A method for improving the accuracy of position estimation in a primary TDoA network

Abstract

The application relates to the technical field of high-precision positioning, and discloses a method for improving the position estimation precision in a main TDoA network. The method broadcasts TDoA messages through a plurality of anchor points in an infrastructure network, and a mobile device receives and preliminarily estimates the position thereof. When the device is outside a polygon area formed by the anchor points or the received TDoA messages are less than 4, a TW-ToA ranging mechanism is triggered, more accurate distance information is obtained through bidirectional communication, and then, a fusion positioning algorithm is adopted to combine the TDoA and TW-ToA messages, a position of the device is accurately estimated by minimizing a target function of a weighted residual sum of squares. The method significantly improves the positioning precision and stability, and is especially suitable for complex environments.

Description

Technical Field

[0001] This invention relates to the field of high-precision positioning technology and discloses a method for improving the accuracy of position estimation in major TDoA networks. Background Technology

[0002] In high-precision positioning systems based on Time-DoA (TDoA), mobile devices typically calculate their position by receiving signals from multiple anchor points and utilizing the hyperbola intersection principle. However, when the mobile device is located at or outside the edge of a polygonal region formed by the anchor points, the positioning error increases significantly due to the geometric dilution effect. Particularly in boundary regions, the hyperbolas may be approximately parallel, amplifying even small time measurement errors and severely reducing positioning accuracy. Existing technologies primarily rely on single TDoA measurements, and insufficient available signals, especially when signals are blocked or the anchor point distribution is suboptimal, further degrade positioning performance. Therefore, a positioning method that enhances robustness and accuracy in complex scenarios is urgently needed. Summary of the Invention

[0003] To address the aforementioned technical shortcomings, the purpose of this invention is to provide a method for improving the location estimation accuracy in major TDoA networks, thus solving the problem of large positioning errors in existing technologies when there are insufficient signals or boundary regions.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for improving the location estimation accuracy in major TDoA networks, comprising: The infrastructure network broadcasts a TDoA message; the infrastructure network contains multiple anchor points. The mobile device receives a TDoA message sent by the anchor point; The mobile device estimates its own location based on the TDoA message; The mobile device detects whether it is outside the polygonal area formed by the anchor points; The mobile device detects the number of TDoA messages it receives; If the mobile device is outside the polygonal area or the number of TDoA messages received by the mobile device is less than 4, the mobile device sends TW-ToA messages to one or more anchor points. The mobile device receives the TW-ToA messages sent by the anchor points and estimates its own position by combining the TDoA messages and TW-ToA messages.

[0005] Preferably, in one possible implementation of the first aspect, the infrastructure network employs an ultra-broadband network.

[0006] Preferably, in one possible implementation of the first aspect, the mobile device employs an ultra-wideband device.

[0007] Preferably, in one possible implementation of the first aspect, estimating its own location based on the TDoA message includes: The mobile device calculates the time difference between the arrival of TDoA messages sent from different anchor points to the mobile device; Construct multiple hyperbolas based on time differences; Based on the constructed hyperbolas, the intersection points are calculated, and the coordinates of the mobile device are estimated.

[0008] Preferably, in one possible implementation of the first aspect, the estimation of its own position by combining TDoA messages and TW-ToA messages employs a fusion positioning algorithm.

[0009] Preferably, in one possible implementation of the first aspect, the fusion localization algorithm includes: Minimize objective function The objective function The weighted sum of the squared residuals of TDoA messages and the squared residuals of TW-ToA messages is calculated using the following formula:

[0010] in, This represents the location vector of the mobile device, and its dimension m is 1, 2, or 3. This represents the measurement value of the i-th TDoA message. n represents the number of TDoA messages, each TDoA message comes from an anchor pair, and each anchor pair consists of two anchors; Indicates location-based and the TDoA message estimates calculated for each anchor point pair location; Indicates the first One TW-ToA message measurement value, , This indicates the number of TW-ToA messages, with each TW-ToA message originating from one anchor point; Indicates location-based and the The estimated TW-ToA message value calculated from each anchor point location; and This represents the weighting coefficient.

[0011] Preferably, in one possible implementation of the first aspect, the TDoA message estimate The calculation is based on the location of the mobile device. The position of the anchor point The calculation formula is:

[0012] in, Indicates the first Dimensional mobile device location vector, and For the first Dimension 1 The position coordinate vectors of the two anchor points in a pair of anchor points. ; The estimated value of the TW-ToA message The calculation is based on the location of the mobile device. and the location of the anchor point, The calculation formula is:

[0013] in, For the first Dimension 1 The position coordinate vector of the anchor point measured by TW-ToA.

[0014] Preferably, in one possible implementation of the first aspect, the minimization objective function Transform into:

[0015] The gradient of the function is:

[0016] Convert to:

[0017]

[0018]

[0019] in, This is the weight matrix. , This is a vector of actual measured values. , For the estimated value vector, .

[0020] Preferably, in one possible implementation of the first aspect, the minimization objective function The solution is obtained using the Gauss-Newton method, including: Let the gradient be the Jacobian matrix H, and the search direction vector be... It is given by the following equation:

[0021] The updated location estimate is calculated using the following formula:

[0022] in, Indicates step size, This is the position estimate for the current iteration step. This is the position estimate after the next iteration step; Iterate through the above steps until convergence.

[0023] Preferably, in one possible implementation of the first aspect, the step size is determined by line search, specifically as follows: Initialize step size ; Calculate the objective function value ; if Not less than Then step size Halve; Repeat the above steps until Less than .

[0024] The beneficial effects of this invention are as follows: by introducing a TW-ToA ranging mechanism and fusing it with TDoA measurement, this invention improves the positioning accuracy at the edge of anchor point coverage or in areas with weak signals.

[0025] When the device is outside the polygonal area or receives fewer than 4 TDoA messages, the system automatically triggers the TW-ToA ranging process to obtain more accurate distance information through bidirectional communication, thus making up for the shortcomings of a single TDoA when the geometry is poor.

[0026] The fusion positioning algorithm optimizes the objective function by weighted least squares and combines the residuals of TDoA and TW-ToA to effectively suppress the propagation of measurement noise and geometric errors, improve positioning accuracy and stability, and enhance adaptability to complex environments. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. 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 effort.

[0028] Figure 1 This application provides a flowchart of a method for improving the accuracy of location estimation in major TDoA networks. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Example 1: As Figure 1 As shown, the present invention provides a method for improving the location estimation accuracy in major TDoA networks, comprising: First, the mobile device is powered on and begins the location process. The mobile device uses an ultra-wideband (UWB) device. The infrastructure network, which contains multiple anchor points, broadcasts TDoA messages. The mobile device receives TDoA messages sent by the anchor points and records the time the data arrives at the mobile device.

[0031] The mobile device calculates the time difference of arrival of TDoA message data sent from different anchor points based on the received TDoA messages, constructs multiple hyperbolas based on the time differences, and then estimates the coordinates of the mobile device based on the intersection of multiple hyperbolas, thus completing the preliminary position estimation.

[0032] Subsequently, the mobile device checks whether it is outside the polygonal area formed by the anchor points, and simultaneously checks the number of TDoA messages it has successfully received. To determine if the mobile device is inside the positioning area: if the mobile device is inside the polygonal area and has received at least 4 TDoA messages, the preliminary positioning result is output directly, completing one positioning operation; otherwise, the subsequent process continues.

[0033] When a mobile device determines that it is outside the polygon area, or receives fewer than 4 TDoA messages, it initiates the TW-ToA ranging process: the mobile device sends a TW-ToA request message to one or more anchor points; the mobile device receives a TW-ToA response message from the anchor points.

[0034] After obtaining TW-ToA ranging information, the mobile device combines the previously received TDoA and TW-ToA messages and uses a fusion positioning algorithm to recalculate its position.

[0035] Specifically, the fusion localization algorithm achieves this by minimizing an objective function, which is a weighted sum of the squared residuals of TDoA measurements and the squared residuals of TW-ToA measurements.

[0036] Let the position vector of the mobile device be... Its dimension It can be 1, 2, or 3. (From...) The TDoA measurement value for each anchor point pair is From The TW-ToA measurement value of each anchor point is .

[0037] Based on mobile device location and the Calculate the TDoA estimate based on the location of each anchor point pair. The calculation formula is:

[0038] in, Indicates the first Dimensional mobile device location vector, and For the first Dimension 1 The position coordinate vectors of the two anchor points in a pair of anchor points. .

[0039] Similarly, based on mobile device location and the Calculate the TW-ToA estimate based on the location of each anchor point. The calculation formula is:

[0040] in, For the first Dimension 1 The position coordinate vector of the anchor point measured by TW-ToA.

[0041] The objective function is defined as:

[0042] in, This represents the location vector of the mobile device, and its dimension m is 1, 2, or 3. This represents the measurement value of the i-th TDoA message. n represents the number of TDoA messages, each TDoA message comes from an anchor pair, and each anchor pair consists of two anchors; Indicates location-based and the TDoA message estimates calculated for each anchor point pair location; Indicates the first One TW-ToA message measurement value, , This indicates the number of TW-ToA messages, with each TW-ToA message originating from one anchor point; Indicates location-based and the The estimated TW-ToA message value calculated from each anchor point location; and This represents the weighting coefficient.

[0043] Minimize objective function This can be transformed into a nonlinear least squares problem, whereby the vector of actual measured values ​​is... The estimated value vector is Weight matrix .

[0044] The objective function can then be written as:

[0045] Its gradient can be calculated using the Jacobian matrix:

[0046] It can be converted to:

[0047]

[0048]

[0049] Further iterative solutions are obtained using the Gauss-Newton method: Let the gradient be the Jacobian matrix H, and the search direction vector be... It is given by the following equation:

[0050] Then, the update of the estimated position is given by the following formula:

[0051] in, The step size is determined through line search. This is the position estimate for the current iteration step. This is the updated position estimate for the next iteration.

[0052] Iterate through the above steps until convergence.

[0053] For step size The specific process determined through line search includes: Initialize step size ,calculate ,like Then step size Halve, Repeat until .

[0054] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for improving the accuracy of location estimation in major TDoA networks, characterized in that, include: The infrastructure network broadcasts a TDoA message; the infrastructure network contains multiple anchor points. The mobile device receives a TDoA message sent by the anchor point; The mobile device estimates its own location based on the TDoA message; The mobile device detects whether it is outside the polygonal area formed by the anchor points; The mobile device detects the number of TDoA messages it receives; If the mobile device is outside the polygonal area or the number of TDoA messages received by the mobile device is less than 4, the mobile device sends TW-ToA messages to one or more anchor points. The mobile device receives the TW-ToA messages sent by the anchor points and estimates its own position by combining the TDoA messages and TW-ToA messages.

2. The method for improving the location estimation accuracy in major TDoA networks according to claim 1, characterized in that, The infrastructure network uses an ultra-broadband network.

3. The method for improving the location estimation accuracy in major TDoA networks according to claim 1, characterized in that, The mobile device is an ultra-wideband device.

4. The method for improving the location estimation accuracy in major TDoA networks according to claim 1, characterized in that, The estimation of its own position based on TDoA messages includes: The mobile device calculates the time difference between the arrival of TDoA messages sent from different anchor points to the mobile device; Construct multiple hyperbolas based on time differences; Based on the constructed hyperbolas, the intersection points are calculated, and the coordinates of the mobile device are estimated.

5. A method for improving the location estimation accuracy in major TDoA networks according to claim 1, characterized in that, The method of combining TDoA and TW-ToA messages to estimate its own position uses a fusion positioning algorithm.

6. A method for improving the location estimation accuracy in a major TDoA network according to claim 5, characterized in that, The fusion positioning algorithm includes: Minimize objective function The objective function The weighted sum of the squared residuals of TDoA messages and the squared residuals of TW-ToA messages is calculated using the following formula: in, This represents the location vector of the mobile device, and its dimension m is 1, 2, or 3. This represents the measurement value of the i-th TDoA message. n represents the number of TDoA messages, each TDoA message comes from an anchor pair, and each anchor pair consists of two anchors; Indicates location-based and the TDoA message estimates calculated for each anchor point pair location; Indicates the first One TW-ToA message measurement value, , This indicates the number of TW-ToA messages, with each TW-ToA message originating from one anchor point; Indicates location-based and the The estimated TW-ToA message value calculated from each anchor point location; and This represents the weighting coefficient.

7. A method for improving the location estimation accuracy in major TDoA networks according to claim 6, characterized in that, The estimated value of the TDoA message The calculation is based on the location of the mobile device. The position of the anchor point The calculation formula is: in, Indicates the first Dimensional mobile device location vector, and For the first Dimension 1 The position coordinate vectors of the two anchor points in a pair of anchor points. ; The estimated value of the TW-ToA message The calculation is based on the location of the mobile device. and the location of the anchor point, The calculation formula is: in, For the first Dimension 1 The position coordinate vector of the anchor point measured by TW-ToA.

8. A method for improving the location estimation accuracy in a major TDoA network according to claim 6, characterized in that, The minimization objective function Transform into: The gradient of the function is: Convert to: in, This is the weight matrix. , This is a vector of actual measured values. , For the estimated value vector, .

9. A method for improving the location estimation accuracy in a major TDoA network according to claim 8, characterized in that, The minimization objective function The solution is obtained using the Gauss-Newton method, including: Let the gradient be the Jacobian matrix H, and the search direction vector be... It is given by the following equation: The updated location estimate is calculated using the following formula: in, Indicates step size, This is the position estimate for the current iteration step. This is the position estimate after the next iteration step; Iterate through the above steps until convergence.

10. A method for improving the location estimation accuracy in a major TDoA network according to claim 9, characterized in that, The step size is determined through line search, and the specific process is as follows: Initialize step size ; Calculate the objective function value ; if Not less than Then step size Halve; Repeat the above steps until Less than .

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