An asynchronous fusion positioning method based on arrival angle and RSSI value

Abstract

The invention discloses an asynchronous fusion positioning method based on arrival angle and RSSI value, comprising: a base station sends information extracted from a radio signal periodically broadcast by a terminal to a server together with base station information; the server classifies and groups the received data according to the terminal MAC address and the base station MAC address; within a time interval T, each type of data, data within a time period NT of each group of data is taken as a group, clustered according to RSSI value and abnormal data is excluded, and each group of clustered data is recombined for fusion positioning; preliminary positioning is performed by using the pole method according to information such as base station position coordinates and terminal working height, and the area is expanded to form a fuzzy positioning area, and then the weight of the fuzzy positioning area is designed according to the arrival angle and RSSI value, the weights of the overlapping areas are superimposed, and the center of gravity of the area with the largest weight is used as the fusion positioning estimation value of the terminal; finally, Kalman filtering is performed on each type of fusion positioning estimation value according to the time interval T to obtain a stable fusion result.

Description

Technical Field

[0001] The invention relates to the technical field of radio signal direction finding, and in particular to an asynchronous fusion positioning method based on arrival angle and RSSI value. Background Art

[0002] With the development of wireless communication technology and the popularization of mobile intelligent terminals, indoor positioning has become a hot application in the current information industry and presents a broad market prospect. The system based on multi-station radio direction finding positioning has high positioning accuracy, but it is affected by multipath, interference, occlusion, etc., and the positioning stability faces great challenges. The present invention classifies and groups observation data such as multi-station direction finding and RSSI values ​​according to the terminal MAC address and the base station MAC address, and sorts them according to the receiving time. Within the time interval T, each type of data is classified as a group within the NT time period of each group of data, clustered according to the RSSI value and excludes abnormal data, and initially locates by the pole method according to the base station location coordinates, the terminal working height and other information and expands to the surroundings to form a fuzzy positioning area, and then designs the fuzzy positioning area weight according to the arrival angle and RSSI value, and the overlapping area weights are superimposed. The center of gravity of the area with the largest weight is used as the fusion positioning estimate of the terminal. Finally, each type of fusion positioning estimate is subjected to Kalman filtering at the time interval T to obtain a stable fusion result. The present invention enables the server to obtain a stable and accurate terminal position estimate, and has the characteristics of asynchronous fusion and high positioning accuracy. Summary of the invention

[0003] In order to overcome the deficiencies in the prior art, the present invention provides an asynchronous fusion positioning method based on arrival angle and RSSI value, which can enable the server to obtain a stable and accurate terminal position estimation value, and has the characteristics of asynchronous fusion and high positioning accuracy.

[0004] In order to achieve the above-mentioned invention object, the technical solution adopted to solve the technical problem is as follows:

[0005] An asynchronous fusion positioning method based on arrival angle and RSSI value includes the following steps:

[0006] Step S1: The base station sends the terminal MAC address, arrival angle, RSSI value and base station MAC address extracted from the radio signal periodically broadcast by the terminal to the server;

[0007] Step S2: The server marks the received data with a receiving time, classifies the data according to the terminal MAC address, groups each type of data according to the base station MAC address, and sorts each group of data according to the receiving time;

[0008] Step S3: for each type of data within the time interval T, the data within each group of data time period NT is taken as a group, clustered according to the RSSI value and the abnormal data is excluded, and the clustered data of each group is recombined for fusion positioning;

[0009] Step S4: Preliminary positioning is performed using the pole method based on the base station location coordinates and the terminal working height information, and then expanded to form a fuzzy positioning area in all directions. The fuzzy positioning area weight is then designed based on the arrival angle and RSSI value. The overlapping area weights are superimposed, and the center of gravity of the area with the largest weight is used as the fusion positioning estimate of the terminal.

[0010] Step S5: Perform Kalman filtering on each type of fused positioning estimation value at time interval T to obtain a stable fusion result.

[0011] Furthermore, the step S1 includes the following steps:

[0012] Step S11: The radio signal periodically broadcast by the terminal includes a MAC address used to distinguish the terminal;

[0013] Step S12: The base station observes the radio signal broadcast by the terminal and extracts the arrival angle, RSSI value and MAC address;

[0014] Step S13: The base station actively pushes the extracted terminal information and the MAC address of the base station to the server.

[0015] Furthermore, the step S2 includes the following steps:

[0016] Step S21: the server receives multiple terminal observation data pushed by multiple base stations and marks the receiving time stamp;

[0017] Step S22: The server classifies the received data according to the terminal MAC address, and all data in each category corresponds to all information of a terminal;

[0018] Step S23: the server groups each type of data according to the base station MAC address, and all data in each group corresponds to all information of a terminal observed by a base station;

[0019] Step S24: The server sorts each group of data according to the time of receipt.

[0020] Furthermore, the step S3 includes the following steps:

[0021] Step S31: for each type of data within the time interval T, each group of data within the forward NT time period is regarded as a group. The smaller N is, the stronger the real-time performance is and the greater the jitter is. On the contrary, the larger N is, the weaker the real-time performance is and the smaller the jitter is.

[0022] Step S32: Each group calculates the distance between two RSSI values, sets a distance threshold, clusters the data that is smaller than the threshold, and excludes the data that is larger than the threshold;

[0023] Step S33: Recombining the clustered data of each group for fusion positioning.

[0024] Furthermore, the step S4 includes the following steps:

[0025] Step S41: Preliminary positioning using the pole method based on the base station location coordinates and the terminal working height information;

[0026] Step S42: Taking the preliminary positioning position as the center, the pitch angle and the azimuth angle are expanded to the surrounding area according to the direction finding accuracy of the direction finding algorithm to form a fuzzy positioning area. The real position is likely to fall within the fuzzy positioning area.

[0027] Step S43: designing the fuzzy positioning area weight according to the pitch angle and the RSSI value. The larger the pitch angle, the stronger the energy, and the larger the weight value. On the contrary, the smaller the pitch angle, the weaker the energy, and the smaller the weight value.

[0028] Step S44: The weights of the overlapping areas are superimposed to find the area with the largest weight, and the center of gravity position of the area is used as the fusion positioning estimation value of the terminal.

[0029] Furthermore, the step S5 includes the following steps:

[0030] Step S51: smoothing the fused positioning estimate value by Kalman filtering;

[0031] Step S52: design the access conditions for the terminal to enter the system working area in combination with the coverage of the positioning system, the base station observed elevation angle and the RSSI value. When the observed data meets the access conditions, it is considered that the terminal enters the system working range, and the starting state of the Kalman filter is set according to the latest fusion positioning estimate value;

[0032] Step S53: design the leaving condition of the terminal leaving the system working area in combination with the coverage of the positioning system, the pitch angle observed by the base station, the RSSI value and the receiving time stamp. When the observed data or the receiving time stamp meets the leaving condition, it is considered that the terminal leaves the system working range and the Kalman filter is stopped.

[0033] Step S54: Perform Kalman filtering on the fused positioning estimate within the system coverage area.

[0034] Due to the adoption of the above technical solution, the present invention has the following advantages and positive effects compared with the prior art:

[0035] The invention discloses an asynchronous fusion positioning method based on arrival angle and RSSI value, which can enable a server to obtain a stable and accurate terminal position estimation value and has the characteristics of asynchronous fusion and high positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0037] Figure 1 It is a flow chart of an asynchronous fusion positioning method based on arrival angle and RSSI value of the present invention;

[0038] Figure 2 It is a schematic diagram of a positioning system corresponding to an asynchronous fusion positioning method based on arrival angle and RSSI value of the present invention. DETAILED DESCRIPTION

[0039] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] This embodiment discloses an asynchronous fusion positioning method based on arrival angle and RSSI value. The process is as follows: Figure 1 As shown, the corresponding positioning system is as Figure 2 As shown, the specific steps include:

[0041] Step S1: The base station sends the terminal MAC address, arrival angle, RSSI value and base station MAC address extracted from the radio signal periodically broadcast by the terminal to the server;

[0042] Step S2: The server marks the received data with a receiving time, classifies the data according to the terminal MAC address, groups each type of data according to the base station MAC address, and sorts each group of data according to the receiving time;

[0043] Step S3: for each type of data within the time interval T, the data within each group of data time period NT is taken as a group, clustered according to the RSSI value and the abnormal data is excluded, and the clustered data of each group is recombined for fusion positioning;

[0044] Step S4: Preliminary positioning is performed using the pole method based on the base station location coordinates, the terminal working height and other information, and then expanded to form a fuzzy positioning area in all directions. The fuzzy positioning area weight is then designed based on the arrival angle and RSSI value. The overlapping area weights are superimposed, and the center of gravity of the area with the largest weight is used as the fusion positioning estimate of the terminal.

[0045] Step S5: Perform Kalman filtering on each type of fused positioning estimation value at time interval T to obtain a stable fusion result.

[0046] Furthermore, the step S1 includes the following steps:

[0047] Step S11: The radio signal periodically broadcast by the terminal includes a MAC address used to distinguish the terminal;

[0048] Step S12: The base station observes the radio signal broadcast by the terminal and extracts the arrival angle, RSSI value and MAC address;

[0049] Step S13: The base station actively pushes the extracted terminal information and the MAC address of the base station to the server.

[0050] Furthermore, the step S2 includes the following steps:

[0051] Step S21: the server receives multiple terminal observation data pushed by multiple base stations and marks the receiving time stamp;

[0052] Step S22: The server classifies the received data according to the terminal MAC address, and all data in each category corresponds to all information of a terminal;

[0053] Step S23: the server groups each type of data according to the base station MAC address, and all data in each group corresponds to all information of a terminal observed by a base station;

[0054] Step S24: The server sorts each group of data according to the time of receipt.

[0055] Furthermore, the step S3 includes the following steps:

[0056] Step S31: for each type of data within a time interval T (such as 0.1s), each group of data within a forward NT (such as 1s) time period is regarded as a group;

[0057] Step S32: Each group calculates the distance between two RSSI values, sets a distance threshold, clusters the data that is smaller than the threshold, and excludes the data that is larger than the threshold;

[0058] Step S33: Recombining the clustered data of each group for fusion positioning.

[0059] Furthermore, the step S4 includes the following steps:

[0060] Step S41: Preliminary positioning using the pole method based on the base station location coordinates, terminal working height and other information;

[0061] Step S42: Taking the preliminary positioning position as the center, the pitch angle and the azimuth angle are expanded to the surrounding area according to the direction finding accuracy of the direction finding algorithm to form a fuzzy positioning area. The real position is likely to fall within the fuzzy positioning area.

[0062] Step S43: designing the fuzzy positioning area weight according to the pitch angle and the RSSI value. The larger the pitch angle, the stronger the energy, and the larger the weight value. On the contrary, the smaller the pitch angle, the weaker the energy, and the smaller the weight value.

[0063] Step S44: The weights of the overlapping areas are superimposed to find the area with the largest weight, and the center of gravity position of the area is used as the fusion positioning estimation value of the terminal.

[0064] Furthermore, the step S5 includes the following steps:

[0065] Step S51: smoothing the fused positioning estimate value by Kalman filtering;

[0066] Step S52: design the access conditions for the terminal to enter the system working area in combination with the coverage of the positioning system, the base station observed elevation angle and the RSSI value. When the observed data meets the access conditions, it is considered that the terminal enters the system working range, and the starting state of the Kalman filter is set according to the latest fusion positioning estimate value;

[0067] Step S53: design the leaving condition of the terminal leaving the system working area in combination with the coverage of the positioning system, the pitch angle observed by the base station, the RSSI value and the receiving time stamp. When the observed data or the receiving time stamp meets the leaving condition, it is considered that the terminal leaves the system working range and the Kalman filter is stopped.

[0068] Step S54: Perform Kalman filtering on the fused positioning estimate within the system coverage area.

[0069] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An asynchronous fusion positioning method based on arrival angle and RSSI value, characterized in that: The following steps are involved: Step S1: The base station sends the terminal MAC address, arrival angle, RSSI value and base station MAC address extracted from the radio signal periodically broadcast by the terminal to the server; Step S2: The server marks the received data with a receiving time, classifies the data according to the terminal MAC address, groups each type of data according to the base station MAC address, and sorts each group of data according to the receiving time; Step S3: for each type of data within the time interval T, the data within each group of data time period NT is taken as a group, clustered according to the RSSI value and the abnormal data is excluded, and the clustered data of each group is recombined for fusion positioning; Step S4: Preliminary positioning is performed using the pole method based on the base station location coordinates and the terminal working height information, and then expanded to form a fuzzy positioning area in all directions. The fuzzy positioning area weight is then designed based on the arrival angle and RSSI value. The overlapping area weights are superimposed, and the center of gravity of the area with the largest weight is used as the fusion positioning estimate of the terminal. The step S4 includes the following steps: Step S41: Preliminary positioning using the pole method based on the base station location coordinates and the terminal working height information; Step S42: Taking the preliminary positioning position as the center, the pitch angle and the azimuth angle are expanded to the surrounding area according to the direction finding accuracy of the direction finding algorithm to form a fuzzy positioning area. The real position is likely to fall within the fuzzy positioning area. Step S43: designing the fuzzy positioning area weight according to the pitch angle and the RSSI value. The larger the pitch angle, the stronger the energy, and the larger the weight value. On the contrary, the smaller the pitch angle, the weaker the energy, and the smaller the weight value. Step S44: The weights of the overlapping areas are superimposed to find the area with the largest weight, and the center of gravity position of the area is used as the fusion positioning estimation value of the terminal; Step S5: Perform Kalman filtering on each type of fused positioning estimation value at time interval T to obtain a stable fusion result.

2. The asynchronous fusion positioning method based on arrival angle and RSSI value according to claim 1, characterized in that: The step S1 includes the following steps: Step S11: The radio signal periodically broadcast by the terminal includes a MAC address used to distinguish the terminal; Step S12: The base station observes the radio signal broadcast by the terminal and extracts the arrival angle, RSSI value and MAC address; Step S13: The base station actively pushes the extracted terminal information and the MAC address of the base station to the server.

3. The asynchronous fusion positioning method based on arrival angle and RSSI value according to claim 1, characterized in that: The step S2 includes the following steps: Step S21: the server receives multiple terminal observation data pushed by multiple base stations and marks the receiving time stamp; Step S22: The server classifies the received data according to the terminal MAC address, and all data in each category corresponds to all information of a terminal; Step S23: the server groups each type of data according to the base station MAC address, and all data in each group corresponds to all information of a terminal observed by a base station; Step S24: The server sorts each group of data according to the time of receipt.

4. The asynchronous fusion positioning method based on arrival angle and RSSI value according to claim 1, characterized in that: The step S3 includes the following steps: Step S31: for each type of data within the time interval T, each group of data within the forward NT time period is regarded as a group. The smaller N is, the stronger the real-time performance is and the greater the jitter is. On the contrary, the larger N is, the weaker the real-time performance is and the smaller the jitter is. Step S32: Each group calculates the distance between two RSSI values, sets a distance threshold, clusters the data that is smaller than the threshold, and excludes the data that is larger than the threshold; Step S33: Recombining the clustered data of each group for fusion positioning.

5. The asynchronous fusion positioning method based on arrival angle and RSSI value according to claim 1, characterized in that: The step S5 includes the following steps: Step S51: smoothing the fused positioning estimate value by Kalman filtering; Step S52: design the access conditions for the terminal to enter the system working area in combination with the positioning system coverage, the base station observation elevation angle and the RSSI value. When the observation data meets the access conditions, it is considered that the terminal enters the system working range, and the starting state of the Kalman filter is set according to the latest fusion positioning estimation value; Step S53: design the leaving condition of the terminal leaving the system working area in combination with the coverage of the positioning system, the pitch angle observed by the base station, the RSSI value and the receiving time stamp. When the observed data or the receiving time stamp meets the leaving condition, it is considered that the terminal leaves the system working range and the Kalman filter is stopped. Step S54: Perform Kalman filtering on the fused positioning estimate within the system coverage area.

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