the positioning method shown in this embodiment, the improved Viterbi algorithm positioning service of the HMM can effectively reduce the complexity and calculation amount of the geomagnetic matching, and improve the efficiency and accuracy of positioning the terminal to be positioned.

The indoor positioning method of the embodiment of the present application is described above. The indoor positioning method of the embodiment of the present application is described below with reference to a practical example. Please refer to FIG. 1 and FIG. 10, and FIG. 10 is an indoor application shown in the application. A schematic diagram of an indoor structure layout of a positioning method.

As shown in FIG. 1 , the positioning system includes positioning base stations 103 disposed at four corners of the positioning area, and each of the positioning base stations 103 can be fixed by using three brackets and externally connected with a lithium battery. The positioning system is further provided with an environmental data server 104 capable of communicating with the four corners of the positioning base station 103, which may be a computer, such as a portable computer such as a notebook computer, in the application scenario, in the environment The data server 104 is exemplified for the notebook computer. The environment data server 104 is configured to implement the indoor positioning function, and the environment data server 104 shown in the application scenario runs a UWB client program, thereby making the environment The data server 104 can receive the location information reported by the UWB positioning terminal 102 and the positioning base station 103 to the environment data server 104. The environment data server 104 runs a server program for data collection, and the server program for running data collection can The location information and the environmental information reported by the smart terminal 101 are received to generate an environmental fingerprint library.

In addition, for the person conducting the survey, the smart terminal 101 and the UWB positioning terminal 102 are worn on the body, and the manner in which the surveyor carries the smart terminal 101 is not limited. For example, the surveyor can place the smart terminal 101 in the pocket. The UWB positioning terminal 102 can be used to carry the UWB positioning terminal 102 in a plurality of manners, and the UWB positioning terminal 102 can be fixed on the top of the helmet by a lithium battery, and is manually powered by the lithium battery. The surveyor can wear the helmet. The advantage of carrying the UWB positioning terminal 102 in a helmet manner is that, on the one hand, the UWB positioning terminal 102 is not blocked by the human body, and the surveying personnel are more likely to be obstructed by obstacles during walking than other installation forms (eg, badges) On the other hand, the UWB positioning terminal 102 is placed on the top of the head and is closest to the actual motion track of the surveyor, and the disturbance caused by the motion is the smallest.

The physical arrow in FIG. 1 is a transmission path indicating that the smart terminal 101 reports the environmental information to the environmental data server 104, and the dotted arrow indicates the transmission path of the UWB positioning terminal 102 and the positioning base station 103 reporting the location information to the environmental data server 104. .

Figure 10 shows an example of the 5th floor of Area N4 of the Nanjing Research and Development Building of Huawei Research Institute. The box area of the 5th floor of Area 5 of the R&D building of Nanjing Research Institute of Huawei is selected (20 meters by car). The range of 13 meters is the location area 1001, the area is recorded as zone1, and four positioning base stations are arranged in the four corners of the zone 1. The description of the structure of the specific positioning base station is shown in FIG. 1 , and details are not described herein.

The positioning area 1001 includes 7 rows of stations, and the reachable area includes 1 long aisle and 6 vertical short aisles. Due to the limitation of the positioning range of the positioning base station, when the positioning range is expanded, the mobile positioning base station needs to be delineated to another positioning area. In order to cover all the reachable areas, the adjacent two positioning areas need to be partially overlapped, so that the phase is guaranteed to be in phase. The transition probability of the discretized lattice between adjacent positioning regions is continuous, thereby effectively ensuring the realization of indoor positioning.

The area of the plane area shown in Figure 10 is (43.5 m + 40 m) × 13 m. Therefore, it can be divided into 7 positioning areas, namely zone1, zone2, ..., zone7, each zone is collected for about 10 minutes. The environment information and the location information are used to generate the environment fingerprint database. For the specific process of the environment information, the location information, and the environment fingerprint database, please refer to the foregoing embodiment, and details are not described herein.

In this application scenario, the UWB positioning system can also be used as an error measurement tool for online positioning. Specifically, the surveying personnel carry the intelligent terminal, and at the same time wear the helmet equipped with the UWB positioning terminal, and walk freely within the deployment range of the positioning base station. The environment data server may further collect environment information of about 5 minutes in the location area 1001 and perform the simulation test on the location information to test the accuracy of positioning the terminal to be located in the location area 1001 and verify the manual survey. The validity of the data. The trajectory of the surveyor within the location area 1001 covers as much as possible of all aisles and reachable areas.

After the creation of the location area 1001, that is, the creation of the zone1 environment fingerprint database, the environment fingerprint database can be created for the zones 2, . . . , zone 7 in turn, and the entire survey of the area shown in FIG. 10 takes about 4 hours.

The results of the manual survey are composed of the environmental information and the location information shown in the above embodiment, and are saved in a CSV file. The data processing stage mainly processes the results of the manual survey stage to generate an environmental fingerprint. Specifically, in the data processing stage, the environmental data The server 104 first reads the CSV file, and divides the positioning area 1001 into a plurality of squares in advance, and each of the squares is the area unit shown in the above embodiment, and creates a fingerprint corresponding to each of the area units.

The environment data server divides the positioning area 1001 into a plurality of area units for the WiFi information, and each area unit is a 3 m×3 m grid, and the first fingerprint database created by the environment data server includes For the first positioning fingerprint corresponding to each area unit, the specific process is shown in the above embodiment.

The environment data server divides the positioning area 1001 into a grid of 0.3 m×0.3 m for each sensor information, and each grid serves as a regional unit, and creates a second fingerprint database based on the divided area units, and creates a specific description of the second fingerprint database. Please refer to the above embodiment for details, and details are not described herein.

After the environment data server creates the first fingerprint database and the second fingerprint database, when the terminal to be located is located in the positioning area 1001, the environment data server is based on the indoor positioning process shown in the above embodiment. The positioning server can be provided to the terminal to be located located in the positioning area 1001.

The embodiment of the present invention further provides a server. The server shown in this embodiment is used to execute the process of creating a first fingerprint database shown in FIG. 2 to FIG. 4, and realizing positioning of the terminal to be located through the first fingerprint database. For details, refer to the embodiment shown in FIG. 2 to FIG. 4. The specific implementation process is not described in this embodiment.

As shown in FIG. 11, the server shown in this embodiment includes:

The receiving unit 1101 is configured to receive the environment information that is sent by the terminal to be located in the location area, where the environment information is the information that is detected by the terminal to be located, and the location to be located is different when the location of the terminal to be located is different. The environmental information detected by the terminal is different;

The acquiring unit 1102 is configured to acquire an environmental fingerprint database corresponding to the positioning area, where the environmental fingerprint database includes at least one positioning fingerprint, the positioning area includes at least one area unit, wherein the target positioning fingerprint corresponds to the first area unit The target location fingerprint is one of the at least one location fingerprint, the first area unit is one of the at least one area unit, and the target location fingerprint includes target environment information and a target location. Information, the target environment information is environment information that is sent to the smart terminal in the first area unit, and the target location information is sent by the ultra-wideband UWB positioning system to instruct the smart terminal to send the target environment. Position coordinates of the information;

Specifically, the obtaining unit 1102 includes:

The first obtaining module 11021 is configured to: when the smart terminal moves in the positioning area, the smart terminal scans all the smart terminals scanned in the preset period during the preset period. Environment information and all location information reported by the UWB positioning system, wherein one of the location information is used to indicate location coordinates when the smart terminal sends one of the environmental information, the environment The information includes wireless fidelity WiFi information and/or sensor information, the WiFi information including a media medium control MAC address and received signal strength indicator RSSI data of each wireless network access point AP scanned by the smart terminal, the sensor The information is information collected by the sensor of the smart terminal;

The first processing module 11022 is configured to determine target location information according to all the location information reported by the UWB positioning system, where the location coordinate indicated by the target location information is located in the first regional unit;

The second processing module 11023 is configured to determine target environment information according to the all the environment information reported by the smart terminal, where the target environment information is environment information reported by the smart terminal in the first area unit;

The third processing module 11024 is configured to determine that the target positioning fingerprint is a positioning fingerprint that includes the target location information and the target environment information.

More specifically, the target environment information includes the WiFi information, and the third processing module 11024 includes:

The first calculation sub-module 110241 is configured to count the total number of samples of all APs scanned by the smart terminal in the first area unit.

a second calculation sub-module 110242, configured to calculate an occurrence probability of the first target AP, chanceP(MACi), by using the following formula;

The first determining sub-module 110243 is configured to determine that the target positioning fingerprint includes a first positioning fingerprint, where the first positioning fingerprint includes an appearance probability earthquake(MAC _i ) of the first target AP.

a first acquisition sub-module 110244, configured to acquire a target RSSI sequence of the first target AP, where the target RSSI sequence includes an RSSI scanned by the first target AP each time by the smart terminal;

a third calculation sub-module 110245, configured to calculate a probability density function Norm (RSSI) of a single target Gaussian distribution model GSM according to the following formula;

a fourth calculation sub-module 110246, configured to calculate a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP according to the following formula;

The second determining submodule 110247 is configured to determine that the first positioning fingerprint includes a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP.

a third determining sub-module 110248, configured to determine a location coordinate of the target location, where the target location is located at any location within the first regional unit;

The fourth determining submodule 110249 is configured to determine that the first positioning fingerprint includes location coordinates of the target location.

The environment information is the WiFi information that is scanned by the terminal to be located in the target time period, and the server further includes:

The first calculating unit 1103 is configured to: if the MAC address of any AP included in the environment information is the same as the MAC address of an AP included in the first positioning fingerprint, calculate the first target sub-match value by using the following formula Px;

Px=log ₁₀ (occurenceP(MAC _i ).gmNorm(RSSI));

a second calculating unit 1104, configured to calculate a matching value corresponding to the first area unit according to the following formula;

Matching value

The third calculating unit 1105 is configured to: if the MAC address of any AP included in the environment information is different from the MAC address of any AP included in the first positioning fingerprint, calculate the second target by using the following formula Sub-match value Py;

Py=log ₁₀ (1-occurenceP(MAC _i ));

a fourth calculating unit 1106, configured to calculate a matching value corresponding to the first area unit according to the following formula;

Matching value

The matching unit 1107 is configured to acquire a positioning location coordinate corresponding to the environment information in the environment fingerprint database, where the positioning location coordinate is a location coordinate of the terminal to be located in the positioning area;

Specifically, the matching unit 1107 includes:

The second obtaining module 11071 is configured to obtain a matching list, where the matching list includes all the regional units included in the positioning area, and all the regional units included in the matching list are large to small according to the matching value. Sort in order;

a third obtaining module 11072, configured to acquire, in the matching list, a position coordinate wi of the target position corresponding to any one of the regional units in the first N bits;

The fourth obtaining module 11073 is configured to calculate the first positioning position coordinate Dx by the following formula;

The determining module 11074 is configured to determine that the positioning position coordinate is the first positioning position coordinate Dx.

For the description of the beneficial effects of the indoor positioning, the embodiment shown in FIG. 2 to FIG. 4 is used for the description of the configuration of the server shown in this embodiment, and details are not described in detail in this embodiment.

Another structure of the server provided by the embodiment of the present invention is exemplarily described below with reference to FIG. 12, wherein the server shown in FIG. 12 is used for execution.

The server shown in this embodiment is configured to perform the positioning of the terminal to be located by using the first fingerprint database and the second fingerprint database, as shown in FIG. 5 and FIG. 9 . For the specific process, the specific implementation process is shown in FIG. 5 and the embodiment shown in FIG. 9. The specific implementation process is not described in this embodiment.

As shown in FIG. 12, the server shown in this embodiment includes:

The receiving unit 1201 is configured to receive the environment information that is sent by the terminal to be located in the location area, where the environment information is the information that is detected by the terminal to be located, and the location to be located is different when the location of the terminal to be located is different. The environmental information detected by the terminal is different;

The obtaining unit 1202 is configured to acquire an environment fingerprint database corresponding to the positioning area, where the environment fingerprint database includes at least one positioning fingerprint, the positioning area includes at least one area unit, wherein the target positioning fingerprint corresponds to the first area unit The target location fingerprint is one of the at least one location fingerprint, the first area unit is one of the at least one area unit, and the target location fingerprint includes target environment information and a target location. Information, the target environment information is environment information that is sent to the smart terminal in the first area unit, and the target location information is sent by the ultra-wideband UWB positioning system to instruct the smart terminal to send the target environment. Position coordinates of the information;

Specifically, the obtaining unit 1202 includes:

The first obtaining module 12021 is configured to: when the smart terminal moves in the positioning area, the smart terminal scans all the smart terminals scanned in the preset period in the preset period Environment information and all location information reported by the UWB positioning system, wherein one of the location information is used to indicate location coordinates when the smart terminal sends one of the environmental information, the environment The information includes wireless fidelity WiFi information and/or sensor information, the WiFi information including a media medium control MAC address and received signal strength indicator RSSI data of each wireless network access point AP scanned by the smart terminal, the sensor The information is information collected by the sensor of the smart terminal;

The first processing module 12022 is configured to determine target location information according to the location information reported by the UWB positioning system, where location coordinates indicated by the target location information are located in the first regional unit;

The second processing module 12023 is configured to determine target environment information according to the all the environment information reported by the smart terminal, where the target environment information is environment information reported by the smart terminal in the first area unit;

The third processing module 12024 is configured to determine that the target positioning fingerprint is a positioning fingerprint that includes the target location information and the target environment information.

The third processing module 12024 creates a description of the specific structure of the first positioning fingerprint, which is shown in FIG. 11 , which is not described in detail in this embodiment, and the target is shown in the embodiment. The third processing module 12024 is further configured to: determine that the target positioning fingerprint includes the first positioning fingerprint and the second positioning fingerprint, where the environment information includes the WiFi information and the sensor information. The second positioning fingerprint is a positioning fingerprint of the hidden Markov model HMM acquired according to the sensor information.

To implement an indoor positioning process based on the second fingerprint database, the server further includes:

a fifth calculating unit 1203, configured to calculate a transition probability of the first regional unit by using a transition probability transitionP(STEP _i ) for performing training to obtain the second localized fingerprint;

a sixth calculating unit 1204, configured to calculate a target traveling direction matching degree azimuthMatch _m in the first area unit according to the following formula, the azimuthMatch _m is a surveying personnel carrying the smart terminal in the first area unit, along the a direction of travel matching when the target traveling direction m is moved, the target traveling direction m being any direction in which the smart terminal moves within the first area unit;

a first processing unit 1205, configured to acquire target geomagnetic information, where the target geomagnetic information is a kth step of moving by a surveying personnel carrying the smart terminal, where the smart terminal is in the first regional unit Geomagnetic information included in the reported sensor information, the target geomagnetism information includes a first component value magE, a second component value magN, a third component value magU, and a geomagnetism precision value magVal, wherein the first component value magE is In the center coordinate system ENU, along the X-direction component value parallel to the horizontal plane, the second component value magN is the Y-direction component value parallel to the horizontal plane under the ENU, and the third component value magU is under the ENU a vertical component value in the Z direction perpendicular to the horizontal plane; the geomagnetic accuracy value magVal represents the measurement accuracy;

The second processing unit 1206 is configured to determine a preset input set X according to the target geomagnetic information, where X={X ₁ =1, X ₂ =magE, X ₃ =magN, X ₄ =magU, X ₅ =magVal, X ₆ =azimthMatch _m };

a third processing unit 1207, configured to calculate, by using the following formula, a target history matching degree matchHistory _m corresponding to the target traveling direction in the first area unit;

among them,

a fourth processing unit 1208, configured to calculate an output probability matchValue(grld _j ) of the first regional unit according to the following formula

The fifth processing unit 1209 is configured to create a second positioning fingerprint of the hidden Markov model HMM based on the transition probability of the first regional unit and the output probability.

The matching unit 1210 is configured to acquire a positioning location coordinate corresponding to the environment information in the environment fingerprint database, where the positioning location coordinate is a location coordinate of the to-be-positioned terminal in the positioning area;

Specifically, the matching unit 1210 includes:

The first determining module 12101 is configured to determine an area to be located, where a coordinate of a position included in the to-be-positioned area is the first positioning position coordinate Dx, and an area of the to-be-positioned area is smaller than an area of the positioning area. ;

The second determining module 12102 is configured to acquire a sequence of sensor information sent by the terminal to be located, where the sensor information sequence includes target sensor information and a target reporting time point, where the target sensor information is the to-be-located terminal in the to-be-positioned area And at least one of the reported at least one sensor information, where the target reporting time point is a time point at which the to-be-targeted terminal reports the target sensor information;

a third determining module 12103, configured to determine, according to a Viterbi algorithm, a set of positioning area units corresponding to the sensor information sequence and having different probability values, where the positioning area unit set includes the During the moving process of the intelligent terminal, at least one area unit passes through the chronological order in order from the front to the back;

a fourth determining module 12104, configured to determine a second positioning position, where the second positioning position is the positioning area unit having the highest probability value, and is sorted at any position included in the last area unit;

The fifth determining module 12105 is configured to determine that the positioning position coordinate is the second positioning position coordinate.

The prediction unit 1211 is configured to use the second positioning position coordinate as a starting position, and determine, according to the pedestrian dead reckoning PDR, a movement trajectory of the to-be-positioned terminal at a future time.

For the description of the beneficial effects of performing the indoor positioning by using the structure of the server shown in this embodiment, please refer to the embodiment shown in FIG. 5 and FIG. 9 , which is not specifically described in this embodiment.

The specific structure of the server is exemplified from the perspective of the physical hardware in FIG. 13 . As shown in FIG. 13 , the server 1300 includes:

Receiver 1302, transmitter 1303, one or more processors 1301, and memory 1304. In some embodiments of the present invention, the receiver 1302, the transmitter 1303, the one or more processors 1301, and the memory 1304 may be connected by a bus or other means, wherein the bus connection is taken as an example in FIG.

Wherein the one or more programs are stored in the memory 1304, the one or more programs including instructions that, when executed by the server, cause the server to perform an indoor as shown in the above embodiments For the specific implementation process, please refer to the above description, which is not described in detail in this embodiment.

Embodiments of the present invention also provide a computer readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a server, cause the server to execute as in the above embodiment For the specific positioning process, please refer to the above description, which is not described in detail in this embodiment.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, it may be implemented in whole or in part in the form of a computer program product.

The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in accordance with embodiments of the present invention are generated in whole or in part. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be from a website site, computer, server or data center Transfer to another website site, computer, server, or data center by wire (eg, coaxial cable, fiber optic, digital subscriber line (DSL), or wireless (eg, infrared, wireless, microwave, etc.). The computer readable storage medium can be any available media that can be stored by a computer or a data storage device such as a server, data center, or the like that includes one or more available media. The usable medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (such as a solid state disk (SSD)).

A person skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the system, the device and the unit described above can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.

In the several embodiments provided by the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in the embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application, in essence or the contribution to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium. A number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like, which can store program codes. .

The above embodiments are only used to explain the technical solutions of the present application, and are not limited thereto; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that they can still The technical solutions described in the embodiments are modified, or equivalent to some of the technical features are included; and the modifications or substitutions do not deviate from the technical solutions of the embodiments of the present application.

Claims

An indoor positioning method, comprising:

Receiving the environment information that is sent by the terminal to be located in the location area, where the environment information is information detected by the terminal to be located, and when the location of the terminal to be located is different, the terminal to be located is detected by the terminal to be located. Different environmental information;

Acquiring an environment fingerprint database corresponding to the location area, where the environment fingerprint database includes at least one location fingerprint, the location area includes at least one area unit, wherein the target location fingerprint corresponds to the first area unit, and the target location fingerprint Locating a fingerprint for one of the at least one positioning fingerprint, the first area unit being one of the at least one area unit, the target positioning fingerprint comprising target environment information and target position information, the target environment The information is environment information that is sent to the smart terminal in the first area unit, and the target location information is a location coordinate that is sent by the ultra-wideband UWB positioning system to indicate that the smart terminal sends the target environment information;

Obtaining a positioning location coordinate corresponding to the environment information in the environment fingerprint database, where the positioning location coordinate is a location coordinate of the to-be-positioned terminal in the positioning area.
The method of claim 1 further comprising:

Obtaining all environmental information and the UWB positioning system scanned by the smart terminal in the preset period reported by the smart terminal during a preset period in the process of acquiring the smart terminal moving in the positioning area All the location information reported, one of the location information is used to indicate location coordinates when the smart terminal sends one of the environmental information, the environment information includes wireless fidelity WiFi information and And/or sensor information, where the WiFi information includes a media medium control MAC address and a received signal strength indicator RSSI data of each wireless network access point AP scanned by the smart terminal, where the sensor information is a sensor of the smart terminal Information collected;

Determining target location information according to all the location information reported by the UWB positioning system, where location coordinates indicated by the target location information are located in the first regional unit;

Determining the target environment information according to the all the environment information reported by the smart terminal, where the target environment information is environment information reported by the smart terminal in the first area unit;

Determining the target location fingerprint is a location fingerprint including the target location information and the target environment information.
The method according to claim 2, wherein the target environment information comprises the WiFi information, and the determining the target positioning fingerprint is a positioning fingerprint including the target location information and the target environment information. include:

Counting the total number of samples of all APs scanned by the smart terminal in the first area unit
And a sampling number N i of the first target AP, where the first target AP is the i-th AP scanned by the smart terminal in the first area unit, and the first area unit is The number of APs scanned by the smart terminal is n, the i and the n are positive integers greater than or equal to 1, and the i is less than or equal to the n;

Calculating an occurrence probability of the first target AP, chanceP(MAC i ), by using the following formula;

Determining that the target positioning fingerprint comprises a first positioning fingerprint, the first positioning fingerprint comprising an occurrence probability of the first target AP (PerformanceP(MAC i )).
The method according to claim 3, wherein the determining the target positioning fingerprint as the positioning fingerprint including the target location information and the target environment information comprises:

Obtaining a target RSSI sequence of the first target AP, where the target RSSI sequence includes an RSSI scanned by the first target AP each time by the smart terminal;

Calculating a probability density function Norm (RSSI) of a single target Gaussian distribution model GSM according to the following formula;

Wherein, the μ is the mean of the target RSSI sequence, and σ is the standard deviation of the target RSSI sequence;

Calculating a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP according to the following formula;

Where π k is a preset weighting coefficient, and the K is a positive integer greater than or equal to 1;

Determining that the first positioning fingerprint comprises a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP.
The method according to claim 4, wherein the determining the target positioning fingerprint as the positioning fingerprint including the target location information and the target environment information comprises:

Determining a position coordinate of the target position, the target position being at any position within the first area unit;

Determining that the first location fingerprint includes location coordinates of the target location.
The method according to claim 5, wherein the environment information is WiFi information scanned by the terminal to be located within a target time period, and the obtaining the environment fingerprint database and the environment information Before the corresponding positioning position coordinates, the method further includes:

If the MAC address of any AP included in the environment information is the same as the MAC address of an AP included in the first positioning fingerprint, the first target sub-match value Px is calculated by the following formula;

Px=log 10 (occurenceP(MAC i ).gmNorm(RSSI));

Calculating a matching value corresponding to the first area unit according to the following formula;

Matching value
The method according to claim 6, wherein the method further comprises: before acquiring the location location coordinates of the environment fingerprint database corresponding to the environment information, the method further comprising:

If the MAC address of any AP included in the environment information is different from the MAC address of any AP included in the first location fingerprint, the second target sub-match value Py is calculated by the following formula;

Py=log 10 (1-occurenceP(MAC i ));

Calculating a matching value corresponding to the first area unit according to the following formula;

Matching value
The method according to claim 7, wherein the acquiring the location location coordinates corresponding to the environment information in the environment fingerprint database comprises:

Obtaining a matching list, where the matching list includes all the area units included in the positioning area, and all the area units included in the matching list are sorted in descending order of the matching value;

Obtaining, in the matching list, a position coordinate wi of the target position corresponding to any one of the area units of the first N bits;

Calculating the first positioning position coordinate Dx by the following formula;

Determining the positioning position coordinate is the first positioning position coordinate Dx.
The method according to claim 8, wherein the target environment information includes the WiFi information and the sensor information, and the determining the target positioning fingerprint includes the target location information and the target The location fingerprint of the environmental information includes:

Determining that the target positioning fingerprint comprises the first positioning fingerprint and the second positioning fingerprint, and the second positioning fingerprint is a positioning fingerprint of the hidden Markov model HMM acquired according to the sensor information.
The method of claim 9 wherein the method further comprises:

Calculating a transition probability transitionP(STEP i ) of the first area unit by using a formula, the transition probability transitionP(STEP i ) is used for training to obtain the second positioning fingerprint;

Wherein, the numerator is transferred to the i-th second area unit in a process of moving the kth step of the movement of the surveyor carrying the smart terminal in the first area unit, wherein the smart terminal is in the first The number of times the sensor information reported in the area unit is sampled, the second location area is a area unit adjacent to the first area unit in the location area, and the number of the second area unit is n And the n and the k are positive integers greater than or equal to 1, and the denominator is a process in which the smart terminal located in the first area unit moves to all the second area units, the smart terminal The total number of times the sensor information reported in the first area unit is sampled.
The method of claim 10, wherein the method further comprises:

Calculating a target traveling direction matching degree azimuthMatch m in the first area unit according to the following formula, the azimuthMatc m h is a surveying personnel carrying the smart terminal moving in the target traveling direction m in the first area unit a traveling direction matching degree, wherein the target traveling direction m is any direction in which the smart terminal moves within the first area unit;

Wherein the minDiff is a deviation angle formed between any direction included in the target direction sequence midAzi and the target heading Azimuth, and the target heading Azimuth is a k-1 step step for the surveyor carrying the intelligent terminal a probability of moving into the first area unit, the target direction sequence midAzi including the target traveling direction and a target time period, wherein the target time period is that the smart terminal is within the first area unit a period of time during which the target travel direction moves;

Acquiring the geomagnetism information, wherein the target geomagnetic information is the kth step of the movement of the surveyor carrying the smart terminal, and the smart terminal reports the geomagnetism included in the sensor information in the first regional unit Information, the target geomagnetism information includes a first component value magE, a second component value magN, a third component value magU, and a geomagnetism precision value magVal, wherein the first component value magE is under the center coordinate system ENU, In the X-direction component value parallel to the horizontal plane, the second component value magN is a Y-direction component value parallel to the horizontal plane under the ENU, and the third component value magU is perpendicular to the Z-direction perpendicular to the horizontal plane under the ENU. Component value; the geomagnetic accuracy value magVal represents measurement accuracy;

Determining a preset input set X according to the target geomagnetic information, where X={X 1 =1, X 2 =magE, X 3 =magN, X 4 =magU, X 5 =magVal,X 6 =azimthMatch m };

Calculating a target history matching degree matchHistory m corresponding to the target traveling direction in the first area unit by using a formula;

among them,
Representing an S-type growth curve sigmoid function for the six target parameter sets X i W i , the target parameter set X i W i comprising a first parameter X i and a second parameter W i , wherein the first parameter X i is Any parameter included in the preset input set, the second parameter W i being a weight value corresponding to the first parameter X i ;

Calculating the output probability matchValue(grld j ) of the first area unit according to the following formula

Wherein, grld j represents the first regional unit, M represents the number of historical matching degrees of the first regional unit, and the target historical matching degree matchHistory m represents any historical matching degree of the M historical matching degrees. ;

A second localized fingerprint that is a hidden Markov model HMM is created based on the transition probability of the first regional unit and the output probability.
The method according to any one of claims 9 to 11, wherein after the first positioning position coordinate Dx is calculated by the following formula, the method further comprises:

Determining an area to be located, wherein a coordinate of a position included in the to-be-positioned area is the first positioning position coordinate Dx, and an area of the to-be-positioned area is smaller than an area of the positioning area;

Acquiring a sequence of sensor information sent by the terminal to be located, the sensor information sequence includes target sensor information and a target reporting time point, where the target sensor information is at least one sensor reported by the terminal to be located in the to-be-positioned area Any one of the information, the target reporting time point is a time point at which the to-be-targeted terminal reports the target sensor information;

Determining, according to the Viterbi algorithm, a set of positioning area units corresponding to the sensor information sequence and having different probability values, the set of positioning area units including the passing of the smart terminal during the moving process The chronological order passes through at least one area unit in order from front to back;

Determining a second positioning position, wherein the second positioning position is the positioning area unit having the highest probability value, and sorting is performed at any position included in the last area unit;

Determining the positioning position coordinate is the second positioning position coordinate.
The method according to claim 12, wherein after the determining the second positioning position, the method further comprises:

Taking the second positioning position coordinate as a starting position, determining a movement trajectory of the to-be-positioned terminal at a future time according to the pedestrian dead reckoning PDR.
A server, comprising:

a receiving unit, configured to receive environment information that is sent by the terminal to be located in the location area, where the environment information is information detected by the terminal to be located, and when the location of the terminal to be located is different, the terminal to be located is The detected environmental information is different;

An acquiring unit, configured to acquire an environment fingerprint database corresponding to the positioning area, where the environment fingerprint database includes at least one positioning fingerprint, the positioning area includes at least one area unit, wherein the target positioning fingerprint corresponds to the first area unit, The target location fingerprint is one of the at least one location fingerprint, the first area unit is one of the at least one area unit, and the target location fingerprint includes target environment information and target location information. The target environment information is environment information that is sent to the smart terminal in the first area unit, where the target location information is sent by the ultra-wideband UWB positioning system to instruct the smart terminal to send the target environment information. Position coordinates

And a matching unit, configured to acquire a positioning location coordinate corresponding to the environment information in the environment fingerprint database, where the positioning location coordinate is a location coordinate of the terminal to be located in the positioning area.
The server according to claim 14, wherein the obtaining unit comprises:

a first acquiring module, configured to acquire, in a process of moving the smart terminal in the positioning area, all environments scanned by the smart terminal in the preset period reported by the smart terminal every preset period Information and all location information reported by the UWB positioning system, wherein one of the location information is used to indicate location coordinates when the smart terminal sends one of the environmental information, the environmental information Included with wireless fidelity WiFi information and/or sensor information, the WiFi information including a media medium control MAC address and received signal strength indicator RSSI data of each wireless network access point AP scanned by the smart terminal, the sensor information Information collected by the sensor of the smart terminal;

a first processing module, configured to determine target location information according to all the location information reported by the UWB positioning system, where location coordinates indicated by the target location information are located in the first regional unit;

a second processing module, configured to determine target environment information according to the all the environment information reported by the smart terminal, where the target environment information is environment information reported by the smart terminal in the first area unit;

And a third processing module, configured to determine that the target positioning fingerprint is a positioning fingerprint that includes the target location information and the target environment information.
The server according to claim 15, wherein the target environment information comprises the WiFi information, and the third processing module comprises:

a first calculation submodule, configured to count the total number of samples of all APs scanned by the smart terminal in the first area unit
And a sampling number N i of the first target AP, where the first target AP is the i-th AP scanned by the smart terminal in the first area unit, and the first area unit is The number of APs scanned by the smart terminal is n, the i and the n are positive integers greater than or equal to 1, and the i is less than or equal to the n;

a second calculation submodule, configured to calculate an occurrence probability of the first target AP, chanceP(MAC i ), by using the following formula;

And a first determining submodule, configured to determine that the target positioning fingerprint includes a first positioning fingerprint, where the first positioning fingerprint includes an appearance probability earthquake(MAC i ) of the first target AP.
The server according to claim 16, wherein the third processing module comprises:

a first acquisition sub-module, configured to acquire a target RSSI sequence of the first target AP, where the target RSSI sequence includes an RSSI scanned by the first target AP by the smart terminal;

a third calculation submodule, configured to calculate a probability density function Norm (RSSI) of a single target Gaussian distribution model GSM according to the following formula;

Wherein, the μ is the mean of the target RSSI sequence, and σ is the standard deviation of the target RSSI sequence;

a fourth calculation submodule, configured to calculate a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP according to the following formula;

Where π k is a preset weighting coefficient, and the K is a positive integer greater than or equal to 1;

And a second determining submodule, configured to determine that the first positioning fingerprint includes a Gaussian mixture distribution function gmNorm (RSSI) of the first target AP.
The server according to claim 17, wherein the third processing module comprises:

a third determining submodule, configured to determine a location coordinate of the target location, where the target location is located at any location within the first regional unit;

And a fourth determining submodule, configured to determine that the first positioning fingerprint includes location coordinates of the target location.
The server according to claim 18, wherein the environment information is WiFi information scanned by the terminal to be located in a target time period, and the server further includes:

a first calculating unit, configured to: if the MAC address of any AP included in the environment information is the same as the MAC address of an AP included in the first positioning fingerprint, calculate the first target sub-match value Px by using the following formula ;

Px=log 10 (occurenceP(MAC i ).gmNorm(RSSI));

a second calculating unit, configured to calculate a matching value corresponding to the first area unit according to the following formula;

Matching value
The server according to claim 19, wherein the server further comprises:

a third calculating unit, configured to: if the MAC address of any AP included in the environment information is different from the MAC address of any AP included in the first positioning fingerprint, calculate the second target by using the following formula Matching value Py;

Py=log 10 (1-occurenceP(MAC i ));

a fourth calculating unit, configured to calculate a matching value corresponding to the first area unit according to the following formula;

Matching value
The server according to claim 20, wherein the matching unit comprises:

a second obtaining module, configured to obtain a matching list, where the matching list includes all the regional units included in the positioning area, and all the regional units included in the matching list are in descending order of the matching value put in order;

a third obtaining module, configured to acquire, in the matching list, a position coordinate wi of the target position corresponding to any one of the regional units in the first N-bit area unit;

a fourth obtaining module, configured to calculate a first positioning position coordinate Dx by the following formula;

And a determining module, configured to determine that the positioning position coordinate is the first positioning position coordinate Dx.
The server according to claim 21, wherein the target environment information includes the WiFi information and the sensor information, and the third processing module is further configured to: determine that the target positioning fingerprint comprises the first a positioning fingerprint and a second positioning fingerprint, wherein the second positioning fingerprint is a positioning fingerprint of the hidden Markov model HMM acquired according to the sensor information.
The server according to claim 22, wherein the server further comprises:

a fifth calculating unit, configured to calculate a transition probability transitionP(STEP i ) of the first area unit by using a formula, the transition probability transitionP(STEP i ) is used for training to obtain the second positioning fingerprint;

Wherein, the numerator is transferred to the i-th second area unit in a process of moving the kth step of the movement of the surveyor carrying the smart terminal in the first area unit, wherein the smart terminal is in the first The number of times the sensor information reported in the area unit is sampled, the second location area is a area unit adjacent to the first area unit in the location area, and the number of the second area unit is n And the n and the k are positive integers greater than or equal to 1, and the denominator is a process in which the smart terminal located in the first area unit moves to all the second area units, the smart terminal The total number of times the sensor information reported in the first area unit is sampled.
The server according to claim 23, wherein the server further comprises:

a sixth calculating unit, configured to calculate a target traveling direction matching degree azimuthMatch m in the first area unit according to the following formula, wherein the azimuthMatch m is a surveying personnel carrying the smart terminal in the first area unit, along the target a traveling direction matching degree when the traveling direction m is moved, wherein the target traveling direction m is any direction in which the smart terminal moves in the first area unit;

Wherein the minDiff is a deviation angle formed between any direction included in the target direction sequence midAzi and the target heading Azimuth, and the target heading Azimuth is a k-1 step step for the surveyor carrying the intelligent terminal a probability of moving into the first area unit, the target direction sequence midAzi including the target traveling direction and a target time period, wherein the target time period is that the smart terminal is within the first area unit a period of time during which the target travel direction moves;

a first processing unit, configured to acquire target geomagnetic information, wherein the target geomagnetic information is in a process of moving the kth step of the surveying personnel of the smart terminal, where the smart terminal is located in the first regional unit And reporting the geomagnetism information included in the sensor information, the target geomagnetism information including a first component value magE, a second component value magN, a third component value magU, and a geomagnetism precision value magVal, wherein the first component value magE is In the center coordinate system ENU, along the X-direction component value parallel to the horizontal plane, the second component value magN is a value of the Y-direction component parallel to the horizontal plane under the ENU, and the third component value magU is under the ENU. a vertical component value in the Z direction perpendicular to the horizontal plane; the geomagnetic accuracy value magVal represents the measurement accuracy;

a second processing unit, configured to determine a preset input set X according to the target geomagnetic information, where X={X 1 =1, X 2 =magE, X 3 =magN, X 4 =magU, X 5 =magVal,X 6 =azimthMatch m };

a third processing unit, configured to calculate, by using the following formula, a target history matching degree matchHistory m corresponding to the target traveling direction in the first area unit;

among them,
Representing an S-type growth curve sigmoid function for the six target parameter sets X i W i , the target parameter set X i W i comprising a first parameter X i and a second parameter W i , wherein the first parameter X i is Any parameter included in the preset input set, the second parameter W i being a weight value corresponding to the first parameter X i ;

a fourth processing unit, configured to calculate an output probability matchValue(grld j ) of the first area unit according to the following formula

Wherein, grld j represents the first regional unit, M represents the number of historical matching degrees of the first regional unit, and the target historical matching degree matchHistory m represents any historical matching degree of the M historical matching degrees. ;

And a fifth processing unit, configured to create a second positioning fingerprint that is a hidden Markov model HMM based on the transition probability of the first regional unit and the output probability.
The server according to any one of claims 21 to 24, wherein the matching unit further comprises:

a first determining module, configured to determine an area to be located, where a coordinate of a position included in the to-be-positioned area is the first positioning position coordinate Dx, and an area of the to-be-positioned area is smaller than an area of the positioning area;

a second determining module, configured to acquire a sequence of sensor information sent by the terminal to be located, where the sensor information sequence includes target sensor information and a target reporting time point, where the target sensor information is that the terminal to be located is in the to-be-positioned area And any one of the reported at least one sensor information, where the target reporting time point is a time point at which the to-be-targeted terminal reports the target sensor information;

a third determining module, configured to determine, according to a Viterbi algorithm, a set of positioning area units corresponding to the sensor information sequence and having different probability values, where the positioning area unit set includes the smart During the moving of the terminal, at least one area unit passes through the chronological order in order from the front to the back;

a fourth determining module, configured to determine a second positioning position, where the second positioning position is the positioning area unit having the highest probability value, and is sorted at any position included in the last area unit;

And a fifth determining module, configured to determine that the positioning position coordinate is the second positioning position coordinate.
The server according to claim 25, wherein the server further comprises:

And a prediction unit, configured to use the second positioning position coordinate as a starting position, and determine, according to the pedestrian dead reckoning PDR, a movement trajectory of the to-be-positioned terminal at a future time.
A positioning system, comprising: a server, a terminal to be located, an intelligent terminal, and an ultra-wideband UWB positioning system, the server being as shown in any one of claims 14 to 26;

The to-be-located terminal is used to send the environment information to the server in the location area, where the environment information is the information detected by the terminal to be located, and the location to be located is different when the location of the to-be-located terminal is different. The environmental information detected by the terminal is different;

The server is configured to acquire an environment fingerprint database corresponding to the location area, where the environment fingerprint database includes at least one location fingerprint, the location area includes at least one area unit, where the target location fingerprint corresponds to the first area unit, The target location fingerprint is one of the at least one location fingerprint, the first area unit is one of the at least one area unit, and the target location fingerprint includes target environment information and target location information. The target environment information is environment information that is sent to the smart terminal in the first area unit, where the target location information is sent by the UWB positioning system to instruct the smart terminal to send the target. Position coordinates when environmental information;

The server is further configured to acquire, in the environment fingerprint database, location location coordinates corresponding to the environment information, where the location location coordinates are location coordinates of the to-be-positioned terminal in the location area.
A server, comprising:

One or more processors, memories, bus systems, and one or more programs, the processors and the memory being coupled by the bus system;

Wherein the one or more programs are stored in the memory, the one or more programs comprising instructions that, when executed by the server, cause the server to perform any of claims 1 to 13 Said method.
A computer readable storage medium storing one or more programs, wherein the one or more programs include instructions that, when executed by a server, cause the server to perform any of claims 1 to 13 The method described in the item.