UWB multi-base-station circular distribution structure and positioning method

Abstract

The invention provides a UWB multi-base-station circular station distribution structure and a positioning method, which are used for improving the regional three-dimensional positioning precision in an ultra wide band UWB system, and the positioning method comprises the steps: obtaining base station coordinates from a three-dimensional positioning region through a multi-base-station circular station distribution structure designed in a geometric circle; obtaining a timestamp, an arrival phase difference and CIR frame information through DS-TWR multi-base-station efficient communication between multiple base stations and a label; receiving distance and angle data of a plurality of UWB base stations, and introducing Kalman filtering to optimize a dynamic error; constructing an equation by using a nonlinear least square method, completing positioning coordinate calculation, and executing a multi-base-station data fusion positioning algorithm; high-precision three-dimensional positioning can be realized through an innovative circular station distribution structure and a positioning method, and the system has the advantages of simplicity and convenience in deployment, miniaturization, low power consumption, high precision and the like, adapts to variable and complex environments, and has a wide application prospect in regional three-dimensional positioning and connector automatic positioning systems.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless positioning, and particularly to a multi-base station circular layout structure and a positioning method based on ultra-wideband (UWB) technology. Background Art

[0002] With the wide application of intelligent positioning technology in fields such as unmanned aerial vehicles, robots, and industrial Internet of Things, the demand for high-precision, miniaturized, and low-power positioning systems is increasing day by day. Although traditional outdoor positioning technologies such as GPS and GNSS can provide meter-level accuracy, they have disadvantages such as large volume, high power consumption, and complex deployment. Indoor positioning technologies such as Bluetooth, RFID, and Wi-Fi have certain applications, but there are still great limitations in accuracy and stability in complex environments.

[0003] Ultra-wideband (UWB) technology, with its nanosecond-level narrowband pulses and strong anti-multipath interference ability, can achieve centimeter-level accuracy positioning, and at the same time, the power consumption is only in the milliwatt level, making it an ideal choice for high-precision indoor and outdoor positioning. UWB positioning is mainly divided into two schemes based on time difference of arrival (TDoA) and time of arrival (TOA). Among them, the TOA scheme has a higher fault tolerance rate and a simpler system structure through two-way ranging (TWR) technology.

[0004] However, the existing UWB positioning methods still have obvious deficiencies: on the one hand, the single-base station TOA and AOA joint positioning scheme has limited information, large random errors, and insufficient algorithm robustness; on the other hand, traditional multi-base station positioning usually adopts the apex layout method to form a square structure, which has great deployment difficulty, high safety risks, and the positions of the base stations are restricted by the building structure, and the advantages of angle measurement cannot be fully utilized. Therefore, there is an urgent need for an innovative base station layout structure positioning method that can not only reduce the complexity of multi-base station deployment but also provide stable and reliable high-precision three-dimensional positioning services. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies in the existing layout technology and provide a UWB multi-base station circular layout structure and a positioning method, which make the system have the characteristics of simple deployment, miniaturization, low power consumption, and high precision.

[0006] To achieve the above purpose, the present invention provides the following invention content:

[0007] A UWB multi-base station positioning method, comprising the following steps:

[0008] S1. Obtain the coordinates of the base stations from the three-dimensional positioning area through a multi-base station circular layout structure designed by geometric circles;

[0009] S2. Obtain the timestamp, arrival phase difference, and CIR frame information through the DS-TWR multi-base station efficient communication between the multi-base stations and the tags;

[0010] S3. Receive the distance and angle data of multiple UWB base stations, and introduce Kalman filtering to optimize the dynamic error;

[0011] S4. Use the nonlinear least squares method to construct an equation and complete the calculation of the positioning coordinates, and execute the multi-base station data fusion positioning algorithm;

[0012] A circular layout structure of multiple UWB base stations includes:

[0013] Circular layout structure module: used to determine the spatial placement state of each base station;

[0014] Coordinate calculation module: used to obtain the spatial coordinates of each base station.

[0015] The circular layout structure module is specifically implemented as follows:

[0016] Based on the three-dimensional regional space, evaluate the size of the spatial area that can be covered by the UWB signal, and construct a circular structure.

[0017] The coordinate calculation module is specifically implemented as follows:

[0018] Determine the integer point positions by iterating the circle radius. Taking the first base station as the origin, other base stations are evenly distributed along the integer points of the circumference, and the heights of each base station are distributed at different positions on the Z-axis, so as to determine the coordinates of each base station.

[0019] A computer is used to run the stored computer program for executing the UWB multi-base station positioning method.

[0020] The circular layout structure and positioning method of multiple UWB base stations provided by the present invention have the following beneficial effects:

[0021] The innovative circular layout structure of multiple base stations reduces the complexity of multi-base station deployment, and at the same time improves the positioning accuracy and stability of the system. This structure gives full play to the complementarity of the angle measurement and distance measurement of the base stations, provides omnidirectional three-dimensional space coverage, and provides redundant information in multiple dimensions to enhance the robustness of the system. The nonlinear least squares method is used to process the multi-base station collaborative measurement data, and the overall positioning accuracy is better than the traditional trilateration positioning implementation algorithm. In the dynamic test within the effective range, the system can stably track the straight-line and curved motion trajectories, and the positioning curve is continuous and smooth without obvious deviation, which is suitable for the regional real-time tracking of dynamic targets such as unmanned aerial vehicles.

[0022] Other beneficial effects in the embodiments of the present invention will be further described below. Description of the Drawings

[0023] Figure 1 It is a schematic diagram of the circular layout structure module provided by the embodiment of the present invention;

[0024] Figure 2 It is a flowchart of the implementation process of the positioning method provided by the embodiment of the present invention;

[0025] Figure 3 It is the result diagram of the three-dimensional positioning host computer provided by the embodiment of the present invention. Specific Embodiments

[0026] The following makes a detailed description of the embodiments of the present invention. It should be emphasized that the following description is merely exemplary and is not intended to limit the scope of the present invention and its applications.

[0027] Please refer to Figure 1 , the embodiment of the present invention provides a UWB multi-base station circular layout structure and a positioning method. This method realizes high-precision three-dimensional positioning through an innovative circular multi-station layout and multi-node signal cooperative processing. The system of this embodiment mainly consists of multiple UWB dual-antenna base stations, tags, and a computer terminal. Compared with the traditional solution, the circular layout structure of the present invention significantly reduces the complexity of multi-base station deployment, while improving the positioning accuracy and stability of the system.

[0028] I. A UWB multi-base station circular layout structure

[0029] Please refer to Figure 1 , the present invention adopts a UWB multi-base station circular layout structure, including: a circular layout structure module and a coordinate calculation module.

[0030] The circular layout structure module is used to determine the spatial placement state and radius of each base station. Through simulation analysis, it is determined that a circular layout with a radius of 5 meters is most suitable for various scenarios.

[0031] The coordinate calculation module determines the integer point positions by iterating the circle radius. Taking the first base station as the origin, other base stations are evenly distributed at integer points along the circumference, and the heights of each base station are distributed at different positions on the Z-axis, thereby determining the coordinates of each base station.

[0032] This circular layout structure has the following advantages compared with the traditional layout structure:

[0033] Give full play to the complementarity of the angle measurement and distance measurement of the base station, and improve the overall accuracy of the system;

[0034] The distance between base stations is moderate and the height distribution is reasonable, providing omnidirectional three-dimensional space coverage;

[0035] Provide redundant information in multiple dimensions to enhance the robustness of the system;

[0036] Reduce the difficulty of multi-base station deployment, and reduce installation risks and costs;

[0037] Adapt to the non-linear least squares positioning algorithm and optimize the positioning result.

[0038] II. A UWB multi-base station positioning method

[0039] Please refer to Figure 2 , in step S1, the multi-base station circular station layout structure designed by geometric circle design is used to obtain the base station coordinates from the three-dimensional positioning area. In this embodiment, through the designed multi-base station circular station layout structure, the origin is set at the lower tangent point of the circle and defined as base station 0 (anc0), with the coordinate of (0, 0, 0). The coordinates of the other base stations are respectively: anc1(-4, 2, 3), anc2(3, 1, 2) and anc3(-5, 5, 1). To obtain complete three-dimensional position information, each base station is deployed at different heights (0m, 1m, 2m and 3m) to ensure the diversity of Z-axis information collection. Each base station is equipped with a dual-antenna system, which can measure distance and angle simultaneously. To simplify angle measurement and analysis, the 0° reference direction of all base stations points to the center of the circle. Please refer to Figure 1 as shown by the dotted line in

[0040] Furthermore, in step S1, for the DS-TWR multi-base station efficient communication, the two-way ranging (DS-TWR) technology is adopted to realize the measurement of high-precision distance and angle information. Compared with the traditional single-sided two-way ranging (SS-TWR), this method can effectively overcome the ranging error problem caused by clock drift.

[0041] Furthermore, in this embodiment, the specific implementation method of the DS-TWR multi-base station efficient communication in step S1 includes:

[0042] 1. The tag first broadcasts a poll message, and the four base stations reply with resp messages in a preset order in turn;

[0043] 2. The tag records the timestamp (poll_tx) of sending the poll message and the timestamps (resp_rx) of receiving the resp messages from each base station;

[0044] 3. The tag sends a final message and records the sending timestamp (final_tx);

[0045] 4. Each base station records the timestamp (poll_rx) of receiving the tag poll message, the timestamp (resp_tx) of sending the resp message, the (resp_rx) of receiving the resp messages from other base stations, and the timestamp (final_rx) of receiving the tag final message;

[0046] 5. Each base station calculates the time of flight (TOF) with the tag according to all the collected timestamps by using the following formula:

[0047]

[0048] Wherein:

[0049] Tround1 is the difference between the timestamp (poll_tx) for sending the poll message and the timestamp (resp_rx) when the tag receives the resp message from the base station; Tround2 is the difference between the timestamp (resp_tx) for the base station to send the resp message and the timestamp (final_rx) for receiving the final message from the tag.

[0050] Treply1 is the difference between the timestamp (poll_tx) when the base station receives the poll message sent by the tag and the timestamp (resp_tx) when the current base station sends the resp message;

[0051] Treply2 is the difference between the timestamp (resp_rx) when the tag receives the resp message from the base station and the timestamp (final_tx) when the tag sends the final message.

[0052] 6. Finally, each base station calculates the actual distance from the tag by multiplying the TOF value by the speed of light (c).

[0053] In step S2, the timestamp, arrival phase difference, and CIR frame information are obtained. In addition to the timestamp and CIR frame, the system of the present invention also uses the angle of arrival (AOA) estimation technology to provide spatial angle information, further enhancing the positioning accuracy. Under far-field conditions, the chaotic timestamp sequence (STS) transmitted by UWB arrives at two receiving antennas with a spacing of d in a parallel manner.

[0054] When the signal arrives at the receiving antenna, due to the spatial position difference between the two antennas, the signal travels a distance D more to reach antenna RX1 than to reach antenna RX2, which results in a difference in the arrival phase of the STS between the two antennas. The system obtains this by measuring the arrival phase (POA) of the two antennas and calculating their difference. According to the geometric relationship, the angle of arrival (θ) of the signal can be calculated by the following formula:

[0055]

[0056] Wherein: θ represents the angle of arrival of the signal; is the measured phase difference; λ is the wavelength of the UWB signal; d is the spacing between the two receiving antennas.

[0057] The antenna spacing is usually designed to be half a wavelength or greater to obtain good angular resolution. Combining distance measurement, this method can provide direction information in a single base station environment and can achieve more complete spatial positioning when working in cooperation with multiple base stations.

[0058] In step S3, the distance and angle data of multiple UWB base stations are received, and Kalman filtering is introduced to optimize the dynamic error. Since the Kalman filter is an autoregressive estimator, based on the known state estimate value at the previous moment, the Kalman filter only needs to obtain the observed value of the current state to calculate the estimated value of the current state, without recording the historical information of observations or estimates. Kalman filtering is an ideal choice for dealing with dynamic positioning problems. This algorithm combines the system model with the measurement data and optimizes the state estimate through the prediction-update iterative process.

[0059] In the UWB positioning system, linear Kalman filtering is mainly used to smooth the distance and angle measurement values, filter short-term fluctuations, and improve the continuity and stability of positioning accuracy.

[0060] The greatest advantage of Kalman filtering lies in its high computational efficiency and low storage requirements, which is particularly suitable for real-time processing in embedded systems. This algorithm also lays a theoretical foundation for advanced filters such as the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) for dealing with more complex non-linear systems.

[0061] Furthermore, in this embodiment, Kalman filtering is mainly used to optimize the original measurement data, providing more reliable input for the non-linear least squares method, thereby improving the overall positioning accuracy.

[0062] In step S4, the non-linear least squares method is used to process the multi-base station cooperative measurement data to improve the positioning accuracy. The core idea of this method is to construct the objective function F(x) = ∑[f i (x)] 2 , where f i (x) represents the residual between the i-th observed value and its predicted value. In the positioning problem, this usually represents the difference between the measured distance and the theoretical distance.

[0063] In this embodiment, the distance from the tag to each base station is obtained by measuring the time of flight (TOF) of the wireless signal;

[0064] The steps of the algorithm embodiment of the present invention are as follows:

[0065] 1. Collect the distance data from the tag to each base station;

[0066] 2. Establish a data structure to store the base station coordinates and distance information;

[0067] 3. Construct the objective function. Based on the Euclidean distance formula, for the currently estimated tag position P(x, y, z), calculate the difference between its theoretical distance and the actual measured distance to each base station as the error function:

[0068] According to the Euclidean distance formula, the distance d i from the tag P to the base station A iIt should satisfy:

[0069]

[0070] For 4 base stations, 4 equations can be established to form a system of non - linear equations:

[0071]

[0072] In practical applications, there are usually errors in the measured distances, and it is difficult to find a solution that exactly satisfies all equations. Therefore, an error function is defined:

[0073]

[0074] The positioning problem is transformed into finding the tag coordinates P(x, y, z) that minimize the sum of squared errors:

[0075] minS(x, y, z) = ∑[f i (x, y, z)] 2

[0076] By introducing iterative optimization strategies such as the Levenberg - Marquardt algorithm to obtain the best - fitting solution, the system can efficiently solve non - linear equations and converge to a reasonable solution even when the initial estimate is inaccurate, thus obtaining an accurate three - dimensional positioning result.

[0077] III. System Test and Verification Results

[0078] The system of the present invention has been comprehensively tested in an open space of 8×15×3 m. The experimental site is selected on the top floor of a university laboratory, providing an open test environment. Four dual - antenna base stations are arranged according to the designed circular structure. The horizontal and vertical positions of the base stations are accurately calibrated using a level and a plumb line. The 0° reference direction of the dual - antenna of the base station is accurately calibrated by placing the tag at the center of the circle.

[0079] In the static test, the tag is fixed at the preset position by a tripod. A total of 18 test points are selected, and the positions are distributed within the experimental area: on the X - axis from - 2 m to 2 m, on the Y - axis from 1 m to 15 m, and on the Z - axis from 1 m to 2.5 m. For each position point, the system performs 30 sets of complete DS - TWR multi - base - station efficient communication ranging. The test results show that the root - mean - square error (RMSE) of the non - linear least - squares method of the present invention on all axes is concentrated in the range of 0 - 0.347 m, and the RMSE on the Y - axis is more concentrated, with an average value of 11.72 cm.

[0080] Please refer to Figure 3, during dynamic testing, the tag is fixed on the top of the drone and flies uniformly along a predetermined trajectory. The system calculates the tag position in real time and visualizes it on the PC host computer. The results show that within a distance of 15 m on the Y-axis, the system can accurately track the drone trajectory, and the positioning curve is continuous and smooth without obvious deviation.

[0081] Through the multi-base station circular layout structure, DS-TWR multi-base station efficient communication ranging, and non-linear least squares positioning algorithm, the present invention realizes a high-precision three-dimensional positioning system. This system has the advantages of simple deployment, miniaturization, low power consumption, and high precision, and is particularly suitable for use in resource-constrained application scenarios, providing reliable technical support for precise positioning applications such as the positioning of large ship deck equipment and the automatic docking of aerospace connectors.

Claims

1. A circular layout structure of UWB multi-base stations, characterized in that, Including: Circular base station layout structure module: used to determine the spatial placement state of each base station; Coordinate calculation module: used to obtain the spatial coordinates of each base station.

2. The UWB multi-base station circular layout structure according to claim 1, characterized in that The circular base station layout structure module is specifically implemented as follows: Based on the three-dimensional regional space, evaluate the size of the spatial area that can be covered by the UWB signal, and construct a circular structure.

3. The UWB multi-base station circular layout structure according to claim 1, characterized in that, The coordinate calculation module is specifically implemented as follows: Determine the integer point positions by iterating the circle radius. Taking the first base station as the origin, other base stations are evenly distributed along the integer points of the circumference, and the heights of each base station are distributed at different positions on the Z-axis, so as to determine the coordinates of each base station.

4. A UWB multi-base station positioning method, through the UWB multi-base station circular layout structure described in any one of claims 1-3, characterized in that, Including the following steps: S1. Obtain the base station coordinates from the three-dimensional positioning area through the multi-base station circular layout structure designed by geometric circles; S2. Through the DS-TWR multi-base station efficient communication between the multi-base station and the tag, obtain the timestamp, arrival phase difference, and CIR frame information; S3. Receive the distance and angle data of multiple UWB base stations, and introduce Kalman filtering to optimize the dynamic error; S4. Use the nonlinear least squares method to construct an equation and complete the positioning coordinate calculation, and execute the multi-base station data fusion positioning algorithm.

5. The UWB multi-base station positioning method according to claim 4, wherein In step S1, the step of obtaining the base station coordinates includes: Iterate the radius of the circle where the base stations are placed according to the size of the area to be located; Select 4 two-dimensional coordinates on a circle with a specific radius; Determine the height of the base station to complete the acquisition of the three-dimensional coordinates of the base station.

6. The UWB multi-base station positioning method according to claim 4, characterized in that, In step S2, the multi-base station and the tag respectively adopt the dual-antenna and single-antenna designs, which specifically include: The tag adopts a single-antenna design for communication initiation and stop, and the base station uses a dual-antenna design to implement PDOA measurement; In DS-TWR communication, use the multi-base station efficient communication ranging method to obtain UWB data.

7. The UWB multi-base station positioning method according to claim 4, characterized in that, In step S3, receiving the distance and angle data of multiple UWB base stations specifically includes: Each base station sends the ranging and angle measurement information at the current moment to other base stations through messages, and uses any UWB base station to converge all data and upload the data through the interface; Perform mean smoothing processing, and introduce Kalman filtering to optimize the dynamic errors of distance and angle, and remove noise and outliers.

8. The UWB multi-base station positioning method according to claim 4, characterized in that, In step S4, the nonlinear least squares method constructs an equation, including: Construct the objective function F(x) = ∑[f i (x)] 2 , where f i (x) represents the residual between the i-th observed value and its predicted value; Introduce algorithm iteration optimization strategies such as Levenberg-Marquardt, so that the system can efficiently solve the nonlinear equation and obtain the optimal positioning result.

9. A computer, characterized in that, The computer is used to run the stored computer program for executing the UWB multi-base station positioning method described in claim 4.

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