CN109951830B - Indoor and outdoor seamless positioning method based on multi-information fusion - Google Patents
Indoor and outdoor seamless positioning method based on multi-information fusion Download PDFInfo
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Abstract
A multi-information fusion indoor and outdoor seamless positioning method comprises the following steps: step S1: a Bluetooth beacon is arranged at a place where a pedestrian passes; collecting the guide data, ibeacon information and real-time relative position information of pedestrians in real time to form multi-source information fusion data; step S2: judging indoor and outdoor; comprehensively judging whether the signal intensity receiving condition of the Bluetooth beacon, the receiving quality of the satellite positioning data and the real-time relative position information are in the indoor map range or not; step S3: in combination with the judgment in step S2, estimation of the pedestrian position is performed. The invention has the advantages of low cost, high precision, long-time reliable positioning and the like under the condition of complex indoor and outdoor environments.
Description
Technical Field
The invention mainly relates to the technical field of positioning, in particular to an indoor and outdoor seamless positioning method based on multi-information fusion.
Background
With the development of modern information technologies such as wireless networks and mobile computing, location-based services have been widely used in various aspects of mass production and life. The GPS, GLONASS and the Beidou positioning system are established successively, so that the outdoor positioning is realized accurately in real time. However, due to the influence of factors such as signal shielding and multi-channel effect, when the satellite positioning system is indoor, the satellite positioning system such as GPS and the like cannot meet the requirements of people on positioning precision. Accordingly, various indoor positioning techniques and methods have been developed. Among these indoor positioning methods, there are ones based on a certain technology alone, such as: based on Bluetooth, WIFI, ultra wideband, micro inertial navigation and the like, a method for combining a plurality of technologies to overcome the disadvantages and realize positioning, such as: fusing micro inertial navigation with ultra wideband, fusing micro inertial navigation with WIFI, and the like.
The indoor positioning method based on Bluetooth mainly realizes positioning in two ways. A method for obtaining the geometric distance from a specific Bluetooth beacon in a space by measuring the signal intensity of the specific Bluetooth beacon in the space and calculating the geometric distance from the specific Bluetooth beacon by means of model conversion is characterized in that a signal intensity attenuation model is built according to the rule of attenuation along with the distance in the Bluetooth radio signal intensity space. This approach first places a sufficient density of bluetooth beacons in the area to be localized and measures the bluetooth beacon spatial coordinate locations. When positioning, the target to be positioned carries a positioning label, the positioning label acquires signal intensity information of surrounding Bluetooth beacons in real time, the signal intensity information is filtered and then subjected to model calculation, the geometric distance between the label and the surrounding Bluetooth beacons is obtained, and finally, a positioning result is given by using a three-point positioning or least square positioning method. The other is a fingerprint matching positioning mode. In the method, bluetooth beacons with sufficient density are firstly arranged in a space to be positioned, then a point is uniformly selected in the space (for example, a point is selected every 1 m multiplied by 1 m), bluetooth signal intensity information on each point is acquired, and a positioning fingerprint library is established by using the position coordinates of the points and the corresponding signal intensity information. During positioning, a positioning target carries with a positioning tag to search and collect surrounding Bluetooth beacon intensity information in real time, and then a fingerprint matching positioning method is utilized to carry out matching calculation on the signal intensity information and the signal intensity information in a fingerprint database, so that the current position of the target is estimated, and positioning is realized.
The indoor positioning method based on WIFI is the same as the positioning method based on Bluetooth in implementation mode, and can also utilize a signal intensity space attenuation rule, perform ranging and positioning firstly, establish a fingerprint library and realize positioning through fingerprint matching. However, in practical application, a fingerprint matching mode is mostly adopted, because in the mode, a WIFI base station is not required to be independently arranged for positioning, a WIFI signal covered in a positioning scene can be directly utilized, a WIFI fingerprint library is only required to be established, and a positioning function can be realized through fingerprint matching, so that the positioning mode is also mostly used in a positioning scene with more available WIFI sources.
The indoor positioning method based on ultra wideband is based on ultra wideband ranging technology. Ultra-wideband ranging, the mainstream method is to transmit radio pulses with extremely high bandwidth, duration as short as nanosecond, and very high time resolution, and then measure the arrival time or arrival time difference of the received pulses to achieve ranging. When the positioning is realized in the mode, firstly, the position of the ultra-wideband ranging base station is reasonably selected in the positioning area, and the base stations are arranged, wherein the position selection must ensure that any point in the positioning area can receive ranging signals of at least three base stations. When positioning, the target to be positioned carries a positioning label, receives ranging information of surrounding base stations in real time, and then calculates the positioning position through a three-point positioning method.
In contrast to the three positioning methods using radio wave technology, the indoor positioning method based on micro inertial navigation uses Micro Electromechanical (MEMS) sensors such as gyroscopes, accelerometers, magnetometers, etc. to achieve position acquisition. When micro inertial navigation is used for pedestrian positioning, commonly called pedestrian dead reckoning (Pedestrian Dead Reckoning, PDR), pedestrian motion data are acquired in real time by utilizing sensors such as an accelerometer, a gyroscope and a magnetometer, the walking steps, the step length and the direction of the pedestrian are measured and counted, and the walking track, the position and other information of the pedestrian are calculated, so that the positioning is finally realized.
In a complex indoor and outdoor environment, the positioning method based on the radio technology inevitably leads to the rise of positioning cost and the reduction of positioning precision due to factors such as signal shielding, multichannel effect and the like. In most cases, the positioning result meeting the precision requirement can be obtained through the guide outdoors, but when the target approaches a high wall or a narrow channel, the positioning becomes unstable and the precision is reduced. In an indoor environment, a positioning method (such as Bluetooth positioning, WIFI positioning, radio frequency RFID positioning and the like) based on radio signal intensity is poor in positioning accuracy and needs dense arrangement. The ultra-wideband positioning is required to be increased because the indoor space is narrow, and the advantages of wide ultra-wideband positioning range cannot be exerted due to shielding of multiple walls, furnishing and the like, so that the cost and the construction difficulty are necessarily increased, and the positioning precision is also reduced due to the influence of shielding and multiple effects. The inertial navigation method is not easy to be interfered by indoor complex environment because the working process does not depend on external information, but the used equipment is convenient to carry, so that the inertial navigation can only adopt the micro inertial navigation technology, and the micro inertial navigation based on the micro-electromechanical sensor has larger error accumulation and direction drift and cannot meet the long-time positioning requirement.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems existing in the prior art, the invention provides the indoor and outdoor seamless positioning method capable of realizing multi-information fusion with low cost, high precision and long-time reliable positioning under the complex indoor and outdoor conditions.
In order to solve the technical problems, the invention adopts the following technical scheme:
a multi-information fusion indoor and outdoor seamless positioning method comprises the following steps:
step S1: a Bluetooth beacon is arranged at a place where a pedestrian passes; collecting the guide data, ibeacon information and real-time relative position information of pedestrians in real time to form multi-information fusion data;
step S2: judging indoor and outdoor; comprehensively judging whether the signal intensity receiving condition of the Bluetooth beacon, the receiving quality of the satellite positioning data and the real-time relative position information are in the indoor map range or not;
step S3: if the method is judged to be outdoor, positioning is carried out by using a loose combined navigation positioning strategy of the particle filter as a fusion frame, a particle filter motion model is obtained according to real-time relative position information, if the particle filter is unavailable, a weighted average value of particle sets is directly calculated to be used as an estimation of pedestrian positions, if the particle filter is available, a sanitation observation is added into the particle filter, and then the weighted average value of the particle sets is calculated to be used as an estimation of pedestrian positions; if the pedestrian position is judged to be indoor, taking particle filtering as a fusion frame, taking real-time relative position information as a particle filtering motion model, adding Bluetooth ranging observation and map constraint observation, and then calculating a weighted average value of particle sets to obtain the pedestrian position estimation.
As a further improvement of the invention: in the step S1, the real-time relative position information is given by an IMU module fixedly installed in a positioning tag at any one of three positions of a foot, a waist or a shoulder of a pedestrian, which is a two-dimensional rectangular coordinate with respect to a positioning start point.
As a further improvement of the invention: in the step S1, the real-time satellite-based data is obtained by a satellite-based positioning module, and is derived from a positioning navigation system, where the data includes the current target longitude and latitude position, and the dop value, the satellite number, and the horizontal plane error that can characterize the positioning position accuracy.
As a further improvement of the invention: in the step S1, the ibeacon information is obtained through a bluetooth module, and includes a bluetooth beacon number and a corresponding signal strength value.
As a further improvement of the invention: in the step S1, the multi-information fusion data is used as a data fusion filter through particle filtering, and the real-time sanitation data, the ibeacon information and the real-time relative position information are input into the particle filtering information fusion filter after time synchronization; and taking the real-time relative position information as a particle filtering motion model, taking the defending data, the ibeacon information and the plane map information as filtering observation information, and finally obtaining the longitude, latitude and floor information of the pedestrian subjected to filtering correction through condition judgment and position correction.
As a further improvement of the invention: also comprises a coordinate alignment process; a guide positioning position is selected, real-time relative position information, ibeacon information and map position are transformed into the same coordinate system through coordinate transformation,
as a further improvement of the invention: the mark alignment process comprises the following steps: firstly, calibrating an indoor map to be used into a global guide map to obtain a coordinate transformation matrix from all pixel points in the indoor map to the global guide map coordinate system, wherein the Bluetooth beacon position coordinate is a coordinate under the map coordinate system, and obtaining the longitude and latitude position of the Bluetooth beacon through the coordinate transformation matrix transformation from the indoor map to the global guide map; and transforming the real-time relative position information coordinate into a map coordinate system to finish coordinate alignment.
As a further improvement of the invention: when the positioning starting point is positioned indoors, two Bluetooth beacons are utilized for coordinate alignment; the method comprises the steps that a pedestrian carries a tag and sequentially passes under two Bluetooth beacons with a certain distance, the maximum signal intensity of the beacon is searched every time the pedestrian passes through one beacon, the pedestrian is considered to be right under a signal when the maximum signal intensity is obtained, the horizontal projection coordinate of the beacon is taken as the actual coordinate P1 of the pedestrian in a map at the moment, and the horizontal projection coordinate value Q1 of the relative coordinate given by the tag at the moment is recorded; the actual coordinates P2 of pedestrians in the map and the relative coordinates Q2 given by the tags at the time when the pedestrians pass through the second alignment beacon are found out through the same method, and then the relative relation between the vector P2P1 and the vector Q2Q1 is utilized to calculate a planar two-dimensional real-time relative position information track alignment coordinate transformation matrix.
As a further improvement of the invention: when the positioning starting point is located outdoors, coordinate alignment is performed by utilizing the guide positioning position; the method comprises the steps of walking outdoors for a certain distance, obtaining the relative track of the guide positioning information and the real-time relative position information in the path, screening position points with higher precision from the guide positioning position by utilizing the dop value and the satellite number information in the guide data, calculating a transformation matrix of the real-time relative position information relative track to the global guide coordinate system through least square estimation, and enabling the sum of the distances from the position points on the real-time relative position information track to the guide position points after the screening to be minimum.
As a further improvement of the invention: when indoor and outdoor judgment is carried out, if the received Bluetooth beacon signal strength is larger than a set detection threshold value, the pedestrian is inferred to be in a sufficiently close range of the Bluetooth beacon, and then the pedestrian is inferred to be in the room at the moment; or in the received guide data, the number of satellites is smaller than a given threshold value, the satellite shielding is serious, and the pedestrian is inferred to be in the room at the moment; if the bluetooth beacon state of sufficient signal strength is not received and the number of received satellites is greater than a given threshold, it is determined that the pedestrian is outdoors.
As a further improvement of the invention: when indoor and outdoor judgment is carried out after alignment, firstly judging whether the received Bluetooth beacon signal strength is greater than a given threshold value, and if so, enabling pedestrians to be indoor; otherwise, judging whether the satellite number is smaller than a given indoor satellite number threshold value, if so, judging whether the current positioning position is in an indoor map range, and if so, enabling pedestrians to be in the indoor; if it cannot be determined that the pedestrian is indoors by the foregoing steps, it is determined that the pedestrian is outdoors.
As a further improvement of the invention: when indoor positioning is performed through Bluetooth, the method comprises the following steps:
(a) The characteristic that propagation in a Bluetooth signal intensity space decays along with the distance is utilized, the approximate distance from Bluetooth is obtained according to an empirical formula of the distance and the signal intensity, and then a positioning position is obtained through triangular positioning;
(b) By utilizing the characteristic that the signal intensity around the Bluetooth beacon is distributed in a fingerprint shape, a Bluetooth signal intensity fingerprint library is established, and then the positioning position is obtained through fingerprint matching.
As a further improvement of the invention: in the step S3, map constraint is completed by taking map information as observation of particle filtering, that is, judging all particles by using a wall-penetrating detection method, and if a certain particle penetrates through a wall, correspondingly reducing the weight of the particle; after the particle filtering resampling, the through-wall particles are replaced by the replica particles of the non-through-wall particles, so that the accuracy of the particle set on the approximation of the actual label position is improved, and the correction of the positioning position is realized.
As a further improvement of the invention: the method comprises the steps of acquiring the height of a positioning position and switching floors of an indoor map, wherein the height is acquired through an air pressure sensor, meanwhile, the floors of pedestrians are judged by utilizing Bluetooth beacons deployed on different floors, and when the signal intensity scanned by a Bluetooth module is greater than a Bluetooth beacon with a given threshold value, the floor of the floor where the beacon is located is used as the current floor of the pedestrian; and the map switching among different floors is judged and switched through the Bluetooth beacons.
As a further improvement of the invention: screening the guard positioning position data through two different screening steps; firstly, carrying out primary screening on satellite positioning position data according to the dop value, the satellite number and the middle error of the horizontal plane in the satellite guiding data, if the satellite guiding data passes the primary screening, selecting a history Wei Daogui trace after the last section of screening to match with the positioning trace of the real-time relative position information corresponding to the section of trace, giving a minimum matching residual, and if the minimum matching residual is smaller than a given available threshold, considering that the satellite data is reliable, otherwise, the satellite positioning data is unreliable, and cannot be used for fusion positioning, and the satellite positioning data is unavailable.
As a further improvement of the invention: the principle of the Bluetooth beacon deployment is as follows:
(1) A beacon is arranged on a door frame of a stair entrance of each indoor floor for identifying, correcting and positioning the floor;
(2) A Bluetooth beacon is arranged on a door frame of each door of each floor to be positioned;
(3) And Bluetooth beacons are distributed in places where the probability of passing by other pedestrians is high, so that the Bluetooth deployment density is ensured.
Compared with the prior art, the invention has the advantages that:
1. the indoor and outdoor seamless positioning method based on multi-information fusion is an outdoor and indoor seamless positioning method comprehensively utilizing the sanitation, micro inertial navigation, bluetooth and map information, and can realize low-cost, high-precision and long-time positioning in complex indoor and outdoor environments, thereby solving the defects that the positioning technology based on radio is greatly influenced by the environment and the positioning technology based on inertial navigation is accumulated in error, and realizing indoor and outdoor continuous and stable seamless positioning.
2. The indoor and outdoor seamless positioning method with multi-information fusion provided by the invention has the advantages that when the indoor and outdoor seamless positioning method is used for outdoor and the defending guide positioning is simply utilized, but when pedestrians walk into a narrow roadway, a woodland and approach to a tall building, the positioning stability and the positioning accuracy are reduced due to defending guide signal shielding, multipath and the like. Positioning is performed by using a combined navigation method based on sanitation navigation and micro inertial navigation, so that positioning accuracy and stability in a complex outdoor environment can be remarkably improved. When the IMU is used for pedestrian positioning only indoors, the positioning errors are unacceptably accumulated along with time due to error accumulation and direction drift of inertial navigation solution, the Bluetooth beacons are used only, the positioning accuracy is low, meanwhile, the cost is high due to high-density deployment, the IMU track and Bluetooth positioning information are fused with a map by a particle filtering method, and the direction drift and position accumulation errors of the IMU can be restrained and corrected by using the map and Bluetooth positioning position points. The system comprehensively utilizes the guide, the IMU, the map and the Bluetooth beacon, so that the problem of seamless long-time high-precision real-time positioning of personnel in complex indoor and outdoor environments can be realized, the indoor positioning beacon is sparsely deployed, the wireless cable is not used, the weak current construction is avoided, and the deployment, maintenance and migration are simple and convenient.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention.
Fig. 2 is a schematic diagram of the present invention in a specific application example.
Fig. 3 is a schematic diagram of the present invention employing a two-point alignment method based on bluetooth beacons in a specific application example.
Fig. 4 is a schematic flow chart of the first stage of indoor and outdoor discrimination in a specific application example of the present invention.
Fig. 5 is a schematic flow chart of the second stage indoor and outdoor discrimination in the specific application example of the present invention.
Fig. 6 is a schematic diagram of a guard signal screening process in a specific application example of the present invention.
Fig. 7 is a schematic diagram of a complete flow of the present invention in a specific application example.
Detailed Description
The invention will be described in further detail with reference to the drawings and the specific examples.
As shown in fig. 1 and 2, the indoor and outdoor seamless positioning method for multi-information fusion of the present invention includes the steps of:
step S1: a Bluetooth beacon is arranged at a place where a pedestrian passes; collecting the guide data, ibeacon information and real-time relative position information of pedestrians in real time to form multi-information fusion data;
step S2: judging indoor and outdoor; and comprehensively judging whether the Bluetooth beacon signal strength receiving condition, the satellite navigation positioning data receiving quality and the real-time relative position information are in the indoor map range or not.
Step S3: if the method is judged to be outdoor, positioning is carried out by using a loose combined navigation positioning strategy of the particle filter as a fusion frame, a particle filter motion model is obtained according to real-time relative position information, if the particle filter is unavailable, a weighted average value of particle sets is directly calculated to be used as an estimation of pedestrian positions, if the particle filter is available, a sanitation observation is added into the particle filter, and then the weighted average value of the particle sets is calculated to be used as an estimation of pedestrian positions; if the pedestrian position is judged to be indoor, taking particle filtering as a fusion frame, taking real-time relative position information as a particle filtering motion model, adding Bluetooth ranging observation and map constraint observation, and then calculating a weighted average value of particle sets to obtain the pedestrian position estimation.
In a specific application example, in the above step S1, the real-time relative position information is given by the IMU module fixedly placed in the positioning tag at any of three positions of the foot, waist or shoulder of the pedestrian, which is a two-dimensional rectangular coordinate with respect to the positioning start point. The real-time satellite derivative is obtained through a satellite guiding positioning module and can be derived from any available positioning navigation system such as GPS, beidou and the like, and the data comprise the longitude and latitude position of the current target, the dop value capable of representing the positioning position precision, the satellite number, the middle error of the horizontal plane and the like. The real-time ibeacon information is acquired through a Bluetooth module, and comprises the serial number of a Bluetooth beacon and a corresponding signal strength value.
In a specific application example, in the step S1, the real-time ibeacon information includes the number of one or more bluetooth, the corresponding signal strength, and the system time when the number and the signal strength of the bluetooth beacon are obtained by scanning. The guide data comprises longitude, latitude, altitude, satellite number, dop value, error in the horizontal plane and acquisition time of the frame guide data. The position data collected by the IMU module comprises an x coordinate value, a y coordinate value, a z coordinate value and a barometer height value of the IMU relative coordinate system, and the system time generated by the IMU position data of the frame, and all the IMU position data are given when a pedestrian completes one step.
In a specific application example, in the step S1, the multi-information fusion data is used as a data fusion filter through particle filtering, the real-time IMU relative position, the guard data and the scanned bluetooth information are input into the particle filtering information fusion filter after time synchronization, the IMU relative position is used as a particle filtering motion model, the guard positioning position, the bluetooth signal intensity positioning information and the plane map information are used as filtering observation information, and the real-time filtering positioning position is corrected through judging under certain conditions. And finally, obtaining the longitude and latitude and floor information of the pedestrian subjected to filtering correction.
In particular application, in the method of the invention, a position update model with relative label position aligned to a map coordinate system is adopted as a propagation model of particle filtering, and the model form is as follows (formula (1)):
wherein Deltal t 、△heading t The step length and the course angle increment given by the IMU when the tag moves from the moment t-1 to the moment t are the step length of the pedestrian carrying the tag for completing one step and the angle increment of the advancing direction of the step relative to the advancing direction of the previous step. X is x t 、y t And head-ing t Respectively the level x of the pedestrian t moment carrying the tag in the map coordinate system,y-axis coordinates and heading.
In particle filtering, the particles of a particle set are obtained by sampling a proposed distribution (or proposed distribution), which in the method of the invention is obtained by adding gaussian noise with zero mean to the propagation model.
The weight correction is divided into three cases of weight correction when the guard positioning position is used as filtering observation, weight correction when the Bluetooth beacon signal strength ranging is used as filtering observation and weight correction when the map constraint is used as filtering observation.
In the first case, the weight correction formula is as follows (formula (2)):
wherein w is t (k) The weight of the kth particle at the time t, ρ is a normalized coefficient, 
For t time, guard positioning position, (x) t (k),y t (k) At time t) is the position, sigma, represented by the kth particle s The mean square error of Gaussian distribution is related to the positioning accuracy of the guide.
In the second case, the weight correction formula is as follows (formula (3)):
wherein w is t (k) The weight of the kth particle at the moment t, ρ is a normalized coefficient, range t (m) distance measured at time t to mth Bluetooth beacon, range t (k, m) is the distance from the kth particle to the mth bluetooth beacon at time t.
When the map constraint is used in the second case, multiplying the weight of the through-wall particles by a coefficient smaller than 1, reducing the weight of the through-wall particles, keeping the original weight of the particles which do not pass through the wall unchanged, and then normalizing all the weights.
In a specific application example, in the above step S1, the principle of bluetooth beacon deployment is as follows:
(1) A beacon is arranged on a door frame of a stair entrance of each indoor floor for identifying, correcting and positioning the floor;
(2) A Bluetooth beacon is arranged on a door frame of each door of each floor to be positioned;
(3) And a Bluetooth beacon is arranged at a place where the probability of passing by other pedestrians is high, so that certain Bluetooth deployment density is ensured.
In a preferred embodiment, the method further comprises a coordinate alignment process in the initialization stage of the positioning method. Whether the relative position of the positioning tag is obtained through the inertial device or the distance measurement information of the Bluetooth beacon or the position of the regional map is relative to the relative coordinate system of the positioning tag, in order to perform positioning fusion, coordinate transformation is needed to be performed first, and the three coordinates are transformed to be under the same coordinate system. In the positioning method, the coordinate system where the navigation positioning position is located is selected as a reference coordinate system, and the relative position coordinates of the tag, the Bluetooth beacon position coordinates and the map coordinate system are transformed into the map coordinate system.
The method comprises the steps of firstly calibrating an indoor map to be used in a global guide map to obtain a coordinate transformation matrix from all pixel points in the indoor map to the global guide map coordinate system, and obtaining the position coordinates of the Bluetooth beacons by marking the corresponding positions in the map when the Bluetooth beacons are deployed, so that the Bluetooth beacon coordinates are the coordinates under the map coordinate system, and obtaining the longitude and latitude positions of the Bluetooth beacons by transforming the coordinate transformation matrix from the indoor map to the global guide map. The IMU relative position coordinates are then transformed into a map coordinate system, i.e., the coordinate alignment shown here.
In the positioning method, the coordinate alignment is realized by one of two methods, and the coordinate alignment is selected according to whether the pedestrian positioning starting point is positioned indoors or outdoors. When the positioning start point is located indoors, two bluetooth beacons are utilized for coordinate alignment, as shown in fig. 3. Which is a kind ofThe principle is as follows: after the label is started and initialized, the label is carried by the pedestrian, the pedestrian sequentially passes under two Bluetooth beacons with certain distance, the maximum signal intensity of the beacon is searched every time the pedestrian passes through one beacon, and the pedestrian is considered to be right under the signal when the maximum signal intensity is reached, so that the horizontal projection coordinate of the beacon can be used as the actual coordinate P1 (x P1 ,y P1 ) At the same time, the horizontal projection coordinate value Q1 (x Q1 ,y Q1 ) The actual coordinates P2 (x) of the pedestrian in the map when passing through the second alignment beacon are found by the same method P2 ,y P2 ) And the relative coordinates Q2 (x Q2 ,y Q2 ). Then, using the relative relationship between the vector P2P1 and the vector Q2Q1, a planar two-dimensional IMU trajectory alignment coordinate transformation matrix is calculated as follows (formula (4)):
△θ＝tan- 1 ((y P2 -yP1)/(x P2 -x P1 ))-tan- 1 ((y Q2 -yQ1)/(x Q2 -x Q1 ))
wherein, (x, y) is the original track point coordinates of the IMU, (x) align ,y align ) And the coordinates of the trace points of the aligned IMU.
When the positioning starting point is located outdoors, coordinate alignment is performed by utilizing the guide positioning position. The method comprises the steps of walking outdoors for a certain distance, acquiring guide positioning information and IMU relative tracks in the path, screening position points with higher precision from guide positioning positions by utilizing dop values and satellite number information in guide data, and calculating a transformation matrix of the IMU relative tracks to a global guide coordinate system through least square estimation, wherein the sum of distances from the position points on the IMU tracks to the corresponding screened guide position points is minimum under the transformation matrix.
When the method is specifically applied, in the process, the indoor and outdoor judgment needs to be combined with three basis conditions of Bluetooth beacon signal strength receiving condition, sanitary guide positioning data receiving quality and whether the real-time positioning position is in the indoor map range or not for comprehensive judgment. According to the flow of the method, the indoor and outdoor judgment is divided into two stages of indoor and outdoor judgment.
Referring to fig. 4, the first stage is indoor and outdoor judgment before successful alignment, and the real-time positioning position of the pedestrian is not obtained before alignment, so that the judgment can only be performed according to the bluetooth beacon signal strength receiving condition and the sanitary positioning data receiving quality.
The specific method comprises the following steps: if the received Bluetooth beacon signal strength is greater than a set detection threshold, it can be inferred that the pedestrian is in a sufficiently close range of the Bluetooth beacon, and because Bluetooth is deployed indoors, it can be inferred that the pedestrian is indoors at this time; or, in the received satellite guide data, the number of satellites is smaller than a given threshold value, the satellite shielding is serious, and it can be inferred that the pedestrian is in the room at the moment. If the bluetooth beacon state of sufficient signal strength is not received and the number of received satellites is greater than a given threshold, it is determined that the pedestrian is outdoors. Otherwise, the pedestrian is in a transition zone from indoor to outdoor.
Referring to fig. 5, the second stage is indoor and outdoor judgment after alignment. The method for judging the indoor and outdoor states comprises the following steps: firstly, judging whether the received Bluetooth beacon signal strength is greater than a given threshold value, if so, the pedestrian is in the room; otherwise, judging whether the satellite number is smaller than a given indoor satellite number threshold value, if so, judging whether the current positioning position is in an indoor map range, and if so, the pedestrian is in the room. If it cannot be determined that the pedestrian is indoors by the foregoing steps, it is determined that the pedestrian is outdoors. Compared with the first stage, the transition zone of the second stage is marked into an outdoor part, and the transition zone is marked into the outdoor part and does not influence the outdoor positioning because the inertial navigation track is aligned to the global coordinate of the guide at the moment and the global positioning coordinate can be given by the inertial navigation under the condition of no guide outdoors.
As a preferred embodiment, the invention uses Bluetooth to make indoor positioning in specific application, and one method is to obtain approximate distance from Bluetooth according to the empirical formula of distance and signal strength by utilizing the characteristic that propagation in Bluetooth signal strength space decays along with distance, and then obtain positioning position by triangular positioning. The other is to build a Bluetooth signal intensity fingerprint library by utilizing the characteristic that the signal intensity around the Bluetooth beacon is distributed in a fingerprint shape, and then obtain a positioning position through fingerprint matching.
In the positioning method, the position of the beacon in the map is corrected by only using the distance from the tag to the Bluetooth beacon, which is measured by the Bluetooth signal intensity ranging. There are two correction methods, one is to take the distance from the tag measured by bluetooth beacon ranging to the bluetooth beacon as the observed quantity of particle filtering. In this manner, the empirical formula for bluetooth ranging is as follows (equation (5)):
wherein rss i Range for the signal strength of the i-th bluetooth beacon currently measured by the tag i For the distance of the tag to the ith bluetooth beacon, n is an environment-dependent coefficient, RSS then it is a signal strength calibration value at one meter. At the position of
range
In particle filtering, the filtering position can be corrected by combining the strategies.
Alternatively, when the tag receives a bluetooth beacon with a signal strength greater than or equal to the RSS of the bluetooth beacon max And when the distance from the current tag position given by the particle filtering to the Bluetooth is larger than a set threshold value, directly correcting the position of the tag in the map to the horizontal projection position of the Bluetooth beacon in the map. In this way, in particle filtering, the horizontal projection position (x, y) of the beacon is used to reinitialize the x and y states of each particle in the particle set, while the head state remains unchanged.
As a preferred embodiment, the invention further performs map constraint correction when applied specifically. In indoor positioning, the positioning position is limited by utilizing some unreachable areas in the map, so that an effective correction effect on the positioning result can be achieved. Under the particle filter framework, map restriction is relatively easy, so that the positioning method is integrated with map information in positioning so as to improve the positioning effect.
The map used for map matching in the positioning method is a binary map, namely, the gray value of the map is only 0 and 1, the 1 value indicates that the pixel point is a wall or other non-penetrable object, and the pixel point with the gray level of 0 is an indoor space and can be penetrated or occupied by the position of the label.
The core of map matching is through-wall detection, wherein the method is to connect the last state position and the current position of a single particle in a binary map by using a straight line, judge the gray values of all nearest neighbor pixels of the line, and if a pixel point with 1 exists, indicate that the particle passes through a wall or other obstacles in the current step of propagation.
In the positioning method, map constraint is completed by taking map information as observation of particle filtering, and the method is to judge all particles by using a through-wall detection method, and if a certain particle passes through a wall, the weight of the particle is correspondingly reduced. After resampling by particle filtering, the wall-penetrating particles will be replaced by replicated particles of non-wall-penetrating particles. Thereby improving the accuracy of the particle set approximation to the actual label position and realizing the correction to the positioning position.
In the positioning method of the present invention, the positioning of the outdoor part is a combined navigation positioning method of sanitation and micro inertial navigation using particle filtering as a fusion frame. In the loose combination navigation, the quality of the positioning position is defended and guided, and the influence on the final fusion positioning result is great. Therefore, before fusion filtering, the guide positioning data are screened, the positioning position displayed by errors is removed, and the stability and the precision of the fusion positioning result can be improved.
In this method, the pilot positioning data is strictly screened by two different screens. Firstly, carrying out primary screening on satellite positioning position data according to the dop value, the satellite number and the middle error of the horizontal plane in the satellite guiding data, if the satellite guiding data passes the primary screening, selecting the history Wei Daogui trace after the last section of screening to match with the IMU positioning trace corresponding to the section of trace, giving out the minimum matching residual, if the minimum matching residual is smaller than a given available threshold, considering that the satellite data is reliable, otherwise, the satellite positioning data is unreliable, the satellite guiding data cannot be used for fusion positioning, and the data cannot be used. The screening procedure is shown in fig. 6.
It should be noted that when data items such as the dop value, the satellite number, and the middle error of the horizontal plane are not included in the satellite guide data, which are limited by the system hardware, the satellite guide data screening method is effective, and the primary screening process is not included in the screening method.
As a preferred embodiment, the positioning method further comprises the steps of acquiring the height of the positioning position and switching floors of the indoor map, acquiring the height through the air pressure sensor, judging the floor where the pedestrian is located by utilizing the Bluetooth beacons deployed on different floors, and taking the floor of the floor where the beacon is located as the current floor where the pedestrian is located when the signal intensity scanned by the Bluetooth module is greater than the Bluetooth beacon with a given threshold value. According to the floor number and the floor height and other information given in the map, the pedestrian position height given by the barometer can be calibrated and corrected. And the map switching between different floors is also judged and switched through the Bluetooth beacons.
The workflow of the present invention is further illustrated in terms of completion in one specific application of the present invention. The general implementation flow of the positioning method is shown in fig. 7. The method comprises the following steps:
(1) Initializing. Loading a bluetooth beacon deployment position table containing all N bluetooth beacons and a binary grid map of an indoor part of a positioning scene, setting a pedestrian walking number carrying a positioning tag as step_num=0, setting a guard alignment data buffer counter, guard_num=0 (in the process of using guard alignment, representing the number of available guard data already stored in a guard data buffer, namely, storing one available guard data and the corresponding IUM position of the data in each guard alignment data buffer, then adding 1 to the counter value), setting a maximum buffer number, guard_max_num (the maximum length of the guard alignment data buffer, the value range being 10-25), setting an alignment flag, align_flag=0 (the value 0 in the process of initializing, when the first available guard data is searched for a Ji Lanya beacon, or the first available guard data is received, the flag is set to be 2 after the alignment is successful, so that the track value 1 indicates that the track alignment is in a positive-position stage, and the signal strength of the bluetooth is set to be used for correcting the signal to the signal is set to be normal by the threshold value of the bluetooth beacon, namely, the signal is set to the maximum signal strength of the signal alignment window is used for correcting the signal alignment, and the signal is set to be the signal strength of the signal window. Performing (2);
(2) The input data is time synchronized.
And receiving Bluetooth numbers and signal intensity information scanned by the Bluetooth module on the positioning label according to time sequence, and waiting for the IMU module to generate step position data and guard guide data. When a step is generated, step_num=step_num+1, respectively obtaining the average signal intensity value of each bluetooth beacon scanned in one step and one guard derivative data closest to the step point in time in one step, taking the beacon average signal intensity value and the latest Wei Daoshu data as the received bluetooth signal intensity value and guard derivative bit value at the step position point, setting the signal intensity value of the bluetooth beacon scanned at the step position point to be a small invalid value (less than-110 dB) if no bluetooth data is scanned in one step, and setting all items in the guard derivative data corresponding to the step position point to be zero if Wei Daoshu data is not received in one step.
(3) If align_flag= 2, perform (7) enter particle filter propagation correction process. Otherwise, if the align_flag < =1, performing indoor and outdoor judgment, and entering an IMU track alignment process: executing (5) if the judgment is indoor; executing (4) when the judgment is outdoor; and (4) determining that the transition zone is determined, and returning to the execution (2).
(4) Alignment using the guard data:
4.1 Determining whether the guard data is available, if not, returning to execution (2), if yes, guard_num=guard_num+1. If satellite_num= 1, align_flag=1 is set. Adding the guide positioning position and the IMU position into a guide alignment data cache, and executing 4.2);
4.2 If the satellite_num is smaller than the satellite_max_num, returning to the execution (2), otherwise, setting the satellite_num=0, assigning to be expressed as '=' to convert longitude and latitude coordinates in the satellite guide alignment data buffer into local coordinates, then calculating a coordinate transformation matrix from the IMU relative coordinates to the satellite guide global coordinates through least square estimation by using the buffered data, and obtaining a position coordinate (x) in the coordinate system after the current IMU coordinate transformation to the satellite guide sitting specimen localization (x) init ,y init ) And heading angle init_heading, and executing (6). Unsuccessful alignment of the guide means that the alignment process has not been completed, the position coordinates (x init ,y init ) And init_header value.
(5) With bluetooth beacon alignment, if align_flag= 0, execute 5.1), if align_flag= 1, execute 5.2):
5.1 Searching for the first bluetooth beacon.
5.1.1 If the signal strength value of all the searched Bluetooth beacons in the step is smaller than rss_min_limit, returning to the step (2), otherwise, executing the step 5.1.2);
5.1.2 Searching the strongest point of the Bluetooth signal strength, and storing the Bluetooth number corresponding to the strongest signal value of the current signal and the relative position coordinate given by the corresponding IMU. Returning to the execution (2) if the search ending condition is not satisfied, otherwise, executing 5.1.3);
5.1.3 Set align_flag=1, and the IMU relative position obtained by taking the strongest point of the signal is recorded as Q1 (x) P1 ,y P1 ) Searching a Bluetooth position table by using a Bluetooth number corresponding to the strongest signal value, obtaining the actual coordinates of the pedestrian in the map at the moment, and localizing the longitude and latitude sitting to obtain P1 (x) P1 ,y P1 ) Returning to the execution (2);
5.2 Searching for a second bluetooth beacon using the same method as in 5.1).
If Q2 (x) Q2 ,y Q2 ) And P2 (x) P2 ,y P2 ) Searching for a second Bluetooth beacon to obtainTake Q2 (x) Q2 ,y Q2 ) And P2 (x) P2 ,y P2 ) Performing alignment transformation on the current IMU relative position by using the method (4) to obtain an aligned position P3 (x) P3 ,y P3 ) Executing 5.3), otherwise, performing alignment transformation on the current IMU relative position by using formula (4) to obtain an aligned position P3 (x) P3 ,y P3 ) Execute 5.3).
5.3 If P2 and P3 are the same point, returning to the execution (2), otherwise, calculating an aligned initial position and an initial course angle:
x init ＝x P3
y init ＝y P3
init_heading＝atan2(y P3 -y p2 ,x P3 -x p2 )
and (6) executing.
(6) The particle filter particle set is initialized.
Using the obtained (x init ,y init ) And init_head initialization particle filter particle set:
Particles{x i ,y i ,heading i ,weights i } N ,i∈{1,2,…,N}，
wherein:
n is the particle number of the particle set, weight is the particle weight, and pos_noise and head_noise are the initialized particle position white noise and heading angle white noise, respectively. Align_flag=2, return to (2).
(7) The whole particle group is backed up, and then the particle group is propagated in one step according to formula (1). And (8) executing.
(8) Judging whether the room is indoor or outdoor, if the room is indoor, executing (9), otherwise, judging whether current guard data are available, executing (12) if the current guard data are not available, updating the particle weight according to the formula (2) if the current guard data are available, resampling the particle set, and executing (12);
(9) Judging the value of beacon_enable, if the beacon_enable= false, executing (10), otherwise judging whether a beacon exists in the beacon information searched in one step, if so, updating the particle weight (Bluetooth ranging correction) according to a formula (3), then resampling the particle set, and executing (10), otherwise, directly executing (10);
(10) Judging the current floor according to floor information corresponding to the scanned Bluetooth beacon and the height given by the barometer, and loading an indoor map according to the floor, and executing (11);
(11) Updating the particle set is modified using map constraints. Setting i=1, executing 11.1);
11.1 Selecting an ith particle, connecting the current position of the particle and the position backed up before one-step propagation operation (obtained from the backup particle set in the step (7) by using a straight line in a binary map to obtain a line segment connecting the positions of the particle in the last step and the current step in the filtering, and executing 11.2);
11.2 Detecting whether the line segment passes through the wall in the indoor binary map, namely judging whether the pixel point with the gray value of 1 exists in the pixel points passing through the line segment in the indoor binary map, if so, passing through the wall in the latest propagation process of the particle, indicating that the positioning position error represented by the particle is large, and setting a particle weight i ＝weight i η (where η. Gtoreq.10), 11.3 is performed. Otherwise, execute 11.3);
11.3 If i < N, (total number of particles N in particle set) is determined, i=i+1 is set, and execution returns to 11.1). Otherwise, the particle weights of the particle sets are normalized, and then the particle sets are resampled, and the process is performed (12).
(12) Calculating an estimated value of the current pedestrian position through a weighted sum of particle states and particle weights, converting the estimated value in the local coordinate system into longitude and latitude coordinates, judging the current floor and the height coordinates according to floor information corresponding to the scanned Bluetooth beacons and the height given by the barometer, and returning to the execution (2).
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the invention without departing from the principles thereof are intended to be within the scope of the invention as set forth in the following claims.
Claims (16)
1. The indoor and outdoor seamless positioning method based on multi-information fusion is characterized by comprising the following steps:
step S1: a Bluetooth beacon is arranged at a place where a pedestrian passes; collecting the guide data, ibeacon information and real-time relative position information of pedestrians in real time to form multi-information fusion data;
step S2: judging indoor and outdoor; comprehensively judging whether the signal intensity receiving condition of the Bluetooth beacon, the receiving quality of the satellite positioning data and the real-time relative position information are in the indoor map range or not;
step S3: if the method is judged to be outdoor, positioning is carried out by using a loose combined navigation positioning strategy of the particle filter as a fusion frame, a particle filter motion model is obtained according to real-time relative position information, if the particle filter is unavailable, a weighted average value of particle sets is directly calculated to be used for estimating the position of a pedestrian, if the particle filter is available, a defending observation is added into the particle filter, and then the weighted average value of the particle sets is calculated to be used for estimating the position of the pedestrian; if the pedestrian position estimation method is judged to be indoor, taking particle filtering as a fusion frame, taking real-time relative position information as a particle filtering motion model, adding Bluetooth ranging observation and map constraint observation, and then calculating a weighted average value of particle sets to obtain the pedestrian position estimation; the guide positioning position is used as the weight correction of the particle, and the weight correction formula is as follows:
Wherein w is t (k) The weight of the kth particle at the time t, ρ is a normalized coefficient,
for t time, guard positioning position, (x) t (k),y t (k) At time t) is the position, sigma, represented by the kth particle s The mean square error of Gaussian distribution is related to the positioning accuracy of the guide.
2. The indoor and outdoor seamless positioning method according to claim 1, wherein in the step S1, the real-time relative position information is given by an IMU module fixedly installed in a positioning tag at any one of three positions of a foot, a waist or a shoulder of a pedestrian, which is a two-dimensional rectangular coordinate with respect to a positioning start point.
3. The indoor and outdoor seamless positioning method according to claim 1, wherein in the step S1, the real-time satellite data are obtained by a satellite guiding positioning module and are derived from a positioning navigation system, and the data include the current target longitude and latitude position and the dop value capable of representing the positioning position accuracy, the satellite number and the middle error of the horizontal plane.
4. The indoor and outdoor seamless positioning method according to claim 1, wherein in the step S1, the ibeacon information is obtained through a bluetooth module, and includes a bluetooth beacon number and a corresponding signal strength value.
5. The indoor and outdoor seamless positioning method according to claim 1, wherein in the step S1, the multi-information fusion data is used as a data fusion filter through particle filtering, and the real-time defending data, ibeacon information and real-time relative position information are input into the particle filtering information fusion filter after time synchronization; and taking the real-time relative position information as a particle filtering motion model, taking the defending data, the ibeacon information and the plane map information as filtering observation information, and finally obtaining the longitude, latitude and floor information of the pedestrian subjected to filtering correction through condition judgment and position correction.
6. The indoor and outdoor seamless positioning method according to any one of claims 1 to 5, further comprising a coordinate alignment process; and selecting a guide positioning position, and transforming the real-time relative position information, the ibeacon information and the map position into the same coordinate system through coordinate transformation.
7. The indoor and outdoor seamless positioning method of multi-information fusion according to claim 6, wherein the coordinate alignment process is: firstly, calibrating an indoor map to be used into a global guide map to obtain a coordinate transformation matrix from all pixel points in the indoor map to the global guide map coordinate system, wherein the Bluetooth beacon position coordinate is a coordinate under the map coordinate system, and obtaining the longitude and latitude position of the Bluetooth beacon through the coordinate transformation matrix transformation from the indoor map to the global guide map; and transforming the real-time relative position information coordinate into a map coordinate system to finish coordinate alignment.
8. The multi-information fusion indoor and outdoor seamless positioning method according to claim 6, wherein when the positioning start point is located indoors, coordinate alignment is performed using two bluetooth beacons; the method comprises the steps that a pedestrian carries a tag and sequentially passes under two Bluetooth beacons with a certain distance, the maximum signal intensity of the beacon is searched every time the pedestrian passes through one beacon, the pedestrian is considered to be right under a signal when the maximum signal intensity is obtained, the horizontal projection coordinate of the beacon is taken as the actual coordinate P1 of the pedestrian in a map at the moment, and the horizontal projection coordinate value Q1 of the relative coordinate given by the tag at the moment is recorded; the actual coordinates P2 of pedestrians in the map and the relative coordinates Q2 given by the tags at the time when the pedestrians pass through the second alignment beacon are found out through the same method, and then the relative relation between the vector P2P1 and the vector Q2Q1 is utilized to calculate a planar two-dimensional real-time relative position information track alignment coordinate transformation matrix.
9. The multi-information fusion indoor and outdoor seamless positioning method according to claim 6, wherein when the positioning start point is located outdoors, coordinate alignment is performed by using the guide positioning position; the method comprises the steps of walking outdoors for a certain distance, obtaining the relative track of the guide positioning information and the real-time relative position information in the path, screening position points with higher precision from the guide positioning position by utilizing the dop value and the satellite number information in the guide data, calculating a transformation matrix of the real-time relative position information relative track to the global guide coordinate system through least square estimation, and enabling the sum of the distances from the position points on the real-time relative position information track to the guide position points after the screening to be minimum.
10. The indoor and outdoor seamless positioning method according to any one of claims 1-5, wherein when performing indoor and outdoor judgment, if the received bluetooth beacon signal strength is greater than a set detection threshold, it is inferred that the pedestrian is in a sufficiently close range of the bluetooth beacon, and it is inferred that the pedestrian is indoor at this time; or in the received guide data, the number of satellites is smaller than a given threshold value, the satellite shielding is serious, and the pedestrian is inferred to be in the room at the moment; if the bluetooth beacon state of sufficient signal strength is not received and the number of received satellites is greater than a given threshold, it is determined that the pedestrian is outdoors.
11. The indoor and outdoor seamless positioning method according to claim 6, wherein when the indoor and outdoor judgment is performed after the alignment, firstly judging whether the received bluetooth beacon signal strength is greater than a given threshold value, and if so, the pedestrian is in the room; otherwise, judging whether the satellite number is smaller than a given indoor satellite number threshold value, if so, judging whether the current positioning position is in an indoor map range, and if so, enabling pedestrians to be in the indoor; if it cannot be determined that the pedestrian is indoors by the foregoing steps, it is determined that the pedestrian is outdoors.
12. The indoor and outdoor seamless positioning method according to any one of claims 1 to 5, wherein when indoor positioning is performed by bluetooth, it comprises the following means (a) or (b):
(a) The characteristic that propagation in a Bluetooth signal intensity space decays along with the distance is utilized, the approximate distance from Bluetooth is obtained according to an empirical formula of the distance and the signal intensity, and then a positioning position is obtained through triangular positioning;
(b) By utilizing the characteristic that the signal intensity around the Bluetooth beacon is distributed in a fingerprint shape, a Bluetooth signal intensity fingerprint library is established, and then the positioning position is obtained through fingerprint matching.
13. The indoor and outdoor seamless positioning method according to any one of claims 1-5, wherein in step S3, map constraint is performed by taking map information as an observation of particle filtering, that is, using a through-wall detection method to determine all particles, and if a particle passes through a wall, reducing the weight of the particle accordingly; after the particle filtering resampling, the through-wall particles are replaced by the replica particles of the non-through-wall particles, so that the accuracy of the particle set on the approximation of the actual label position is improved, and the correction of the positioning position is realized.
14. The multi-information fusion indoor and outdoor seamless positioning method according to any one of claims 1-5, further comprising acquisition of positioning position height and floor switching of an indoor map, wherein the height is acquired by an air pressure sensor, meanwhile, a bluetooth beacon deployed on different floors is utilized to judge the floor where a pedestrian is located, and when the signal intensity scanned by a bluetooth module is greater than a bluetooth beacon with a given threshold value, the floor where the beacon is located is used as the current floor where the pedestrian is located; and the map switching among different floors is judged and switched through the Bluetooth beacons.
15. The indoor and outdoor seamless positioning method according to any one of claims 1 to 5, wherein the pilot positioning position data is screened by two different screens in the above steps; firstly, carrying out primary screening on satellite positioning position data according to the dop value, the satellite number and the middle error of the horizontal plane in the satellite guiding data, if the satellite guiding data passes the primary screening, selecting a history Wei Daogui trace after the last section of screening to match with the positioning trace of the real-time relative position information corresponding to the section of trace, giving a minimum matching residual, and if the minimum matching residual is smaller than a given available threshold, considering that the satellite data is reliable, otherwise, the satellite positioning data is unreliable, and cannot be used for fusion positioning, and the satellite positioning data is unavailable.
16. The indoor and outdoor seamless positioning method according to any one of claims 1-5, wherein the principle of bluetooth beacon deployment is as follows:
(1) A beacon is arranged on a door frame of a stair entrance of each indoor floor for identifying, correcting and positioning the floor;
(2) A Bluetooth beacon is arranged on a door frame of each door of each floor to be positioned;
(3) And Bluetooth beacons are distributed in places where the probability of passing by other pedestrians is high, so that the Bluetooth deployment density is ensured.
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