CN111083659B - Indoor positioning fusion method - Google Patents
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- CN111083659B CN111083659B CN202010024107.5A CN202010024107A CN111083659B CN 111083659 B CN111083659 B CN 111083659B CN 202010024107 A CN202010024107 A CN 202010024107A CN 111083659 B CN111083659 B CN 111083659B
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- 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
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- 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
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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
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
Abstract
An indoor positioning fusion method relates to an indoor positioning technology, in particular to a method for carrying out comprehensive positioning according to Bluetooth signals, inertial navigation data and geomagnetic data. The terminal sends a Bluetooth signal at regular time, and a Bluetooth receiving tag is screened by a game theory method according to the inertial navigation positioning position; and after the fingerprints are matched, screening fingerprint combinations according to the inertial navigation positioning position and the geomagnetic positioning position, obtaining a Bluetooth positioning position according to the screened fingerprint combinations, and obtaining a final positioning point according to the inertial navigation positioning position and the Bluetooth positioning position. By adopting the method provided by the invention, the Bluetooth receiving label interfered by the multipath effect can be effectively deleted, and only the normally received Bluetooth receiving label is selected for fingerprint matching; the final positioning point is comprehensively corrected by a Bluetooth positioning position and an inertial navigation positioning position, and several positioning technologies complement each other, so that the positioning is accurate.
Description
Technical Field
The invention relates to an indoor positioning technology, in particular to a method for comprehensively positioning according to Bluetooth signals, inertial navigation data and geomagnetic data.
Background
Obtaining the position information of the target has a very important meaning in many fields, and the positioning technology is getting more and more attention and research of people. The existing mature positioning service is limited to outdoor scenes, and satellite positioning systems such as a Global Positioning System (GPS), a Beidou and other Global Navigation Satellite Systems (GNSS) can well solve the outdoor positioning problem, but the satellite signal strength and quality are rapidly reduced in indoor and other shielding environments. The indoor signal quality and strength of the ground cellular mobile network are far better than those of a satellite system, but the positioning accuracy of the mobile cellular network is poor and is in the order of tens of meters to hundreds of meters.
In special scenes, such as prisons, hospitals, nursing homes, commercial services, parks, scenic spots and in the field of warehousing services, high-precision indoor positioning technology has a very important meaning and is a basic condition for some applications. In the aspect of social public safety guarantee, an accurate indoor positioning technology can provide indoor navigation service for firefighters, policemen and other personnel; in prisons, the moving range of prisoners can be effectively monitored; the intelligent navigation system can provide accurate navigation in indoor environments such as markets, museums and the like, and can provide nursing and positioning services for patients and old people in hospitals and nursing homes. In a warehouse service, items may be located.
Currently, many indoor positioning technologies are available for positioning a moving object in an indoor space. For example, Wi-Fi, Bluetooth, infrared, ultra wideband, RFID, ZigBee, ultrasonic, and the like.
Due to the complex indoor environment, the wireless signals are easy to generate interference such as multipath effect, and the accurate positioning is difficult to realize by adopting a single technical means.
The applicant proposes "an indoor positioning system and method based on bluetooth" (201711238640.6) in 2017, and in practical application, as the indoor environment becomes more complex, the positioning requirement cannot be met.
Disclosure of Invention
The invention aims to provide a method for eliminating multipath effect caused by complicated indoor environment and providing more accurate indoor positioning.
In order to achieve the purpose, the invention adopts the technical scheme that: an indoor positioning fusion method is realized by an indoor positioning system based on Bluetooth, wherein the positioning system comprises a terminal with a Bluetooth signal sending device, a Bluetooth receiving tag, a positioning management server and a communication network for connecting the Bluetooth receiving tag and the positioning management server; drawing a positioning space map, setting a positioning reference point on the map, collecting fingerprint data on the positioning reference point, filtering, and storing the fingerprint data in a database, wherein the positioning reference point is a fingerprint point.
The key point is that: the terminal is provided with an MEMS sensor which comprises an acceleration sensor, a gyroscope and a geomagnetic sensor.
The method comprises the following steps:
and step A, acquiring all Bluetooth receiving tags which receive Bluetooth signals sent by the terminal and corresponding signal intensity.
And step B, taking the last positioning result as a reference, and obtaining the inertial navigation positioning position according to the data of the MEMS sensor.
And step C, screening out a Bluetooth receiving tag set according to the information obtained in the step A and the step B.
And D, performing fingerprint matching on the Bluetooth receiving label set obtained in the step C to obtain a fingerprint point set M.
And E, obtaining a geomagnetic positioning position according to the data of the MEMS sensor.
And F, screening the fingerprint point set M according to the inertial navigation positioning position and the geomagnetic positioning position to obtain a fingerprint point set N.
And G, calculating the Bluetooth positioning position according to the fingerprint electric set N.
And H, obtaining a final positioning point according to the inertial navigation positioning position and the Bluetooth positioning position.
Further, a Bluetooth receiving label set and a fingerprint point set are screened out according to a game theory.
The above steps are performed in each positioning cycle.
According to the method, firstly, a Bluetooth receiving tag interfered by multipath effect is deleted according to the receiving intensity of a Bluetooth signal and the position of the receiving tag, then fingerprint matching is carried out, then, whether the matched fingerprint falls into an inertial navigation positioning position and the periphery of the geomagnetic positioning position or not is judged, the fingerprint which is mismatched is deleted, the Bluetooth positioning position is calculated according to the selected fingerprint, and then the inertial navigation positioning position is used for correcting the Bluetooth positioning position to obtain a final positioning point.
In the invention, the Bluetooth receiving tags and fingerprints are screened by depending on the inertial navigation positioning position and the geomagnetic positioning position. The inertial navigation positioning can generate accumulated errors, but in the invention, the reference position of the inertial navigation positioning is the final positioning point obtained by the last positioning, and is relatively accurate position data, and the time interval of the two times of positioning is not large, so the accumulated errors can be ignored.
By adopting the method provided by the invention, the Bluetooth receiving label interfered by the multipath effect can be effectively deleted, and only the normally received Bluetooth receiving label is selected for fingerprint matching; the inertial navigation positioning is based on the last indoor positioning result, and the result is credible; performing secondary screening on the matched fingerprints according to the inertial navigation positioning position and the geomagnetic positioning position; the final positioning point is comprehensively corrected by a Bluetooth positioning position and an inertial navigation positioning position, and several positioning technologies complement each other, so that the positioning is accurate.
Drawings
Fig. 1 is a schematic diagram of the arrangement and positioning of an indoor positioning space.
Detailed Description
And (5) implementing the foundation.
The present invention is based on the applicant's prior application entitled bluetooth-based indoor positioning system and method (201711238640.6).
The indoor positioning system based on the Bluetooth comprises a terminal with a Bluetooth signal sending device, a Bluetooth receiving tag, a positioning management server and a communication network for connecting the Bluetooth receiving tag and the positioning management server, wherein the terminal also comprises an acceleration sensor; the communication network is composed of a 485 concentrator and a communication line, the 485 concentrator is respectively connected with the Bluetooth receiving tag and the communication gateway through the communication line, and the communication gateway is connected with the positioning management server.
The system divides the positioning space into different positioning areas according to the existing physical separation, and the positioning areas are also areas divided at the minimum, and each positioning area is provided with 2 or more than 2 Bluetooth receiving tags; each Bluetooth receiving tag is provided with a coverage area, and the coverage areas are a positioning area where the Bluetooth receiving tag is located and an adjacent positioning area; the positioning management server stores a map of a positioning space, IDs of Bluetooth receiving tags and coverage ranges.
The positioning management server stores a fingerprint information database consisting of position information of the positioning reference points and signal intensity vectors, and the position information of the positioning reference points comprises coordinates and a belonging positioning area.
The terminal broadcasts information at regular time, the Bluetooth receiving tag receives the information and sends the received signal strength to the positioning management server.
When the above method is performed, first, preliminary preparation is performed.
Establishing a reference coordinate system, drawing a positioning space map in the reference coordinate system, setting the lower left corner of the indoor plane map as a coordinate origin, setting one wall of the building as an X axis, and setting the other wall vertical to the building as a Y axis; and drawing an indoor plan in actual size, wherein the indoor plan comprises physical isolation of walls, doors and the like.
Bluetooth receiving tags are arranged in each area, the 485 communication network is connected, and the coverage range of each Bluetooth receiving tag is set and stored in a server.
And setting the position of a positioning reference point in each positioning area.
Fingerprint data of each positioning reference point is collected to generate a fingerprint database. The positioning reference points are fingerprint points.
As is well known, the transmission of bluetooth signals is greatly influenced by the environment, and in order to make the environment during acquisition closer to the actual use environment, each room, corridor, etc. of a floor are arranged in a daily use state during signal acquisition, and permanent articles, such as tables, chairs, cabinets, etc., are placed.
The terminal is the bracelet, wears on the wrist, because human sheltering from, even the people is in different orientation, when different positions in same position, and the broadcast signal intensity that the bracelet was received to the bluetooth receiving tag is also different.
A person wears the bracelet, stands on the positioning reference point, and selects a use scene facing to the east, the west, the south and the north. In each scene, the bracelet sends 100 broadcasts of intensity 0 dBm.
In each scene, the Bluetooth receiving tags which are closer to the positioning reference point can receive all broadcast information, while the Bluetooth receiving tags which are farther from the positioning reference point can receive a part of broadcast information, and some Bluetooth receiving tags cannot receive broadcast information.
During the data acquisition, only one or a few bracelet sends the broadcast information, and the radio environment is comparatively clean, for more accurate fingerprint data that obtains, receives the label to the bluetooth that receives the information, carries out filtering process to the signal strength who receives the information.
Performing fusion filtering processing based on Gaussian filtering, Kalman filtering and mean value filtering on the signal strength, and storing a piece of fingerprint data which is used as the positioning reference point into a database by combining (ID 1, RSSI 1), (ID 2, RSSI 2),.........., (IDn, RSSIn) and position information, wherein n is the number of Bluetooth receiving tags, IDm (1 < = m < = n) is the identification code of the mth Bluetooth receiving tag, and RSSIm (1 < = m < = n) is the signal strength of the filtered mth Bluetooth receiving tag; if the Bluetooth receiving tag with the IDm does not receive the broadcast information, the RSSIm is set to have a minimum intensity value of-200 dBm.
Fuse filtering and handle, according to the quantity of receiving bracelet broadcast signal, divide two kinds of situations:
case 1: if the number of the RSSIs belonging to a certain Bluetooth receiving tag (AP) is larger than or equal to an RSSI number threshold value THRE _ RSSI _ NUM, if so, 5, calculating the average value mu and the standard deviation sigma of each piece of RSSI data belonging to the AP (each piece of data comprises RSSI values of a plurality of APs), keeping the data of the RSSI values between mu-3 sigma and mu +3 sigma for the RSSI component of the AP, rejecting the data which are not in the range as the wild values, after the processing is finished, performing Kalman filtering processing on the RSSI data kept by each AP (filtering the data according to the receiving sequence by taking the average value u as the initial value of a Kalman filter), and calculating the average value of the processed data to be used as the fingerprint point RSSI vector of the AP.
Case 2: and if the RSSI number belonging to a certain AP is less than the RSSI number threshold value THRE _ RSSI _ NUM, directly averaging the RSSI component of the AP to be used as the RSSI vector of the fingerprint point of the AP.
Mean value: (S)1+S2+...+Sk) And k, wherein k is the number of received broadcast messages and S is the signal strength.
In the above process, the signal strength minimum, i.e., -200dBm, is not processed. In the following description, the signal strength minimum value of-200 dBm is a sign of no received signal, and is used only for comparison and no arithmetic processing is performed.
One positioning reference point is provided with 4 pieces of fingerprint data which belong to different directions.
In fig. 1, the distribution of bluetooth reception tags and fingerprint points in an indoor positioning space is shown.
Provided is an implementation mode.
And step A, acquiring all Bluetooth receiving tags which receive Bluetooth signals sent by the terminal and corresponding signal intensity.
The terminal sends broadcast information with the intensity of 0dBm at a fixed frequency (such as 5 Hz); the Bluetooth receiving tag sends the received broadcast information to a positioning management server together with the ID and the signal strength, and the positioning management server filters the information to generate the following real-time vectors: (ID 1, RSSI 1), (ID 2, RSSI 2),.
Wherein n is the number of bluetooth receiving tags, IDm (1 < = m < = n) is the id of the mth bluetooth receiving tag, RSSIm (1 < = m < = n) is the arithmetic average of the signal strength of the terminal received by the mth bluetooth receiving tag, and RSSIm is set to-200 dBm if the bluetooth receiving tag with the id does not receive the broadcast information of the terminal.
And step B, taking the last positioning result as a reference, and obtaining the inertial navigation positioning position according to the data of the acceleration sensor and the gyroscope.
The indoor positioning technology based on the MEMS inertial navigation chip uses a pedestrian track calculation method, the walking step number and the estimated step length are calculated based on the gait characteristics of pedestrians, and the position of the pedestrian is calculated by combining with course information.
A gait detection model and a step size model are respectively established based on a triaxial MEMS acceleration sensor, a course model is established based on a triaxial MEMS gyroscope, and the position change of the positioning terminal is obtained by using a track calculation method. The step counting model counts steps of the walking process of the human body according to the periodic change of the acceleration, the step size model determines model parameters according to the walking characteristics of each person, and the heading model calculates the walking direction of the human body based on data output by the gyroscope.
The last positioning result is shown in fig. 1 as the position of "time T0".
And step C, screening out a Bluetooth receiving tag set according to the information obtained in the step A and the step B.
And B, the Bluetooth receiving tag obtained in the step A receives some abnormal signals due to the influence of indoor multipath effect. This step rejects these tags.
The rejection can be carried out according to the signal intensity and the distance between the Bluetooth receiving tag and the last positioning point. However, if the terminal moves faster, the distance between the last positioning point and the current positioning point is longer, and the situation of mistaken deletion is easy to occur.
In step C of the invention, a Bluetooth receiving label set is screened according to a game theory, and the method comprises the following steps:
step C1, aiming at each bluetooth receiving tag APi which receives the bluetooth signal sent by the terminal, assuming that the signal strength is APi _ rssi, then:
APi _ intensity _ distance =1 if APi _ rssi > = -30 dbm;
APi _ intensity _ distance =2 if-30 dbm > APi _ rssi > = -40 dbm;
APi _ intensity _ distance =3 if-40 dbm > APi _ rssi > = -50 dbm;
APi _ intensity _ distance =4 if-50 dbm > APi _ rssi > = -55 dbm;
APi _ intensity _ distance =5 if-55 dbm > APi _ rssi > = -60 dbm;
APi _ intensity _ distance =6 if-60 dbm > APi _ rssi > = -65 dbm;
APi _ intensity _ distance =7 if-65 dbm > APi _ rssi > = -70 dbm;
APi _ intensity _ distance =8 if-70 dbm > APi _ rssi > = -80 dbm;
APi _ intensity _ distance =9 if-80 dbm > APi _ rssi > = -90 dbm;
and if the APi _ rssi < -90dbm, then the APi _ intensity _ distance = 10.
The APi _ intensity _ distance represents the intensity of the received bluetooth signal sent by the terminal, and the larger the signal intensity is, the smaller the value is.
Step C2, assuming that APx is farthest from the inertial navigation positioning position in all the Bluetooth receiving tags receiving the Bluetooth signals, and dividing the distance from the APx to the inertial navigation positioning position into 10 equal parts; for each bluetooth receiving tag APi which receives a bluetooth signal sent by a terminal, APi _ distance = d, d is the distance from the APi to the inertial navigation positioning position, the maximum is 10, and the minimum is 1.
Signals sent by the terminal at different times are possibly different in the Bluetooth receiving tags receiving the signals due to factors such as the position of the terminal, the surrounding environment and the like.
The reference of the inertial navigation positioning is the last positioning result, and the last positioning result is assumed to be accurate, and because the interval of the two positioning times is short (such as 10 seconds), the accumulated error of the inertial navigation positioning can be ignored, so that the position of the inertial navigation positioning can be considered to be accurate and close to the final positioning result.
The APi _ distance represents the distance from the bluetooth receiving tag to the temporary positioning point (inertial navigation positioning point), and the closer the distance, the smaller the value.
And step C3, aiming at each Bluetooth receiving tag APi which receives the Bluetooth signal sent by the terminal, calculating APi _ uniform = | APi _ intensity _ distance-APi _ distance |.
The APi _ uniformity represents a difference between the signal strength received by a certain bluetooth reception tag and a distance from a temporary positioning point (inertial navigation positioning point).
If the signal is strong and close to the temporary positioning point or the signal is weak and far from the temporary positioning point, the consistency is good, the selection possibility is high, otherwise, the consistency is poor.
And step C4, setting a threshold value D _ threshold = m, wherein m is a positive integer and 2< m <5, and calculating the revenue function Ui = D _ threshold-APi _ uniformity of each APi.
Setting and calculating the revenue function is the basis of game theory. m is related to an application scene, the arrangement density of indoor Bluetooth receiving tags and the like, and the larger the density is, the smaller the m value is.
If APi _ uniformity is small, consistency is good, and if APi _ uniformity is large, consistency is poor. The Bluetooth receiving label with good consistency is selected as the positioning basis.
According to the game theory, the game process is to select a group of Bluetooth receiving tags with the largest revenue function. If there are 4 bluetooth receiving tags AP1, AP2, AP3 and AP4 receiving the bluetooth signal from the terminal, the possible combinations are: { AP1}, { AP2}, { AP3}, { AP4}, { AP1, AP2}, { AP1, AP3}, { AP1, AP4}, { AP2, AP3}, { AP2, AP4}, { AP3, AP4}, { AP1, AP2, AP3}, { AP1, AP2, AP4}, { AP2, AP3, AP4}, { AP1, AP2, AP3, AP4 }.
And respectively calculating the sum of the revenue functions of the combinations, and taking the combination corresponding to the maximum value to obtain a Bluetooth receiving tag set.
It is clear that if all the revenue functions in the combination are greater than 0, then the sum of the revenue functions is maximum.
In order to simplify the above process, in the present application, an APi of the revenue function Ui > =0 is selected, and then a bluetooth reception tag set is obtained. APi with Ui =0 does not contribute to the overall revenue function, but in order to obtain more bluetooth reception tags to increase the positioning accuracy, such tags are also included in the selection range.
As shown in fig. 1, at time T0+ T, assuming that all 9 bluetooth receiving tags can receive bluetooth signals, AP9 is farthest from the inertial navigation position.
Through the above process, a bluetooth receiving tag set is obtained, such as { AP1, AP2, AP3, AP4, AP5, AP8}, and other bluetooth receiving tags are rejected because the revenue function is less than 0.
Bluetooth positioning requires a large amount of bluetooth to receive tag data. If the number of the screened Bluetooth receiving tags in the steps is too small, the environment is complex, and the Bluetooth positioning is unreliable. If the number of the bluetooth receiving tags screened in the step C is less than the threshold _ num1, the bluetooth positioning is not used in the current positioning, the final positioning position is the inertial navigation positioning position, the positioning is finished, the threshold _ num1 is a positive integer, and the threshold _ num1 is greater than 3.
Generally, the value of m is fixed for one application scenario. But in the initial application phase of a scenario, the selection of m may not be correct. If the screened Bluetooth receiving tags are few in multiple positioning processes (such as 3 times), the value of m is increased.
And D, performing fingerprint matching on the Bluetooth receiving label set obtained in the step C to obtain a fingerprint point set M.
Fingerprint matching uses the method proposed in the applicant's prior application a bluetooth-based indoor positioning system and method (201711238640.6).
Selecting fingerprint data according to the following principle:
1-1 all tags that receive a bluetooth signal are included in the tags that have a signal in the fingerprint data.
1-2, selecting the Bluetooth receiving labels with strongest signals and second strongest signals from all the labels receiving the Bluetooth signals; in the fingerprint data, the signal strength of the two tags is within the range of +/-RSSI _ TOLER of the strongest and second strongest signals, the RSSI _ TOLER is an error tolerance value, and the range of the RSSI _ TOLER is 6dBm-10 dBm.
All fingerprint data satisfying the above conditions constitute a fingerprint point set M.
In fig. 1, it is assumed that a set of fingerprint points M = {3, 6, 7, 8, 9, 10, 11, 12, 13, 14} satisfying the above condition.
And E, obtaining a geomagnetic positioning position according to the data of the MEMS sensor.
Many methods for geomagnetic positioning are disclosed in detail in the publication No. 201810463296.9, and will not be described in detail herein.
And F, screening the fingerprint set M according to the inertial navigation positioning position and the geomagnetic positioning position to obtain a fingerprint point set N.
And D, the fingerprint point set M obtained in the step D can cause mismatching due to multipath effect, and the step F is to remove the mismatched fingerprint points.
As shown in fig. 1, the fingerprint point set M includes 10 fingerprint points of 3, 6, 7, 8, 9, 10, 11, 12, 13, and 14.
In the step F, the fingerprint set M is screened according to the game theory, and the method comprises the following steps:
and F1, setting a circular area with the radius of R _ INS as a credible range D _ INS by taking the coordinate of the inertial navigation positioning position as a circle center, wherein the distance R _ INS is greater than 2 meters.
Step F2, setting the circular area with radius R _ Geomagnetism as the credible range D _ Geomagnetism with the coordinate of the geomagnetic positioning position as the center of circle, wherein R _ Geomagnetism is larger than 2.5 meters.
Step F3, for each fingerprint point Fi in the fingerprint point combination M, the following calculation is performed.
Step F3-1: the initial value of the revenue function Ui of the fingerprint point is set to 0.
Step F3-2: if the fingerprint point Fi is in the range of D _ INS, Ui = Ui +2, otherwise Ui = Ui-1; if the fingerprint point Fi is within the range D _ geomagnetetism, Ui = Ui +1.5, otherwise Ui = Ui-1.
Step F4, selecting Fi of the revenue function Ui > =0 to obtain the fingerprint point set N.
In step F4, the calculation of the revenue function is also simplified.
Referring to fig. 1, fingerprints 7, 8, 12, and 13 satisfy the above condition, and the resulting fingerprint point set N includes these 4 fingerprints.
If the number of the fingerprint points in the fingerprint point set N selected in the step F is less than threshold _ num2, threshold _ num2 is a positive integer and threshold _ num2 is greater than 2, which indicates that the environment is complex and the bluetooth positioning is unreliable, the final positioning point is the inertial navigation positioning position, and the positioning is finished.
And G, calculating the Bluetooth positioning position according to the fingerprint point set N.
Suppose that the real-time vector of the bluetooth receiving tag APx receiving the terminal bluetooth signal and the corresponding signal strength is: (APi, APi _ rssi), (APj, APj _ rssi),. · and (APm, APm _ rssi).
The data of the fingerprint points are uniformly expressed as: (AP1, R1), (AP 2, R2),..... -, (APn, Rn).
{ APi, APj.,..,. APm } is a subset of { AP1, AP 2.,..,. APn }.
Euclidean distance: SQRT ((AP 1_ rsi-R1)2+(AP2_rssi―R2)2+... ...+ (APn_rssi―Rn)2 )。
If APx in the fingerprint point data is not present in the live vector, then in the above equation, the corresponding APx _ rssi is set to 0.
And calculating Euclidean distances between all the fingerprint points in the fingerprint point set N and the real-time vector.
And if the Euclidean distance between a certain fingerprint point and the real-time vector is 0, the coordinate of the positioning reference point corresponding to the fingerprint point is the Bluetooth positioning position.
Otherwise, calculating the reciprocal of each Euclidean distance, solving a square value, then performing normalization processing, taking the square value as a weight item, and calculating the Bluetooth positioning position according to the positioning reference point coordinates corresponding to the fingerprint points in the fingerprint point set N.
In this embodiment, it is assumed that the set of bluetooth receiving tags obtained in step C is { APi, APj. ·.
And step F, obtaining a fingerprint point set N, wherein the fingerprint point set N comprises fingerprints 7, 8, 12 and 13. And calculating the Euclidean distance between each fingerprint point and the real-time vector to finally obtain the Bluetooth positioning position.
And H, obtaining a final positioning point according to the inertial navigation positioning position and the Bluetooth positioning position.
The coordinates of the inertial navigation positioning Position are Position _ ins, the Bluetooth positioning Position is Position _ rssi,
the final anchor point Position = a Position rssi + b Position ins,
the parameters a >0, b >0, a + b =1, and a is a value between 0.6 and 0.85, and the specific numerical value is set according to the arrangement density of the Bluetooth receiving tags.
And calculating the positioning point at the T0+ T moment by adopting a weighted fusion algorithm and taking the positioning point at the T0 moment as a reference.
Claims (4)
1. An indoor positioning fusion method is realized based on a Bluetooth indoor positioning system, wherein the positioning system comprises a terminal with a Bluetooth signal sending device, a Bluetooth receiving tag, a positioning management server and a communication network for connecting the Bluetooth receiving tag and the positioning management server; drawing a positioning space map, setting a positioning reference point on the map, collecting fingerprint data on the positioning reference point, filtering, and storing the fingerprint data in a database, wherein the positioning reference point is a fingerprint point;
the method is characterized in that:
configuring an MEMS sensor in the terminal;
the method comprises the following steps:
step A, acquiring all Bluetooth receiving tags which receive Bluetooth signals sent by a terminal and corresponding signal intensity;
step B, taking the last positioning result as a reference, and obtaining an inertial navigation positioning position according to the data of the MEMS sensor;
step C, screening out a Bluetooth receiving tag set according to the information obtained in the step A and the step B;
step D, performing fingerprint matching on the Bluetooth receiving label set obtained in the step C to obtain a fingerprint point set M;
step E, obtaining a geomagnetic positioning position according to the data of the MEMS sensor;
step F, screening the fingerprint point set M according to the inertial navigation positioning position and the geomagnetic positioning position to obtain a fingerprint point set N;
g, calculating a Bluetooth positioning position according to the fingerprint point set N;
step H, obtaining a final positioning point according to the inertial navigation positioning position and the Bluetooth positioning position;
the MEMS sensor comprises an acceleration sensor, a gyroscope and a geomagnetic sensor;
in the step C, a Bluetooth receiving label set is screened according to a game theory, and the method comprises the following steps:
step C1, aiming at each bluetooth receiving tag APi which receives the bluetooth signal sent by the terminal, assuming that the signal strength is APi _ rssi, then:
APi _ intensity _ distance =1 if APi _ rssi > = -30 dbm;
APi _ intensity _ distance =2 if-30 dbm > APi _ rssi > = -40 dbm;
APi _ intensity _ distance =3 if-40 dbm > APi _ rssi > = -50 dbm;
APi _ intensity _ distance =4 if-50 dbm > APi _ rssi > = -55 dbm;
APi _ intensity _ distance =5 if-55 dbm > APi _ rssi > = -60 dbm;
APi _ intensity _ distance =6 if-60 dbm > APi _ rssi > = -65 dbm;
APi _ intensity _ distance =7 if-65 dbm > APi _ rssi > = -70 dbm;
APi _ intensity _ distance =8 if-70 dbm > APi _ rssi > = -80 dbm;
APi _ intensity _ distance =9 if-80 dbm > APi _ rssi > = -90 dbm;
APi _ intensity _ distance =10 if APi _ rssi < -90 dbm;
step C2, assuming that APx is farthest from the inertial navigation positioning position in all the Bluetooth receiving tags receiving the Bluetooth signals, and dividing the distance from the APx to the inertial navigation positioning position into 10 equal parts; aiming at each Bluetooth receiving tag APi which receives a Bluetooth signal sent by a terminal, APi _ distance = d, wherein d is the distance from the APi to an inertial navigation positioning position, the maximum is 10, and the minimum is 1;
step C3, aiming at each Bluetooth receiving label APi which receives the Bluetooth signal sent by the terminal, calculating APi _ uniform = | APi _ intensity _ distance-APi _ distance |;
step C4, setting a threshold value D _ threshold = m, wherein m is a positive integer and 2< m <5, and calculating a revenue function Ui = D _ threshold-APi _ uniform of each APi;
step C5, selecting an APi of a revenue function Ui > =0 to obtain a Bluetooth receiving label set;
in the step F, the fingerprint point set M is screened according to the game theory, and the method comprises the following steps:
step F1, setting a circular area with the radius of R _ INS as a credible range D _ INS by taking the coordinate of the inertial navigation positioning position as a circle center, wherein the radius of R _ INS is more than 2 meters;
step F2, setting a circular area with the radius R _ Geomagnetism as a credible range D _ Geomagnetism by taking the coordinate of the geomagnetic positioning position as a circle center, wherein the R _ Geomagnetism is more than 2.5 meters;
step F3, for each fingerprint point Fi in the fingerprint point combination M, the following calculation is performed:
step F3-1: setting the initial value of the revenue function Ui of the fingerprint point as 0;
step F3-2: if the fingerprint point Fi is in the range of D _ INS, Ui = Ui +2, otherwise Ui = Ui-1; if the fingerprint point Fi is within the range of D _ geomagnetetism, Ui = Ui +1.5, otherwise Ui = Ui-1;
step F4, selecting Fi of the revenue function Ui > =0 to obtain the fingerprint point set N.
2. The method of claim 1, wherein: and if the number of the tags in the bluetooth receiving tag set selected in the step C is less than hreshold _ num1 and hreshold _ num1>3, the final positioning point is the inertial navigation positioning position, and the positioning is finished.
3. The method according to claim 1 or 2, characterized in that: and F, if the number of the fingerprint points in the fingerprint point set N screened in the step F is less than hreshold _ num2 and hreshold _ num2>2, the final positioning point is the inertial navigation positioning position, and the positioning is finished.
4. The method of claim 1, wherein:
in step H, the coordinate of the inertial navigation positioning Position is Position _ ins, the Bluetooth positioning Position is Position _ rssi,
the final anchor point Position = a Position rssi + b Position ins,
wherein the parameters a >0, b >0, a + b =1, a taking a value between 0.6 and 0.85.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106382931A (en) * | 2016-08-19 | 2017-02-08 | 北京羲和科技有限公司 | An indoor positioning method and a device therefor |
| CN107014375A (en) * | 2017-02-22 | 2017-08-04 | 上海谦尊升网络科技有限公司 | The indoor locating system and method for ultralow deployment |
| CN109298436A (en) * | 2018-05-15 | 2019-02-01 | 重庆邮电大学 | A kind of indoor positioning and air navigation aid of multi-information fusion |
| US10328342B2 (en) * | 2015-09-24 | 2019-06-25 | Intel Corporation | Magic wand methods, apparatuses and systems for defining, initiating, and conducting quests |
Family Cites Families (1)
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10328342B2 (en) * | 2015-09-24 | 2019-06-25 | Intel Corporation | Magic wand methods, apparatuses and systems for defining, initiating, and conducting quests |
| CN106382931A (en) * | 2016-08-19 | 2017-02-08 | 北京羲和科技有限公司 | An indoor positioning method and a device therefor |
| CN107014375A (en) * | 2017-02-22 | 2017-08-04 | 上海谦尊升网络科技有限公司 | The indoor locating system and method for ultralow deployment |
| CN109298436A (en) * | 2018-05-15 | 2019-02-01 | 重庆邮电大学 | A kind of indoor positioning and air navigation aid of multi-information fusion |
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