Positioning method, device, equipment, storage medium and computer program product

Abstract

The present application relates to a positioning method, device, equipment, storage medium and computer program product, which are used in a target terminal. The method includes: First, receiving first uplink signal measurement data including AOA data and TDOA data sent by a first base station and second uplink signal measurement data sent by a second base station. Then, inputting the first uplink signal measurement data, the second uplink signal measurement data and the positioning data of the target terminal at the previous moment into a positioning state space model, and solving the positioning state space model based on a preset algorithm to obtain the positioning data of the target terminal at the current moment. By using this method, three-dimensional positioning data of the target terminal at the current moment can be obtained by establishing a state space model and solving it according to the uplink signal measurement data including AOA data and TDOA data of two base stations and the data of the terminal at the previous moment.

Description

Technical Field

[0001] The present application relates to the field of communication technologies, and in particular, to a positioning method, apparatus, device, storage medium, and computer program product. Background Art

[0002] With the development of communication technologies, wireless terminal devices are increasingly widely used. In order to provide more convenient services to users, it is often necessary to locate the position of the terminal. Currently, most wireless base stations are equipped with one-dimensional linear arrays, which can measure the one-dimensional angle of arrival (AOA) information of the terminal's uplink signal. If high-precision synchronization of clocks among multiple wireless base stations can be ensured, accurate measurement of the time difference of arrival (TDOA) information of the terminal's uplink signal can be achieved simultaneously.

[0003] However, in current positioning algorithms, the azimuth angle observation model (AAOM) is usually used to process the one-dimensional AOA information measured by wireless base stations. This observation model only includes the two-dimensional coordinate information of the terminal and ignores the height difference information between the terminal and the base station. Therefore, 3D positioning of the terminal cannot be achieved. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a positioning method, apparatus, device, storage medium, and computer program product that can achieve 3D positioning of the terminal.

[0005] In a first aspect, the present application provides a positioning method for a target terminal. The method includes: receiving first uplink signal measurement data sent by a first base station and second uplink signal measurement data sent by a second base station, where both the first uplink signal measurement data and the second uplink signal measurement data include AOA data and TDOA data; inputting the first uplink signal measurement data, the second uplink signal measurement data, and the positioning data of the target terminal at the previous moment into a positioning state space model, and solving the positioning state space model based on a preset algorithm to obtain the positioning data of the target terminal at the current moment; where the positioning state space model includes a positioning observation model and a positioning state model, the positioning observation model includes an incident angle observation model and a three-dimensional TDOA observation model, the incident angle observation model is used to characterize the relationship between the AOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data of the target terminal, the second antenna data of the first base station, and the third antenna data of the second base station, and the three-dimensional TDOA observation model is used to characterize the relationship between the TDOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data, the second antenna data, and the third antenna data, and the positioning state model is used to characterize the relationship between the positioning data of the target terminal at the current moment and the positioning data of the target terminal at the previous moment.

[0006] In one embodiment, the positioning state model is specifically used to characterize the relationship between the positioning data of the target terminal at the current moment, the positioning data of the target terminal at the previous moment, the state transition matrix at the previous moment, the noise input matrix at the previous moment, and the state noise vector at the previous moment.

[0007] In one embodiment, the state transition matrix at the previous moment and the noise input matrix at the previous moment are obtained according to the tracking sampling interval.

[0008] In one embodiment, the first antenna data includes the antenna position data of the target terminal, the second antenna data includes the antenna position data and antenna attitude data of the first base station, and the third antenna data includes the antenna position data and antenna attitude data of the second base station.

[0009] In one embodiment, the antenna position data of the target terminal includes the position coordinates of the phase center of the antenna of the target terminal in the local rectangular coordinate system; the antenna position data of the first base station includes the position coordinates of the phase center of the antenna of the first base station in the local rectangular coordinate system; the antenna attitude data of the first base station includes the attitude angle of the antenna of the first base station in the local rectangular coordinate system; the antenna position data of the second base station includes the position coordinates of the phase center of the antenna of the second base station in the local rectangular coordinate system; the antenna attitude data of the second base station includes the attitude angle of the antenna of the second base station in the local rectangular coordinate system.

[0010] In one embodiment, the first base station and the second base station are deployed in a first manner or a second manner; wherein, the first manner includes deploying the first base station and the second base station on the same side of a rectangular positioning area, and ensuring a height difference between the first base station and the second base station; the second manner includes deploying the first base station and the second base station at two vertex positions of a matrix positioning area.

[0011] In one embodiment, based on a preset algorithm, the positioning state space model is solved to obtain the positioning data of the target terminal at the current moment, including: determining the target constraint conditions according to the deployment manners of the first base station and the second base station; determining the positioning data based on the preset algorithm, the target constraint conditions, the positioning observation model, and the positioning state model.

[0012] In one embodiment, determining the target constraint conditions according to the deployment manners of the first base station and the second base station includes: if the deployment manner of the first base station and the second base station is the first manner, obtaining the first constraint conditions among the first antenna data, the second antenna data, and the third antenna data, and using the first constraint conditions as the target constraint conditions.

[0013] In one embodiment, determining the target constraint conditions according to the deployment manners of the first base station and the second base station includes: if the deployment manner of the first base station and the second base station is the second manner, obtaining the first constraint conditions among the first antenna data, the second antenna data, and the third antenna data, and obtaining the second constraint conditions among the antenna height of the target terminal, the antenna height of the first base station, and the antenna height of the second base station, and using the first constraint conditions and the second constraint conditions as the target constraint conditions.

[0014] In one embodiment, the preset algorithm is a particle filter algorithm.

[0015] In a second aspect, the present application also provides a positioning device. The device includes:

[0016] A receiving module, configured to receive the first uplink signal measurement data sent by the first base station and the second uplink signal measurement data sent by the second base station, wherein both the first uplink signal measurement data and the second uplink signal measurement data include AOA data and TDOA data;

[0017] A calculation module, configured to input the first uplink signal measurement data, the second uplink signal measurement data, and the positioning data of the target terminal at the previous moment into a positioning state space model, and solve the positioning state space model based on a preset algorithm to obtain the positioning data of the target terminal at the current moment; wherein, the positioning state space model includes a positioning observation model and a positioning state model, the positioning observation model includes an incident angle observation model and a three-dimensional TDOA observation model, the incident angle observation model is used to characterize the relationship between the AOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data of the target terminal, the second antenna data of the first base station, and the third antenna data of the second base station, and the three-dimensional TDOA observation model is used to characterize the relationship between the TDOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data, the second antenna data, and the third antenna data, and the positioning state model is used to characterize the relationship between the positioning data of the target terminal at the current moment and the positioning data of the target terminal at the previous moment.

[0018] In one embodiment, the positioning state model is specifically configured to characterize the relationship between the positioning data of the target terminal at the current moment, the positioning data of the target terminal at the previous moment, the state transition matrix at the previous moment, the noise input matrix at the previous moment, and the state noise vector at the previous moment.

[0019] In one embodiment, the state transition matrix at the previous moment and the noise input matrix at the previous moment are obtained according to the tracking sampling interval.

[0020] In one embodiment, the first antenna data includes the antenna position data of the target terminal, the second antenna data includes the antenna position data and the antenna attitude data of the first base station, and the third antenna data includes the antenna position data and the antenna attitude data of the second base station.

[0021] In one embodiment, the antenna position data of the target terminal includes the position coordinates of the phase center of the antenna of the target terminal in the local rectangular coordinate system; the antenna position data of the first base station includes the position coordinates of the phase center of the antenna of the first base station in the local rectangular coordinate system; the antenna attitude data of the first base station includes the attitude angle of the antenna of the first base station in the local rectangular coordinate system; the antenna position data of the second base station includes the position coordinates of the phase center of the antenna of the second base station in the local rectangular coordinate system; the antenna attitude data of the second base station includes the attitude angle of the antenna of the second base station in the local rectangular coordinate system.

[0022] In one embodiment, the first base station and the second base station are deployed in a first manner or a second manner; wherein, the first manner includes deploying the first base station and the second base station on the same side of a rectangular positioning area, and ensuring a height difference between the first base station and the second base station; the second manner includes deploying the first base station and the second base station at two vertex positions of a matrix positioning area.

[0023] In one embodiment, the calculation module is specifically configured to determine a target constraint condition according to the deployment manner of the first base station and the second base station; and determine positioning data based on a preset algorithm, the target constraint condition, a positioning observation model, and a positioning state model.

[0024] In one embodiment, the calculation module is specifically configured to, if the deployment manner of the first base station and the second base station is the first manner, obtain a first constraint condition among first antenna data, second antenna data, and third antenna data, and use the first constraint condition as the target constraint condition.

[0025] In one embodiment, the calculation module is specifically configured to, if the deployment manner of the first base station and the second base station is the second manner, obtain a first constraint condition among first antenna data, second antenna data, and third antenna data, and obtain a second constraint condition among the antenna height of the target terminal, the antenna height of the first base station, and the antenna height of the second base station, and use the first constraint condition and the second constraint condition as the target constraint conditions.

[0026] In one embodiment, the preset algorithm is a particle filter algorithm.

[0027] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the method according to any one of the first aspects are implemented.

[0028] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the steps of the method according to any one of the first aspects are implemented.

[0029] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of the first aspects are implemented.

[0030] The above positioning method, device, equipment, storage medium and computer program product are used in a target terminal. First, the first uplink signal measurement data including AOA data and TDOA data sent by a first base station and the second uplink signal measurement data sent by a second base station are received. Then, the first uplink signal measurement data, the second uplink signal measurement data, and the positioning data of the target terminal at the previous moment are input into a positioning state space model, and the positioning state space model is solved based on a preset algorithm to obtain the positioning data of the target terminal at the current moment. Among them, the positioning state space model includes a positioning observation model and a positioning state model. The positioning observation model includes an incident angle observation model and a three-dimensional TDOA observation model. The incident angle observation model is used to characterize the relationship between the AOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data of the target terminal, the second antenna data of the first base station, and the third antenna data of the second base station. The three-dimensional TDOA observation model is used to characterize the relationship between the TDOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data, the second antenna data, and the third antenna data. The positioning state model is used to characterize the relationship between the positioning data of the target terminal at the current moment and the positioning data of the target terminal at the previous moment. This application obtains the current three-dimensional positioning data of the target terminal by establishing a state space model and solving it based on the uplink signal measurement data including AOA data and TDOA data of two base stations and the data of the terminal at the previous moment. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic flowchart of the positioning method in one embodiment;

[0032] Figure 2 It is a schematic flowchart of the positioning method in another embodiment;

[0033] Figure 3 It is a schematic diagram of the co - side deployment of the first base station and the second base station in one embodiment;

[0034] Figure 4 It is a schematic diagram of the vertex - angle deployment of the first base station and the second base station in another embodiment;

[0035] Figure 5 It is a flowchart of the positioning method based on particle filter in the co - side deployment in another embodiment;

[0036] Figure 6 It is a flowchart of the positioning method based on particle filter in the vertex - angle deployment in another embodiment;

[0037] Figure 7 It is a schematic diagram of the simulation result in the co - side deployment in another embodiment;

[0038] Figure 8Schematic diagram of simulation results in the case of vertical angle deployment in another embodiment;

[0039] Figure 9 Schematic flow chart of the positioning method in another embodiment;

[0040] Figure 10 Structural block diagram of the positioning device in one embodiment;

[0041] Figure 11 Internal structure diagram of a computer device in one embodiment. Detailed implementation manners

[0042] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0043] In one embodiment, as Figure 1 shown, there is provided a schematic flow chart of a positioning method. This embodiment is applied to a terminal, where the terminal can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. In the embodiments of the present application, for the target terminal, the method includes the following steps:

[0044] Step 101: Receive the first uplink signal measurement data sent by the first base station and the second uplink signal measurement data sent by the second base station.

[0045] Among them, both the first uplink signal measurement data and the second uplink signal measurement data include AOA data and TDOA data. The target terminal is the terminal to be positioned. The first uplink signal measurement data is the data sent by the first base station to the target terminal, and the second uplink signal measurement data is the data sent by the second base station to the target terminal.

[0046] Step 102: Input the first uplink signal measurement data, the second uplink signal measurement data, and the positioning data of the target terminal at the previous moment into the positioning state space model, and solve the positioning state space model based on a preset algorithm to obtain the positioning data of the target terminal at the current moment.

[0047] Among them, the positioning state space model includes a positioning observation model and a positioning state model. The positioning observation model includes an incident angle observation model and a three-dimensional TDOA observation model. The incident angle observation model is used to characterize the relationship between the AOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data of the target terminal, the second antenna data of the first base station, and the third antenna data of the second base station. The three-dimensional TDOA observation model is used to characterize the relationship between the TDOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data, the second antenna data, and the third antenna data. The positioning state model is used to characterize the relationship between the positioning data of the target terminal at the current moment and the positioning data of the target terminal at the previous moment.

[0048] In the above embodiment, first, receive the first uplink signal measurement data including AOA data and TDOA data sent by the first base station and the second uplink signal measurement data sent by the second base station. Then, input the first uplink signal measurement data, the second uplink signal measurement data, and the positioning data of the target terminal at the previous moment into the positioning state space model, and solve the positioning state space model based on a preset algorithm to obtain the positioning data of the target terminal at the current moment. Among them, the positioning state space model includes a positioning observation model and a positioning state model. The positioning observation model includes an incident angle observation model and a three-dimensional TDOA observation model. The incident angle observation model is used to characterize the relationship between the AOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data of the target terminal, the second antenna data of the first base station, and the third antenna data of the second base station. The three-dimensional TDOA observation model is used to characterize the relationship between the TDOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data, the second antenna data, and the third antenna data. The positioning state model is used to characterize the relationship between the positioning data of the target terminal at the current moment and the positioning data of the target terminal at the previous moment. According to the uplink signal measurement data including AOA data and TDOA data of two base stations, and the data of the terminal at the previous moment, the present application obtains the current three-dimensional positioning data of the target terminal by establishing and solving a state space model.

[0049] In one embodiment, the positioning state model is specifically used to characterize the relationship between the positioning data of the target terminal at the current moment, the positioning data of the target terminal at the previous moment, the state transition matrix at the previous moment, the noise input matrix at the previous moment, and the state noise vector at the previous moment.

[0050] The positioning state model proposed in the present application is:

[0051] x k =F k-1 x k-1 +G k-1 wk-1 (Formula 1)

[0052] Wherein, is the positioning data of the target terminal at the current moment, x k-1 is the positioning data of the target terminal at the previous moment, and represent the position coordinates of the phase center of the target terminal's antenna in the local rectangular coordinate system at time k, and respectively represent the velocity components of the phase center of the target terminal's antenna on the x-axis, y-axis and z-axis of the local rectangular coordinate system at time k, F k-1 is the state transition matrix at time k-1, G k-1 is the noise input matrix at time k-1, T is the tracking sampling interval, w k-1 is the state noise vector at time k-1.

[0053] Optionally, the state transition matrix at the previous moment and the noise input matrix at the previous moment are obtained according to the tracking sampling interval. The state transition matrix at the previous moment is:

[0054]

[0055] The noise input matrix at the previous moment is:

[0056]

[0057] In one embodiment, the first antenna data includes the antenna position data of the target terminal, the second antenna data includes the antenna position data and antenna attitude data of the first base station, and the third antenna data includes the antenna position data and antenna attitude data of the second base station.

[0058] Wherein, the antenna position data of the target terminal includes the position coordinates of the phase center of the target terminal's antenna in the local rectangular coordinate system; the antenna position data of the first base station includes the position coordinates of the phase center of the first base station's antenna in the local rectangular coordinate system; the antenna attitude data of the first base station includes the attitude angles of the first base station's antenna in the local rectangular coordinate system; the antenna position data of the second base station includes the position coordinates of the phase center of the second base station's antenna in the local rectangular coordinate system; the antenna attitude data of the second base station includes the attitude angles of the second base station's antenna in the local rectangular coordinate system.

[0059] Optionally, the attitude angles may be azimuth angle, pitch angle and roll angle. The first base station is the first radio base station, and the second base station is the second radio base station.

[0060] The positioning state space model of the present application further includes a positioning observation model, as shown in the following formula:

[0061] ξk = ψ(x k ) + υ k (Formula 2)

[0062] Where, ξ k represents the AOA and TDOA observation vectors of the first and second radio base stations at time k.

[0063]

[0064] represents the incident angle of the target terminal antenna phase center in the antenna coordinate system of the i-th radio base station at time k, that is, the AOA information of the target terminal measured by the i-th radio base station at time k. ρ T,k represents the TDOA information between the target terminal antenna phase center and the antennas of the second and first radio base stations at time k.

[0065] ψ(x k ) = [h1(x k ) h2(x k ) g(x k )] T (Formula 4)

[0066] Where

[0067]

[0068] α i = cosψ i cosγ i - sinψ i sinθ i sinγ i

[0069] β i = sinψ i cosγ i + cosψ i sinθ i sinγ i

[0070] κ i = - cosθ i sinγ i

[0071] υ k = [v 1,k v 2,k τ k ) T

[0072] From Formula 2, Formula 3, Formula 4 and the above parameters, we can get:

[0073]

[0074] ρ T,k = g(x k ) + τ k (Equation 6)

[0075] Among them, Equation 5 is the incident angle observation model, and Equation 6 is the three-dimensional TDOA observation model.

[0076] Among them, ψ i , θ i and γ i are the attitude angles of the i-th wireless base station antenna in the local rectangular coordinate system, which are the azimuth angle, elevation angle, and roll angle respectively, that is, the antenna attitude data. and are the position coordinates of the phase center of the i-th wireless base station antenna in the local rectangular coordinate system, that is, the antenna position data, arccos(g) is the inverse cosine function, υ k is the total observation noise vector of the first wireless base station and the second wireless base station at time k, v i,k is the AOA observation noise of the i-th wireless base station at time k, τ k is the TDOA observation noise at time k.

[0077] In the embodiment of the present application, the steps of solving the positioning state space model based on a preset algorithm to obtain the positioning data of the target terminal at the current moment are as Figure 2 shown, including:

[0078] Step 201, determine the target constraint conditions according to the deployment method of the first base station and the second base station.

[0079] The first base station and the second base station are deployed in the first manner or in the second manner; among them, the first manner includes deploying the first base station and the second base station on the same side of the rectangular positioning area, and ensuring that there is a height difference between the first base station and the second base station; the second manner includes deploying the first base station and the second base station at two vertex positions of the matrix positioning area.

[0080] The first manner is the same-side deployment manner. As Figure 3 shown, the first base station and the second base station are located on the same side of the rectangular positioning area. In order to ensure the feasibility of 3D positioning using the uplink AOA and TDOA information of the two base stations, on the one hand, it is necessary to ensure that there is a height difference between the deployment positions of the two wireless base stations, and on the other hand, it is necessary to satisfy the following first constraint condition for the 3D tracking state of the uplink AOA and TDOA fusion of the two base stations as shown in the following formula:

[0081]

[0082] Therefore, if the deployment modes of the first base station and the second base station are the first mode, obtain the first constraint condition among the first antenna data, the second antenna data, and the third antenna data, and use the first constraint condition as the target constraint condition.

[0083] If the deployment modes of the first base station and the second base station are the second mode, obtain the first constraint condition among the first antenna data, the second antenna data, and the third antenna data, and obtain the second constraint condition among the antenna height of the target terminal, the antenna height of the first base station, and the antenna height of the second base station, and use the first constraint condition and the second constraint condition as the target constraint conditions.

[0084] The second mode is the vertical angle deployment mode. As Figure 4 shown, the second constraint condition is shown in the following formula:

[0085]

[0086] Therefore, when the deployment mode is the second mode, the target constraint condition is as described in the following formula:

[0087]

[0088] where min(·,·) is to take the minimum value.

[0089] Step 202: Determine the positioning data based on a preset algorithm, the target constraint condition, and the positioning observation model and the positioning state model.

[0090] Among them, the preset algorithm can be a particle filter algorithm. The preset algorithm can also be other algorithms such as a Gaussian filter algorithm, an auxiliary particle filter algorithm, or a Kalman filter algorithm. This application takes the constraint-based particle filter algorithm as an example for illustration. First, initialize the particle filter, that is, extract Λ particles from the prior probability density function p(x0) The initial particle weights are Subsequently, perform importance sampling and obtain Λ particles using formula 1 That is

[0091]

[0092] Then, update the particle weights according to the following formula

[0093]

[0094] If the first base station and the second base station are in the same-side deployment scheme, then:

[0095]

[0096] If the first base station and the second base station are in the vertical angle deployment scheme, then:

[0097]

[0098]

[0099]

[0100] where is the likelihood function of the particle, ξ has the same meaning as in the above formula, which are the AOA and TDOA observation vectors and the AOA and TDOA observation models of the first and second radio base stations at time k, respectively, and R k and is the covariance matrix of the AOA and TDOA observation noise vectors υ k of the first and second radio base stations, k and is the normalized weight, and then resampling is performed to obtain a new set of particles The corresponding particle weights are

[0101] Finally, the state estimate value of the terminal at time k can be expressed as

[0102]

[0103] The specific process of the above method for fusing AOA and TDOA in the uplink of the first and second radio base stations based on constrained particle filtering is as shown in Figure 5 when deployed on the same side, and as shown in Figure 6 when deployed in an apex angle configuration.

[0104] To verify the effectiveness of the positioning method of this application, a simulation experiment is carried out. For the first deployment scheme, i.e., the same-side deployment scheme, the simulation sets the position coordinates of the first radio base station as and with the attitude angles ψ1 = 0, θ1 = 0, and γ1 = 0, and the position coordinates of the second radio base station as and with the attitude angles ψ2 = 0, θ2 = 0, and γ2 = 0. The standard deviation of the AOA observation error of both radio base stations is 1 degree, the standard deviation of the TDOA observation error is 0.1 meter, the number of particles of the particle filter is set to 500, and a total of 100 Monte Carlo simulations are carried out. The initial state of the terminal is set as

[0105]

[0106] Please refer to Figure 7, which shows the terminal position estimation performance of the proposed dual - base - station uplink AOA and TDOA fusion 3D positioning method based on constrained particle filtering. According to Figure 7 it can be seen that the proposed dual - base - station uplink AOA and TDOA fusion 3D positioning method based on constrained particle filtering can achieve high - precision 3D positioning of the terminal by only using two wireless base stations equipped with one - dimensional linear arrays.

[0107] For the second deployment scheme, i.e., the vertical - angle deployment scheme, the simulation sets the position coordinates of the first wireless base station as and with the attitude angles ψ1 = 0, θ1 = 0, and γ1 = 0, and the position coordinates of the second wireless base station as and with the attitude angles ψ2 = 0, θ2 = 0, and γ2 = 180°. The standard deviation of the AOA observation error of both wireless base stations is 1 degree, the standard deviation of the TDOA observation error is 0.1 meter, the number of particles of the particle filter is set to 500, and a total of 100 Monte Carlo simulations are carried out. The initial state of the terminal is set as

[0108]

[0109] Please refer to Figure 8 , Figure 8 , which shows the target terminal position estimation performance of the proposed dual - base - station uplink AOA and TDOA fusion 3D positioning method based on constrained particle filtering. According to Figure 8 it can be seen that the proposed dual - base - station uplink AOA and TDOA fusion 3D positioning method based on constrained particle filtering can achieve high - precision 3D positioning of the terminal by only using two wireless base stations equipped with one - dimensional linear arrays.

[0110] In the embodiment of the present application, please refer to Figure 9 , which shows the flowchart of a positioning method provided by the embodiment of the present application. The positioning method includes the following steps:

[0111] Step 901: Receive the first uplink signal measurement data sent by the first base station and the second uplink signal measurement data sent by the second base station.

[0112] Step 902: Input the first uplink signal measurement data, the second uplink signal measurement data, and the positioning data of the target terminal at the previous moment into the positioning state - space model.

[0113] Step 903: Determine the target constraint conditions according to the deployment methods of the first base station and the second base station.

[0114] Step 904: Determine the positioning data based on the preset algorithm, the target constraint conditions, and the positioning observation model and the positioning state model.

[0115] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown in sequence according to the indications of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0116] Based on the same inventive concept, an embodiment of the present application further provides a positioning device for implementing the positioning method involved above. The solution for solving the problem provided by this device is similar to the solution recorded in the above method. Therefore, the specific limitations in one or more embodiments of the positioning device provided below can refer to the limitations on the positioning method in the above text, and will not be repeated here.

[0117] In one embodiment, as Figure 10 shown, a positioning device 1000 is provided, including: a receiving module 1001 and a calculating module 1002, where:

[0118] The receiving module 1001 is configured to receive first uplink signal measurement data sent by a first base station and second uplink signal measurement data sent by a second base station. The first uplink signal measurement data and the second uplink signal measurement data both include AOA data and TDOA data;

[0119] The calculating module 1002 is configured to input the first uplink signal measurement data, the second uplink signal measurement data, and the positioning data of the target terminal at the previous moment into a positioning state space model, and solve the positioning state space model based on a preset algorithm to obtain the positioning data of the target terminal at the current moment; where the positioning state space model includes a positioning observation model and a positioning state model. The positioning observation model includes an incident angle observation model and a three-dimensional TDOA observation model. The incident angle observation model is used to characterize the relationship between the AOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data of the target terminal, the second antenna data of the first base station, and the third antenna data of the second base station. The three-dimensional TDOA observation model is used to characterize the relationship between the TDOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data, the second antenna data, and the third antenna data. The positioning state model is used to characterize the relationship between the positioning data of the target terminal at the current moment and the positioning data of the target terminal at the previous moment.

[0120] In one embodiment of the present application, the positioning state model is specifically used to characterize the relationship between the positioning data of the target terminal at the current moment, the positioning data of the target terminal at the previous moment, the state transition matrix at the previous moment, the noise input matrix at the previous moment, and the state noise vector at the previous moment.

[0121] In one embodiment of the present application, the state transition matrix at the previous moment and the noise input matrix at the previous moment are obtained according to the tracking sampling interval.

[0122] In one embodiment of the present application, the first antenna data includes the antenna position data of the target terminal, the second antenna data includes the antenna position data and the antenna attitude data of the first base station, and the third antenna data includes the antenna position data and the antenna attitude data of the second base station.

[0123] In one embodiment of the present application, the antenna position data of the target terminal includes the position coordinates of the phase center of the antenna of the target terminal in the local rectangular coordinate system; the antenna position data of the first base station includes the position coordinates of the phase center of the antenna of the first base station in the local rectangular coordinate system; the antenna attitude data of the first base station includes the attitude angle of the antenna of the first base station in the local rectangular coordinate system; the antenna position data of the second base station includes the position coordinates of the phase center of the antenna of the second base station in the local rectangular coordinate system; the antenna attitude data of the second base station includes the attitude angle of the antenna of the second base station in the local rectangular coordinate system.

[0124] In one embodiment of the present application, the first base station and the second base station are deployed in a first manner or in a second manner; wherein, the first manner includes deploying the first base station and the second base station on the same side of the rectangular positioning area, and ensuring that there is a height difference between the first base station and the second base station; the second manner includes deploying the first base station and the second base station at two vertex positions of the matrix positioning area.

[0125] In one embodiment of the present application, the calculation module 1002 is specifically configured to determine the target constraint condition according to the deployment manner of the first base station and the second base station; and determine the positioning data based on a preset algorithm, the target constraint condition, the positioning observation model, and the positioning state model.

[0126] In one embodiment of the present application, the calculation module 1002 is specifically configured to, if the deployment manner of the first base station and the second base station is the first manner, obtain the first constraint condition between the first antenna data, the second antenna data, and the third antenna data, and use the first constraint condition as the target constraint condition.

[0127] In an embodiment of the present application, the calculation module 1002 is specifically configured to, if the deployment manners of the first base station and the second base station are the second manner, obtain a first constraint condition among the first antenna data, the second antenna data, and the third antenna data, and obtain a second constraint condition among the antenna height of the target terminal, the antenna height of the first base station, and the antenna height of the second base station, and use the first constraint condition and the second constraint condition as the target constraint condition.

[0128] In an embodiment of the present application, the preset algorithm is a particle filter algorithm.

[0129] Each module in the above positioning device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor in the computer device in the form of hardware or be independent of the processor, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0130] In an embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 11 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals in a wired or wireless manner. The wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, a positioning method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or can be a button, a trackball, or a touchpad provided on the housing of the computer device, or can also be an external keyboard, a touchpad, or a mouse, etc.

[0131] Those skilled in the art can understand that Figure 11The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0132] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0133] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0134] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0135] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions.

[0136] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0137] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0138] The above-described embodiments only represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the patent of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A positioning method, characterized in that, For a target terminal, the positioning method includes: Receiving first uplink signal measurement data sent by a first base station and second uplink signal measurement data sent by a second base station, where both the first uplink signal measurement data and the second uplink signal measurement data include one-dimensional angle of arrival (AOA) data and time difference of arrival (TDOA) data; Inputting the first uplink signal measurement data, the second uplink signal measurement data, and the positioning data of the target terminal at the previous moment into a positioning state space model, and solving the positioning state space model based on a preset algorithm to obtain the positioning data of the target terminal at the current moment; Wherein, the positioning state space model includes a positioning observation model and a positioning state model. The positioning observation model includes an incident angle observation model and a three-dimensional TDOA observation model. The incident angle observation model is used to characterize the relationship between the AOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data of the target terminal, the second antenna data of the first base station, and the third antenna data of the second base station. The three-dimensional TDOA observation model is used to characterize the relationship between the TDOA data in the first uplink signal measurement data and the second uplink signal measurement data and the first antenna data, the second antenna data, and the third antenna data. The positioning state model is used to characterize the relationship between the positioning data of the target terminal at the current moment and the positioning data of the target terminal at the previous moment.

2. The method according to claim 1, wherein The positioning state model is specifically used to characterize the relationship between the positioning data of the target terminal at the current moment and the positioning data of the target terminal at the previous moment, the state transition matrix at the previous moment, the noise input matrix at the previous moment, and the state noise vector at the previous moment.

3. The method according to claim 1, characterized in that, The first antenna data includes the antenna position data of the target terminal, the second antenna data includes the antenna position data and antenna attitude data of the first base station, and the third antenna data includes the antenna position data and antenna attitude data of the second base station.

4. The method according to claim 3, wherein The antenna position data of the target terminal includes the position coordinates of the phase center of the antenna of the target terminal in the local rectangular coordinate system; The antenna position data of the first base station includes the position coordinates of the phase center of the antenna of the first base station in the local rectangular coordinate system; The antenna attitude data of the first base station includes the attitude angles of the antenna of the first base station in the local rectangular coordinate system; The antenna position data of the second base station includes the position coordinates of the phase center of the antenna of the second base station in the local rectangular coordinate system; The antenna attitude data of the second base station includes the attitude angles of the antenna of the second base station in the local rectangular coordinate system.

5. The method according to any one of claims 1 to 4, characterized in that The first base station and the second base station are deployed in a first manner or in a second manner; Wherein, the first manner includes deploying the first base station and the second base station on the same side of a rectangular positioning area, and ensuring that there is a height difference between the first base station and the second base station; The second method includes deploying the first base station and the second base station at two vertex positions of the matrix positioning area.

6. The method according to claim 5, wherein Solving the positioning state space model based on the preset algorithm to obtain the positioning data of the target terminal at the current moment, including: Determining target constraint conditions according to the deployment methods of the first base station and the second base station; Determining the positioning data based on the preset algorithm, the target constraint conditions, the positioning observation model, and the positioning state model.

7. The method according to claim 6, characterized in that, The determining target constraint conditions according to the deployment methods of the first base station and the second base station includes: If the deployment methods of the first base station and the second base station are the first method, obtaining the first constraint condition between the first antenna data, the second antenna data, and the third antenna data, and using the first constraint condition as the target constraint condition.

8. The method according to claim 6, wherein The determining target constraint conditions according to the deployment methods of the first base station and the second base station includes: If the deployment methods of the first base station and the second base station are the second method, obtaining the first constraint condition between the first antenna data, the second antenna data, and the third antenna data, and obtaining the second constraint condition between the antenna height of the target terminal, the antenna height of the first base station, and the antenna height of the second base station, and using the first constraint condition and the second constraint condition as the target constraint conditions.

9. The method according to claim 6, wherein The preset algorithm is a particle filter algorithm.

10. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 9.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 9.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 9.

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