A positioning method based on the particle distribution characteristics around TDoA hyperbola

Abstract

The present invention relates to the field of communication technology, specifically a positioning method based on the particle distribution characteristics around the TDoA hyperbola, including the following contents: obtaining the distance difference between the positioning tag and each base station according to the TDoA ranging, performing data cleaning on the distance difference, and calculating and generating several hyperbolas according to the cleaned distance difference; initializing particles in the signal coverage area of ​​the base station, assigning corresponding weights to the particles under different hyperbolas according to the distances from the particles to each hyperbola; superimposing and normalizing the weights of the particles to generate the global weights of each particle; screening the particles according to the global weights and a preset threshold, and calculating and generating the positioning coordinates of the positioning tag according to the global weights of the screened particles. The adoption of this scheme can solve the technical problems of too many initial conditions and complex algorithms required in the positioning process based on the TDoA technology in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a positioning method based on the distribution characteristics of particles around a TDoA hyperbola. Background Art

[0002] The Time Difference of Arrival (TDoA) method is one of the commonly used positioning technologies. Its principle is to use the time difference of receiving signals from multiple base stations to determine the location of the tag. The positioning tag sends a wireless ranging signal to the outside, and all base stations within the wireless coverage range of the tag will receive the wireless signal. If there are two base stations with known coordinates that receive the signal, and the distance between the tag and the two base stations is different, then the time when the two base stations receive the signal is different. According to the geometric relationship, the distance difference between the two known points is a constant, and the time difference between the tag sending the signal to the two base stations is a constant. The position of the tag is on a hyperbola with these two points as the focus. Therefore, the position coordinates of the tag can be obtained by solving the set of equations.

[0003] However, the above method has the following problems: according to the solution of the equation group, it can be seen that 2 unknown quantities require more than 3 linear uncorrelated variances, that is, the coordinate points of at least 4 base stations need to be known; at the same time, the number of equations in the above-solved equation group is greater than the number of unknown quantities, which belongs to an overdetermined equation group, and the calculation process of an overdetermined equation group is complicated. Summary of the invention

[0004] The present invention aims to provide a positioning method based on the particle distribution characteristics around the TDoA hyperbola to solve the technical problems of too many initial conditions and complex algorithms required in the positioning process based on the TDoA technology in the prior art.

[0005] The present invention provides the following basic scheme:

[0006] A positioning method based on the particle distribution characteristics around the TDoA hyperbola includes the following contents:

[0007] The distance difference between the positioning tag and each base station is obtained according to TDoA ranging, and the distance difference is cleaned up, and several hyperbolas are generated according to the cleaned distance difference calculation;

[0008] Also included are the following:

[0009] Initialize particles in the signal coverage area of ​​the base station, and assign corresponding weights to particles under different hyperbolas according to the distances from the particles to each hyperbola;

[0010] The weights of the particles are superimposed and normalized to generate the global weight of each particle;

[0011] The particles are screened according to the global weight and the preset threshold, and the positioning coordinates of the positioning tag are calculated and generated according to the global weight of the screened particles.

[0012] Beneficial effects of the basic program:

[0013] This scheme obtains the distance difference between the positioning tag and each base station through TDoA ranging, thereby obtaining several hyperbolas; then, by initializing the particles, the weight of each particle under different hyperbolas is assigned according to the distance between the particle and the hyperbola, that is, the probability that the particle is the positioning coordinate of the positioning tag for the corresponding hyperbola, and this probability conforms to the Gaussian distribution as the distance between the particle and the hyperbola is close.

[0014] The weights of the particles under each hyperbola are superimposed and normalized to obtain the global weight of each particle. The particles are screened by the global weight and threshold, and the positioning coordinates of the positioning tag are obtained based on the screened particles. By adjusting the threshold, the screened particles are adjusted, thereby adjusting the positioning accuracy.

[0015] This solution uses nonlinear independent hyperbolic equations for positioning, and the minimum number of base station coordinate points required for positioning is 3, which reduces the required initial conditions. At the same time, this solution does not directly solve the overdetermined equations, simplifies the calculation process, reduces the complexity of the algorithm, and improves the positioning response speed.

[0016] Further, the particles are initialized in the signal coverage area of ​​the base station, including the following:

[0017] The positioning coordinates of the historical positioning tags are obtained, and the selected area within the signal coverage area is generated according to the preset demarcation conditions and the positioning coordinates of the historical positioning tags, and the particles are evenly dispersed in the selected area.

[0018] Beneficial effects: The selected area is generated according to the positioning coordinates and demarcation conditions of the historical positioning tags. For example, the positioning coordinates of the historical positioning tags are used as the origin, and a circular area with a specified distance as the radius is demarcated as the selected area. The particles are initialized by the positioning coordinates of the historical positioning tags, and there is no need to scatter the particles in the two-dimensional space of the entire signal coverage area, which reduces the algorithm complexity and improves the efficiency of particle initialization.

[0019] Further, the particles are initialized in the signal coverage area of ​​the base station, including the following:

[0020] Acquire the designated area within the signal coverage area and evenly spread the particles in the designated area.

[0021] Beneficial effect: The designated area is a manually designated area. When initializing particles based on the positioning coordinates of historical positioning tags, positioning deviations are also continuously accumulated. When the deviation is too large, it will affect the positioning accuracy. Therefore, by initializing particles in a manually designated area, the accumulated positioning deviations are eliminated and the positioning accuracy is improved.

[0022] Furthermore, the particle is assigned a weight corresponding to each hyperbola according to the distance from the particle to each hyperbola, including the following:

[0023] The weights of particles under different hyperbolas are calculated according to the following formula:

[0024]

[0025] In the formula, m is the number of particles, n is the number of hyperbolas, and D n is the distance from the particle to the nth hyperbola, p m (D n ) is the weight of the m-th particle under the n-th hyperbola, μ is the expectation of the variable D, and σ is the standard deviation of the variable D.

[0026] Beneficial effect: The weight is the probability that the coordinates of each particle are the positioning coordinates of the positioning tag. The probability conforms to the Gaussian distribution as the distance between the particle and the hyperbola is close. The particle is assigned the corresponding weight under each hyperbola according to the above formula.

[0027] Furthermore, the particle weights are superimposed and normalized to generate the global weight of the particle, including the following:

[0028] Add the weights of the particles under each hyperbola, and normalize the added weights according to the following formula to generate the global weight of each particle:

[0029]

[0030] In the formula, p m (D) is the global weight of the mth particle.

[0031] Beneficial effect: The global weight of the particles is calculated by this method, the sum of the weights of the particles is summed up by superposition, and the sum of the weights is uniformly processed through indifferent normalization, which facilitates the subsequent unified management of the data.

[0032] Furthermore, the particles are screened according to the global weight and the preset threshold, including the following:

[0033] Compare the global weight of each particle with the preset threshold, and filter out particles whose global weight is greater than the threshold.

[0034] Beneficial effect: Filter particles whose global weight is greater than the threshold. The larger the global weight, the greater the probability that the coordinates of the particle are the positioning coordinates of the positioning tag. By screening particles, the amount of subsequent calculations can be reduced while reducing the amount of interference and improving positioning accuracy.

[0035] Furthermore, the following are also included:

[0036] The weight expectation and weight variance are calculated according to the global weight of each particle, and the threshold is generated according to the weight expectation and weight variance.

[0037] Beneficial effect: The threshold is determined by the global weight, so as to adjust the size of the threshold and then determine the required positioning accuracy according to the actual application scenario.

[0038] Furthermore, the positioning coordinates of the positioning tags are generated based on the global weight calculation of the screened particles, including the following:

[0039] Generate a particle set based on the screened particles, obtain the coordinates and global weights of the particles in the particle set, and calculate the positioning coordinates of the positioning label according to the following formula:

[0040]

[0041] In the formula, x est ,y est is the positioning coordinate of the positioning label, P′(D) is the global weight of the particle in the particle set, and X and Y are the coordinates of the particle in the particle set.

[0042] Beneficial effect: The screened particles form a particle set, and a weighted average calculation is performed on the particle set to obtain the positioning coordinates of the positioning tag. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a flow chart of an embodiment of a positioning method based on the particle distribution characteristics around the TDoA hyperbola of the present invention;

[0044] Figure 2 The present invention is a flowchart of an embodiment of a positioning method based on the particle distribution characteristics around the TDoA hyperbola. DETAILED DESCRIPTION

[0045] The following is further described in detail through specific implementation methods:

[0046] Example

[0047] A positioning method based on the particle distribution characteristics around the TDoA hyperbola, as shown in the attached Figure 1 As shown, including the following:

[0048] S1: Obtain the distance difference between the positioning tag and each base station based on TDoA ranging, clean up the distance difference data, and calculate and generate several hyperbolas based on the cleaned distance difference; as shown in the attached figure Figure 2 As shown in the figure, Target is the positioning tag, points A, B, and C are base stations, and TDoA_AC and TDoA_BC are the corresponding hyperbolas.

[0049] S2: Initialize particles in the signal coverage area of ​​the base station, assign corresponding weights to particles under different hyperbolas according to the distances from the particles to each hyperbola; superimpose and normalize the weights of the particles to generate the global weights of each particle.

[0050] S3: Screen the particles according to the global weight and the preset threshold, and calculate and generate the positioning coordinates of the positioning tag according to the global weight of the screened particles.

[0051] The method also includes the following: calculating the weight expectation and weight variance according to the global weight of each particle, and generating a threshold according to the weight expectation and weight variance. Specifically, the threshold may be a manually set constant or a variable, for example, the threshold may be the weight expectation or the sum of the weight expectation and the weight variance. In this embodiment, the threshold is a manually set constant.

[0052] In step S1, data cleaning is performed on the distance differences, including eliminating distance differences with large errors. In other embodiments, the distance differences with large errors are corrected based on the mean values ​​calculated based on the distance differences.

[0053] In step S2, particles are initialized in the signal coverage area of ​​the base station, including the following: when positioning for the first time, a designated area within the signal coverage area is obtained, and particles are evenly distributed in the designated area. When positioning is not the first time, the positioning coordinates of the historical positioning tags are obtained, and a selected area within the signal coverage area is generated according to the preset demarcation conditions and the positioning coordinates of the historical positioning tags, and particles are evenly distributed in the selected area.

[0054] The designated area is the area where the positioning coordinates of the positioning tag in the artificially designated signal coverage area may be located. The demarcation condition is to use the positioning coordinates of the historical positioning tag as the center of the circle and the preset specified distance as the radius to demarcate the selected area. After initializing particles with the positioning coordinates of the historical positioning tag for multiple times, the designated area in the signal coverage area is obtained, and the particles are evenly dispersed in the designated area, thereby eliminating the accumulated positioning deviation and improving the positioning accuracy.

[0055] In step S2, the weights corresponding to the particles under different hyperbolas are assigned according to the distances from the particles to the hyperbolas, including the following contents: the weights corresponding to the particles under different hyperbolas are calculated according to the following formulas:

[0056]

[0057] In formula (1), m is the number of particles, n is the number of hyperbolas, and the value of n is greater than 3. n is the distance from the particle to the nth hyperbola, p m (D n ) is the weight of the m-th particle under the n-th hyperbola, μ is the expectation of the variable D, and σ is the standard deviation of the variable D.

[0058] In the specific calculation, the distance from the particle to the hyperbola in the two-dimensional plane obeys a Gaussian distribution with a mean of 0 and a variance of 1, that is, the value of is 0 and the value of is 1, so formula (1) is simplified to the following formula:

[0059]

[0060] Calculate the weight of each particle under different hyperbolas in turn.

[0061] In step S2, the weights of the particles are superimposed and normalized to generate the global weight of the particles, including the following: the weights of the particles under each hyperbola are added, and the added weights are normalized according to the following formula to generate the global weight of each particle,

[0062]

[0063] In formula (2), p m (D) is the global weight of the mth particle.

[0064] Calculate the global weight of each particle in turn.

[0065] In step S3, the particles are screened according to the global weight and the preset threshold, including the following: comparing the global weight of each particle with the preset threshold, and screening particles whose global weight is greater than the threshold. According to the actual application scenario, the threshold is adjusted to change the positioning accuracy to meet different requirements.

[0066] In step S3, the positioning coordinates of the positioning tag are calculated based on the global weights of the screened particles, including the following: generating a particle set based on the screened particles, obtaining the coordinates and global weights of the particles in the particle set, and calculating the positioning coordinates of the positioning tag according to the following formula:

[0067]

[0068] In formula (3), x est ,y est is the positioning coordinate of the positioning label, P′(D) is the global weight of the particle in the particle set, X, Y are the coordinates of the particle in the particle set, and X, Y and P′(D) are all row vectors.

[0069] The selected particles form a particle set, and the expectation is calculated by weighted average on the particle set to obtain the positioning coordinates of the positioning tag.

[0070] This solution uses nonlinear independent hyperbolic equations for positioning, and the minimum number of base station coordinate points required for positioning is 3, which reduces the required initial conditions. At the same time, this solution does not directly solve the overdetermined equations, which simplifies the calculation process, reduces the complexity of the algorithm, and improves the positioning response speed. This solution also initializes particles by selecting or specifying areas, without the need to scatter particles in the two-dimensional space of the entire signal coverage area, reducing the complexity of the algorithm and improving the efficiency of particle initialization.

[0071] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A positioning method based on the particle distribution characteristics around the TDoA hyperbola, comprising the following contents: The distance difference between the positioning tag and each base station is obtained according to TDoA ranging, and the distance difference is cleaned up, and several hyperbolas are generated according to the cleaned distance difference calculation; It is characterized in that Also included are the following: Initialize particles in the signal coverage area of ​​the base station, and assign corresponding weights to particles under different hyperbolas according to the distances from the particles to each hyperbola, including the following: The weights of particles under different hyperbolas are calculated according to the following formula: In the formula, m is the number of particles, n is the number of hyperbolas, and D n is the distance from the particle to the nth hyperbola, is the weight of the mth particle under the nth hyperbola, is the expectation of variable D, is the standard deviation of variable D; The weights of the particles are superimposed and normalized to generate the global weight of each particle; The particles are screened according to the global weight and the preset threshold, and the positioning coordinates of the positioning tag are calculated and generated according to the global weight of the screened particles.

2. A positioning method based on the particle distribution characteristics around the TDoA hyperbola according to claim 1, It is characterized in that Initialize particles in the signal coverage area of ​​the base station, including the following: The positioning coordinates of the historical positioning tags are obtained, and the selected area within the signal coverage area is generated according to the preset demarcation conditions and the positioning coordinates of the historical positioning tags, and the particles are evenly dispersed in the selected area.

3. A positioning method based on the particle distribution characteristics around the TDoA hyperbola according to claim 1, It is characterized in that Initialize particles in the base station’s signal coverage area, Includes the following: Acquire the designated area within the signal coverage area and evenly spread the particles in the designated area.

4. A positioning method based on the particle distribution characteristics around the TDoA hyperbola according to claim 1, It is characterized in that The particle weights are superimposed and normalized to generate the global weight of the particle, including the following: Add the weights of the particles under each hyperbola, and normalize the added weights according to the following formula to generate the global weight of each particle: In the formula, is the global weight of the mth particle.

5. A positioning method based on the particle distribution characteristics around the TDoA hyperbola according to claim 1, It is characterized in that Particles are screened based on global weights and preset thresholds, including the following: Compare the global weight of each particle with the preset threshold, and filter out particles whose global weight is greater than the threshold.

6. A positioning method based on the particle distribution characteristics around the TDoA hyperbola according to claim 1, Features: Also included are the following: The weight expectation and weight variance are calculated according to the global weight of each particle, and the threshold is generated according to the weight expectation and weight variance.

7. A positioning method based on the particle distribution characteristics around the TDoA hyperbola according to claim 1, It is characterized in that The positioning coordinates of the positioning label are generated based on the global weight calculation of the screened particles, including the following: Generate a particle set based on the screened particles, obtain the coordinates and global weights of the particles in the particle set, and calculate the positioning coordinates of the positioning label according to the following formula: In the formula, x est ,y est is the positioning coordinate of the positioning tag, is the global weight of the particle in the particle set, and X and Y are the coordinates of the particle in the particle set.

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