CN111698774A - Indoor positioning method and device based on multi-source information fusion - Google Patents

Indoor positioning method and device based on multi-source information fusion Download PDF

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CN111698774A
CN111698774A CN202010583946.0A CN202010583946A CN111698774A CN 111698774 A CN111698774 A CN 111698774A CN 202010583946 A CN202010583946 A CN 202010583946A CN 111698774 A CN111698774 A CN 111698774A
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positioning
bluetooth
base station
bluetooth base
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CN111698774B (en
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王刚刚
李素敏
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Beijing Maiding Aite Technology Co ltd
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Beijing Maiding Aite Technology Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0257—Hybrid positioning
    • G01S5/0263—Hybrid positioning by combining or switching between positions derived from two or more separate positioning systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication

Abstract

The invention relates to an indoor positioning method and device based on multi-source information fusion, belonging to the technical field of indoor positioning, wherein the method comprises the following steps: performing Bluetooth positioning based on the collected Bluetooth base station signals and the collected Bluetooth base station data to obtain a Bluetooth positioning result; carrying out dead reckoning on the basis of the collected course information and acceleration information to obtain a current motion track; judging whether the current motion track meets the multi-source information fusion positioning condition; if not, adopting the Bluetooth positioning result as an indoor positioning result; and if the result is consistent with the result, performing fusion positioning combining Bluetooth positioning, dead reckoning and geomagnetic matching positioning, and taking the fusion positioning result as an indoor positioning result. The fusion position method can achieve the positioning precision superior to 1.4 meters under the probability of 60 percent; when the fusion positioning can not be used, the Bluetooth positioning method can also realize the positioning precision superior to 2 meters under the probability of 60 percent.

Description

Indoor positioning method and device based on multi-source information fusion
Technical Field
The invention relates to the technical field of indoor positioning, in particular to an indoor positioning method and device based on multi-source information fusion.
Background
With the large number of applications of mobile smart terminal devices represented by smart phones, Location Based Services (LBS) are increasingly widely used, such as services for navigation, takeout, etc. of traveling vehicles, but these demands are mainly based on satellite signals represented by GPS. For satellite signals, to achieve high-precision positioning, at least four satellite signals need to be received simultaneously, but in urban areas, valleys and indoor environments where high buildings stand, the satellite signals are affected by multipath, particularly shading and other factors, and positioning is almost impossible. Statistically, most LBS users are in the room 70% -90% of the time, and the commercial activities are also mostly concentrated in indoor scenarios, such as business overload; in addition, with the development of 5G, the positioning requirements of industrial scene personnel and equipment are more and more extensive. Therefore, the positioning requirement in the environment without satellite signals such as indoor environment is more and more urgent.
Aiming at the wide requirements of LBS, different research institutions propose different positioning technologies, and for smart phones, technologies such as WiFi, Bluetooth, magnetic fields, inertia and the like are mainly adopted at present. With the maturity of IEEE502.11 standard, WiFi access devices (APs) are widely used, and WiFi-based positioning technology is also widely researched, and common WiFi positioning means include a fingerprint method, a triangulation method, and the like. However, as weak current construction is required during AP installation, troubles are brought to installation and deployment, the AP deployment density is generally low, and the positioning accuracy is limited. The bluetooth technical association introduced the bluetooth version 4.0 in 2010, and the obvious characteristics of the bluetooth technical association are that the power consumption is low, the equipment is small, and the bluetooth technical association is an ideal positioning beacon. In the indoor environment, because the building structure contains a large amount of ferromagnetic materials, the magnetic field characteristics are abundant for the indoor environment, and the magnetic field characteristics can be used as a natural positioning means. An Inertial Navigation System (INS) is an independent navigation means, which mainly uses an accelerometer and a gyroscope to provide continuous and high-frequency position output, but is based on the mathematical principle of integral solution, and a small error of a sensor can bring a huge error under the time accumulation effect, especially a low-precision micro inertial navigation unit (MEMS-IMU). At present, most of smart phones comprise built-in MEMS-IMUs, and cannot provide high-precision positioning during long-endurance.
Disclosure of Invention
In view of the above analysis, the present invention aims to provide an indoor positioning method and device based on multi-source information fusion; the Bluetooth positioning, the magnetic field positioning and the pedestrian dead reckoning are combined, and a new solution is provided for indoor positioning.
The invention discloses an indoor positioning method based on multi-source information fusion, which comprises the following steps:
performing Bluetooth positioning based on the collected Bluetooth base station signals and the collected Bluetooth base station data to obtain a Bluetooth positioning result;
carrying out dead reckoning on the basis of the collected course information and acceleration information to obtain a current motion track;
judging whether the current motion track meets the multi-source information fusion positioning condition; if not, adopting the Bluetooth positioning result as an indoor positioning result; if the indoor positioning result is matched with the indoor positioning result, performing fusion positioning combining Bluetooth positioning, dead reckoning and geomagnetic matching positioning, and taking the fusion positioning result as the indoor positioning result;
and the multi-source information fusion positioning condition is that the course change rate of the current motion track is smaller than a course change threshold.
Further, the bluetooth positioning comprises:
respectively deploying Bluetooth base stations at N set positions in an indoor space; storing the mac address and the coordinates of each deployed Bluetooth base station in a Bluetooth base station database;
collecting Bluetooth signals on line, and acquiring the signal intensity of each Bluetooth base station corresponding to the mac address;
selecting a Bluetooth base station for positioning according to the signal intensity;
and acquiring the position information of the Bluetooth base station for positioning from the Bluetooth base station database, and acquiring the Bluetooth positioning information by adopting weighted calculation in combination with the corresponding signal intensity.
Further, the signal strength of each Bluetooth base station is represented as Rt＝(rt1,rt2,…,rtN) (ii) a Wherein the content of the first and second substances,
Figure BDA0002553434060000031
at time t maciSignal strength of a bluetooth base station; m is mac collected in a set time intervaliNumber of signals corresponding to Bluetooth base station, rssit,ijIndicates mac within the time periodiThe signal intensity corresponding to the jth signal corresponding to the Bluetooth base station.
Further, the method for selecting the Bluetooth base station for positioning according to the signal strength comprises the following steps:
sequencing the signal intensity of each Bluetooth base station to obtain the first four Bluetooth base stations with the maximum signal intensity;
calculating the space distances from the Bluetooth base station with the maximum signal intensity to other three Bluetooth base stations;
and discarding the Bluetooth base station with the largest spatial distance with the Bluetooth base station with the largest signal intensity to obtain three Bluetooth base stations for positioning.
Further, the method of weight calculation includes:
calculating weights of three bluetooth base stations for positioning
Figure BDA0002553434060000032
In the formula, rtkRepresenting the signal strength of the kth Bluetooth base station at the time t;
for the weight wkNormalizing to obtain normalized weight
Figure BDA0002553434060000033
The sum of the weights of the three Bluetooth base stations used for positioning;
according to a weighted formula
Figure BDA0002553434060000034
Calculating the Bluetooth positioning position P at the moment tt；(xk,yk) The location of the kth bluetooth base station at time t.
Further, the fused localization comprises:
generating a sample set to be positioned for magnetic field positioning based on a current Bluetooth positioning result; each sample to be positioned in the sample set to be positioned comprises a plane coordinate and course information;
for each sample to be positioned, based on the plane coordinate and the course information of the sample, projecting the current motion track with a set length onto an indoor plane graph, and extracting corresponding magnetic field data in a corresponding magnetic field database; calculating the magnetic field distance between the magnetic field data acquired in real time and the extracted magnetic field data in the database;
calculating the weight of each sample to be positioned according to the magnetic field distance information of each sample to be positioned;
and performing weighted calculation according to the plane coordinates and the weight of each sample to be positioned to obtain a fusion positioning result.
Furthermore, the plane coordinate of the sample to be positioned is set by taking the plane coordinate of the Bluetooth positioning result as a center and taking a set distance as an interval, and the plane coordinate covers a first set range; the distance of the interval is adjusted according to the geomagnetic matching positioning precision; the first setting range is set according to the requirement of geomagnetic matching data quantity and the requirement of geomagnetic matching distance according to experience;
and on the plane coordinates of the sample to be positioned, setting by taking the current course as a center and setting at set angle intervals, and generating course information of the sample to be positioned.
Further, when the current motion trail is not projected to the obstacle area on the indoor plane graph, the magnetic field distance formula is
Figure BDA0002553434060000041
Wherein disiRepresenting the calculated magnetic field distance, M, of the sample i to be positionednow,jRepresenting a magnetic field value corresponding to a jth point in the current motion track; mdb,i,jRepresents the jth magnetic field value in the magnetic field database extracted based on the sample i to be positioned, and n represents the number of magnetic field data contained on the current motion trail with the set length.
Further, the weighted calculation method of the fusion positioning comprises the following steps:
calculating a weight for each sample to be positioned
Figure BDA0002553434060000042
Normalizing the weights
Figure BDA0002553434060000043
According to a weighted formula
Figure BDA0002553434060000044
Calculating the position of fusion positioning; (x)j,yj) Represents the plane position where the jth sample to be positioned is located, and R is the number of samples to be positioned.
The invention also discloses an indoor positioning device based on multi-source information fusion, which comprises a sensor module, a database module and a positioning algorithm module;
the sensor module comprises an acceleration sensor, a direction sensor, a geomagnetic sensor and a Bluetooth module and is used for providing acceleration information, heading information, geomagnetic information and Bluetooth information for the positioning algorithm module;
the database module comprises a Bluetooth base station database and a geomagnetic database and is used for providing Bluetooth base station data and geomagnetic data in a positioning area for the positioning algorithm module;
the positioning algorithm module is used for executing the indoor positioning method for indoor positioning.
The invention has the following beneficial effects:
the invention integrates PDR, magnetic field positioning, Bluetooth positioning and indoor map information, provides a high-precision indoor positioning method, can achieve the positioning precision superior to 1.4 meters under the probability of 60 percent, and can also achieve the positioning precision superior to 2 meters under the probability of 60 percent by adopting the Bluetooth positioning method when the integrated positioning can not be used.
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The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
Fig. 1 is a flowchart of an indoor positioning method according to a first embodiment of the present invention;
fig. 2 is a flowchart of bluetooth positioning according to a first embodiment of the present invention;
fig. 3 is a schematic diagram of a bluetooth base station according to a first embodiment of the present invention;
fig. 4 is a distribution diagram of the cumulative probability of bluetooth positioning error in the first embodiment of the present invention;
FIG. 5 is a flowchart of a fusion positioning method according to a first embodiment of the present invention;
FIG. 6 is a scene plan of an environment according to a first embodiment of the invention;
fig. 7 is a schematic diagram of an installation location of a bluetooth base station according to a first embodiment of the present invention;
FIG. 8 is a magnetic field distribution diagram according to a first embodiment of the present invention;
FIG. 9 is a diagram of a walking trajectory in the first embodiment of the present invention;
FIG. 10 is a diagram of a real-time positioning result according to a first embodiment of the present invention;
FIG. 11 is a diagram illustrating a cumulative distribution of probability of positioning errors according to a first embodiment of the present invention;
fig. 12 is a schematic diagram illustrating a principle of an indoor positioning apparatus according to a second embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form a part hereof, and which together with the embodiments of the invention serve to explain the principles of the invention.
Example one
The embodiment discloses an indoor positioning method based on multi-source information fusion, as shown in fig. 1, comprising the following steps:
s101, carrying out Bluetooth positioning based on the collected Bluetooth base station signals and the collected Bluetooth base station data to obtain a Bluetooth positioning result;
s102, carrying out pedestrian dead reckoning on the basis of the collected course information and acceleration information to obtain a current motion track;
step S103, judging whether the current motion track meets the multi-source information fusion positioning condition; if not, adopting the Bluetooth positioning result as an indoor positioning result; and if the result is consistent with the result, performing fusion positioning combining Bluetooth positioning, pedestrian dead reckoning and geomagnetic matching positioning, and taking the fusion positioning result as an indoor positioning result.
Specifically, as shown in fig. 2, the bluetooth positioning in step S101 includes:
step S201, deploying Bluetooth base stations at N set positions in an indoor space; storing the mac address and the coordinates of each deployed Bluetooth base station in a Bluetooth base station database;
in the positioning technology based on the Bluetooth signal, the positioning technology is influenced by the deployment of the Bluetooth base station. The signal attenuation model of the Bluetooth signal in the open environment is
Figure BDA0002553434060000061
Wherein d is0For reference distance, at d0Has a signal strength of P0The signal strength at distance d is P and the obstacle-induced error ξ satisfies a normal distribution.
From the signal attenuation model, the bluetooth signal is exponentially attenuated along with the distance, the change of the signal strength (RSSI) is obvious in a range close to the base station, but the RSSI distribution tends to be flat along with the increase of the distance, and the correlation between the position change and the RSSI is high in a range with obvious RSSI change. Combining the signal attenuation model and the actual measurement result, as shown in fig. 3, the embodiment provides that the deployment interval of the bluetooth base station is set to 6 meters.
After the Bluetooth base station is deployed, the mac address is used as the unique identifier of the Bluetooth base station and is used as the basis for selecting the Bluetooth base station during online positioning, and the Bluetooth base station database consists of the mac address and the position of the base station corresponding to the mac address. Specifically shown as follows. DB { (mac)i,xiYi), i ═ 1, …, N; wherein, maciRepresents mac address, x corresponding to ith Bluetooth base stationi,yiThe plane coordinate where the Bluetooth is located is shown, and N represents the total number of installed Bluetooth base stations.
Step S202, collecting Bluetooth signals on line, and acquiring the signal intensity of each Bluetooth base station corresponding to the mac address;
in the on-line positioning stage, Bluetooth signal acquisition is carried out through the smart phone, and aiming at the mac addresses of the Bluetooth base stations existing in the database, the signal intensity of the Bluetooth base stations corresponding to the mac addresses within a certain time is averaged to obtain RSSI signals for positioning.
Specifically, the signal intensity R of each Bluetooth base station collected at the time tt＝(rt1,rt2,…,rtN) (ii) a Wherein the content of the first and second substances,
Figure BDA0002553434060000071
m is mac collected in a set time intervaliNumber of signals corresponding to Bluetooth base station, rssit,ijIndicates mac within the time periodiThe signal intensity corresponding to the jth signal corresponding to the Bluetooth base station; the time interval of the present embodiment may be set to 1 second.
Step S203, selecting a Bluetooth base station for positioning according to the signal intensity;
in a positioning process, the number of the Bluetooth base stations acquired by the smart phone is large, different Bluetooth positioning methods are different in the method for selecting the Bluetooth base station for positioning, and the selection of the Bluetooth base station has a great influence on the positioning accuracy.
Specifically, the method for selecting the bluetooth base station for positioning includes:
1) sequencing the signal intensity of each Bluetooth base station to obtain the first four Bluetooth base stations with the maximum signal intensity;
2) calculating the space distance between the Bluetooth base station with the maximum signal intensity and other three groups of Bluetooth base stations;
3) and discarding the Bluetooth base station with the largest spatial distance with the Bluetooth base station with the largest signal intensity to obtain three Bluetooth base stations for positioning.
Step S204, the position information of the Bluetooth base station used for positioning is obtained from the Bluetooth base station database, and the Bluetooth positioning information is obtained by adopting weighting calculation in combination with the corresponding signal intensity.
The method for obtaining the Bluetooth positioning information by adopting the weighted calculation comprises the following steps:
calculating three bluetooth base stations for positioningWeight of (2)
Figure BDA0002553434060000081
In the formula, rtkRepresenting the signal strength of the kth Bluetooth base station at the time t;
for the weight wkNormalizing to obtain normalized weight
Figure BDA0002553434060000082
The sum of the weights of the three Bluetooth base stations used for positioning;
according to a weighted formula
Figure BDA0002553434060000083
Calculating the Bluetooth positioning position P at the moment tt；(xk,yk) The location of the kth bluetooth base station at time t.
The bluetooth positioning method of this embodiment is tested, the test scenario is selected as an office environment, the office is 9 × 6m, the position of the installed bluetooth base station is as shown in fig. 3, grid division is performed to obtain 39 positioning test points, based on the bluetooth positioning method, the finally obtained positioning error cumulative probability distribution is as shown in fig. 4, and therefore, based on the bluetooth positioning algorithm provided herein, the positioning accuracy is better than 2 meters at a probability of 60%.
Specifically, the Pedestrian Dead Reckoning (PDR) in step S102 is calculated by the following equation:
Figure BDA0002553434060000091
here Pos _ Xi、Pos_YiThe current relative position is represented, Len _ step represents the step size of the current step, ψ represents the heading information output by the smart phone, and since most of the current smart devices provide a mature filtering algorithm for acquiring the device attitude, the present embodiment can acquire the device attitude information including the heading information by using the existing attitude filtering algorithm.
Pedestrian gait detection is obtained based on the following equation:
Figure BDA0002553434060000092
in the formula, Acc is a resultant acceleration acquired by an acceleration sensor of the smartphone, and represents a root mean square of acceleration data within a certain time period (for example, 0.5 s); throld1_ acc is a resultant acceleration threshold; var is the variance; acc _ max is the maximum value of the combined acceleration in the set period; acc _ min is the minimum value of the resultant acceleration in a set period; throld2_ acc: the peak-to-peak value threshold of the resultant acceleration in a set period is set.
Pedestrian step size estimation
Figure BDA0002553434060000093
Wherein fs is the acquisition frequency of an inertial sensor of the smart phone; fs step is the duration for which the current step lasts.
The current motion trail of the pedestrian can be obtained through the dead reckoning of the pedestrian.
In step S103 of this embodiment, it is determined to use a bluetooth positioning result or a fusion positioning result combining bluetooth positioning, pedestrian dead reckoning, and geomagnetic matching positioning according to the current motion trajectory. The multi-source information fusion positioning condition is that the course change rate of the current motion track is smaller than a course change threshold. If the current position is smaller than the preset value, performing fusion positioning combining Bluetooth positioning, pedestrian dead reckoning and geomagnetic matching positioning; and if not, adopting the Bluetooth positioning result as an indoor positioning result. The course change threshold may be determined empirically, for example, by determining a course change rate in a motion trajectory over a period of time that the current motion trajectory is rotating in place, if the current motion trajectory is not suitable for fusion positioning to improve positioning accuracy, the bluetooth positioning result is output as the current positioning result.
Specifically, as shown in fig. 5, the fusion positioning in step S103 includes:
s501, generating a sample set to be positioned for magnetic field positioning based on a current Bluetooth positioning result; each sample to be positioned in the sample set to be positioned comprises a plane coordinate and course information;
the plane coordinate of the sample to be positioned is set by taking the plane coordinate of the Bluetooth positioning result as a center and taking a set distance as an interval, and the plane coordinate covers a first set range; the distance of the interval is adjusted according to the geomagnetic matching positioning precision; the first setting range is set according to the requirement of geomagnetic matching data quantity and the requirement of geomagnetic matching distance according to experience; and on the plane coordinates of the sample to be positioned, setting by taking the current course as a center and setting at set angle intervals, and generating course information of the sample to be positioned.
For example, a plane coordinate of the bluetooth positioning result is taken as a center, a grid is drawn at intervals of 0.5 meter in a circle with a radius of 5 meters in length, a plane coordinate of the sample to be positioned is generated, and on each grid coordinate, the current heading is taken as the center, and heading information of the sample to be positioned is further generated by 5-degree heading change.
Step S502, projecting the current motion track with set length to an indoor plane map based on the plane coordinate and the course information of each sample to be positioned, and extracting corresponding magnetic field data in a corresponding magnetic field database; calculating the magnetic field distance between the magnetic field data acquired in real time and the extracted magnetic field data in the database;
the current motion track with the set length can be set according to the positioning requirement, for example, a motion track obtained by dead reckoning a pedestrian with the length of 10 steps is selected. When the pedestrian running dead reckoning is carried out, the magnetic sensor of the smart phone collects geomagnetic information in real time, and magnetic field data which correspond to the current motion track and are collected in real time are obtained.
And for each sample to be positioned, which comprises plane coordinates and heading information, corresponding to the projection of the current motion trail of the indoor plane map. And magnetic field data corresponding to the current motion trajectory can be extracted from the magnetic field database through projection of the current motion trajectory.
Specifically, the data in the magnetic field database are collected based on special equipment, and an indoor plane graph and high-precision position and magnetic field information can be obtained simultaneously. The final database architecture is shown below:
DBmag＝{ui,j|i＝1,…M,j＝1,…N}；
in the formula, M is row/2, N is col/2, and row and col represent the number of rows and columns of the pixel matrix corresponding to the indoor plane diagram; acquiring an obtained plan, wherein 20 pixel points represent actual 1 meter;
Figure BDA0002553434060000111
here mag represents the total strength of the magnetic field at that location. The actual plane position can be converted from the position where the point is located in the database.
The formula for calculating the magnetic field distance between the magnetic field data collected in real time and the extracted magnetic field data in the database is as follows:
Figure BDA0002553434060000112
disirepresenting the calculated magnetic field distance, M, of the sample i to be positionednow,jRepresenting a magnetic field value corresponding to a jth point in the current motion track; mdb,i,jThe method comprises the steps of projecting a current motion track to a jth magnetic field value in a magnetic field database extracted from an indoor plane graph based on plane coordinates and course information of a sample i to be positioned, wherein n represents the number of magnetic field data contained in the current motion track with a set length. Judging that the magnetic field distance is 100000000 when the current motion trail passes through the obstacle through the indoor plan; of course other numbers are possible.
Step S503, calculating the weight of each sample to be positioned according to the magnetic field distance information of each sample to be positioned;
and S504, carrying out weighting calculation according to the indoor plane coordinates and the weight of each sample to be positioned to obtain a fusion positioning result.
Specifically, the fusion positioning weighted calculation method includes:
calculating a weight for each sample to be positioned
Figure BDA0002553434060000113
Normalizing the weights
Figure BDA0002553434060000121
Is the sum of the weights of all samples to be located.
According to a weighted formula
Figure BDA0002553434060000122
Calculating the position of fusion positioning; (x)j,yj) Represents the plane position where the jth sample to be positioned is located, and R is the number of samples to be positioned.
The multi-source information fusion positioning method of the embodiment is tested and verified, and the verification place is selected as an office environment and comprises a long straight corridor. The scene plan of the environment is shown in fig. 6, which is 50 meters long and 20 meters wide. The bluetooth base stations are installed at 14 locations as shown in fig. 7. The generated magnetic field plane distribution is shown in fig. 8.
When the positioning verification is carried out, the walking track is shown in fig. 9, the real-time positioning result is shown in fig. 10, the error probability accumulation distribution graph is shown in fig. 11, and the positioning error is smaller than 1.4 m under the 60% probability.
To sum up, this embodiment integrates PDR, magnetic field positioning, bluetooth positioning, and indoor map information, provides a high-precision indoor positioning method, and can achieve a positioning precision better than 1.4 meters at a probability of 60%, and when the integrated positioning cannot be used, the bluetooth positioning method adopted can also achieve a positioning precision better than 2 meters at a probability of 60%.
Example two
The embodiment discloses an indoor positioning device based on multi-source information fusion, as shown in fig. 12, comprising a sensor module, a database module and a positioning algorithm module;
the sensor module comprises an acceleration sensor, a direction sensor, a geomagnetic sensor and a Bluetooth module and is used for providing acceleration information, heading information, geomagnetic information and Bluetooth information for the positioning algorithm module;
the database module comprises a Bluetooth base station database and a geomagnetic database and is used for providing Bluetooth base station data and geomagnetic data in a positioning area for the positioning algorithm module;
the positioning algorithm module is used for executing the indoor positioning method to perform indoor positioning;
performing Bluetooth positioning based on Bluetooth base station signals acquired by a Bluetooth module and Bluetooth base station data in a Bluetooth base station database;
carrying out pedestrian dead reckoning on the basis of acceleration information and course information acquired by an acceleration sensor and a direction sensor to obtain a current motion track;
judging whether the current motion track meets the multi-source information fusion positioning condition; if not, adopting the Bluetooth positioning result as an indoor positioning result; and (4) according with the combination, performing fusion positioning combining Bluetooth positioning, pedestrian dead reckoning and geomagnetic matching positioning.
Details and effects of the specific positioning method are the same as those in the first embodiment, and are not repeated here.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.

Claims (10)

1. An indoor positioning method based on multi-source information fusion is characterized by comprising the following steps:
performing Bluetooth positioning based on the collected Bluetooth base station signals and the collected Bluetooth base station data to obtain a Bluetooth positioning result;
carrying out dead reckoning on the basis of the collected course information and acceleration information to obtain a current motion track;
judging whether the current motion track meets the multi-source information fusion positioning condition; if not, adopting the Bluetooth positioning result as an indoor positioning result; if the indoor positioning result is matched with the indoor positioning result, performing fusion positioning combining Bluetooth positioning, dead reckoning and geomagnetic matching positioning, and taking the fusion positioning result as the indoor positioning result;
and the multi-source information fusion positioning condition is that the course change rate of the current motion track is smaller than a course change threshold.
2. The intelligent terminal device indoor positioning method according to claim 1, wherein the bluetooth positioning comprises:
respectively deploying Bluetooth base stations at N set positions in an indoor space; storing the mac address and the coordinates of each deployed Bluetooth base station in a Bluetooth base station database;
collecting Bluetooth signals on line, and acquiring the signal intensity of each Bluetooth base station corresponding to the mac address;
selecting a Bluetooth base station for positioning according to the signal intensity;
and acquiring the position information of the Bluetooth base station for positioning from the Bluetooth base station database, and acquiring the Bluetooth positioning information by adopting weighted calculation in combination with the corresponding signal intensity.
3. The method as claimed in claim 2, wherein the signal strength of each bluetooth base station is represented as Rt＝(rt1,rt2,…,rtN) (ii) a Wherein the content of the first and second substances,
Figure FDA0002553434050000011
at time t maciSignal strength of a bluetooth base station; m is mac collected in a set time intervaliNumber of signals corresponding to Bluetooth base station, rssit,ijIndicates mac within the time periodiThe signal intensity corresponding to the jth signal corresponding to the Bluetooth base station.
4. The intelligent terminal device indoor positioning method according to claim 2, wherein the method for selecting the bluetooth base station for positioning according to the signal strength comprises:
sequencing the signal intensity of each Bluetooth base station to obtain the first four Bluetooth base stations with the maximum signal intensity;
calculating the space distances from the Bluetooth base station with the maximum signal intensity to other three Bluetooth base stations;
and discarding the Bluetooth base station with the largest spatial distance with the Bluetooth base station with the largest signal intensity to obtain three Bluetooth base stations for positioning.
5. The intelligent terminal device indoor positioning method according to claim 4,
the method for calculating the weight comprises the following steps:
calculating weights of three bluetooth base stations for positioning
Figure FDA0002553434050000021
In the formula, rtkRepresenting the signal strength of the kth Bluetooth base station at the time t;
for the weight wkNormalizing to obtain normalized weight
Figure FDA0002553434050000022
Figure FDA0002553434050000023
The sum of the weights of the three Bluetooth base stations used for positioning;
according to a weighted formula
Figure FDA0002553434050000024
Calculating the Bluetooth positioning position P at the moment tt；(xk,yk) The location of the kth bluetooth base station at time t.
6. The intelligent terminal device indoor positioning method according to any one of claims 1 to 5, wherein the fusion positioning comprises:
generating a sample set to be positioned for magnetic field positioning based on a current Bluetooth positioning result; each sample to be positioned in the sample set to be positioned comprises a plane coordinate and course information;
for each sample to be positioned, based on the plane coordinate and the course information of the sample, projecting the current motion track with a set length onto an indoor plane graph, and extracting corresponding magnetic field data in a corresponding magnetic field database; calculating the magnetic field distance between the magnetic field data acquired in real time and the extracted magnetic field data in the database;
calculating the weight of each sample to be positioned according to the magnetic field distance information of each sample to be positioned;
and performing weighted calculation according to the plane coordinates and the weight of each sample to be positioned to obtain a fusion positioning result.
7. The intelligent terminal device indoor positioning method according to claim 6,
the plane coordinate of the sample to be positioned is set by taking the plane coordinate of the Bluetooth positioning result as a center and taking a set distance as an interval, and the plane coordinate covers a first set range; the distance of the interval is adjusted according to the geomagnetic matching positioning precision; the first setting range is set according to the requirement of geomagnetic matching data quantity and the requirement of geomagnetic matching distance according to experience;
and on the plane coordinates of the sample to be positioned, setting by taking the current course as a center and setting at set angle intervals, and generating course information of the sample to be positioned.
8. The intelligent terminal device indoor positioning method according to claim 6,
when the current motion trail is not projected to the obstacle area on the indoor plane graph, the magnetic field distance formula is
Figure FDA0002553434050000031
Wherein disiRepresenting the calculated magnetic field distance, M, of the sample i to be positionednow,jRepresenting a magnetic field value corresponding to a jth point in the current motion track; mdb,i,jRepresents the jth magnetic field value in the magnetic field database extracted based on the sample i to be positioned, and n represents the number of magnetic field data contained on the current motion trail with the set length.
9. The intelligent terminal device indoor positioning method according to claim 9,
the fusion positioning weighted calculation method comprises the following steps:
calculating a weight for each sample to be positioned
Figure FDA0002553434050000032
Normalizing the weights
Figure FDA0002553434050000033
According to a weighted formula
Figure FDA0002553434050000034
Calculating the position of fusion positioning; (x)j,yj) Represents the plane position where the jth sample to be positioned is located, and R is the number of samples to be positioned.
10. An indoor positioning device based on multi-source information fusion is characterized by comprising a sensor module, a database module and a positioning algorithm module;
the sensor module comprises an acceleration sensor, a direction sensor, a geomagnetic sensor and a Bluetooth module and is used for providing acceleration information, heading information, geomagnetic information and Bluetooth information for the positioning algorithm module;
the database module comprises a Bluetooth base station database and a geomagnetic database and is used for providing Bluetooth base station data and geomagnetic data in a positioning area for the positioning algorithm module;
the positioning algorithm module is used for executing the indoor positioning method according to any one of claims 1 to 9 for indoor positioning.
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