Reference base station dynamic selection method, positioning method, system, device and medium

Abstract

The present application relates to the field of ultra-wideband positioning technology, and discloses a method for dynamic selection of reference base stations, a positioning method, a system, a device, and a medium. The dynamic selection method includes: taking the historical position of a mobile device as the target assumed position, determining the assumed distance between the mobile device and each base station, and then determining the geometric precision factor; determining the link quality based on the channel response parameters of each base station when receiving the signal sent by the mobile device; calculating the Hadamard product of the geometric precision factor and the link quality of each base station to select a reference base station for positioning the mobile device at the current moment. The present application determines the geometric position relationship and channel status of the mobile device relative to each base station based on the geometric precision factor and link quality to select a reference base station for current positioning, so that the reference base station can be dynamically adjusted according to the target position and link communication conditions, thereby ensuring the high reliability of positioning results in different scenarios.

Description

Technical Field

[0001] The present application relates to the field of ultra-wideband positioning technology, and in particular to a reference base station dynamic selection method, positioning method, system, device and medium. Background Art

[0002] Ultra-Wide Band (UWB) is a new, carrier-free communication technology that differs significantly from traditional communication and positioning techniques. It utilizes nanosecond-scale time pulses to enable communication between pre-deployed anchor nodes with known locations and newly added blind nodes, and uses triangulation to determine their locations. Because UWB positioning signals can penetrate obstacles such as wood and glass, they can be used for various indoor and outdoor trajectory tracking applications, particularly in scenarios requiring high precision. Existing technologies for high-precision UWB positioning typically rely on TDOA (time difference of arrival) positioning technology, where multiple base stations receive signals from the same target and then measure the time difference between these signals arriving at each base station to determine the target's location. This approach leverages UWB's superior time resolution and stable, precise time synchronization in complex indoor environments, achieving centimeter-level positioning accuracy.

[0003] However, in the process of implementing TDOA-based UWB positioning, the existing technology is rather arbitrary in selecting reference base stations, and does not take into account the differences in link quality caused by different base stations due to different geographical locations and the different optimal reference base stations corresponding to different geographical locations. Therefore, when positioning is achieved only based on a single fixed reference base station during the target movement, it is difficult to ensure the accuracy and stability of the dynamic positioning results. Summary of the Invention

[0004] In view of this, in order to solve the technical problem in the prior art that during the target movement, the link quality differences between different base stations due to different geographical locations and the different optimal reference base stations corresponding to different geographical locations are not taken into account, but only rely on a single fixed reference base station for positioning, resulting in a decrease in accuracy and stability during dynamic positioning, the present application provides a reference base station dynamic selection method, positioning method, system, device and medium.

[0005] In a first aspect, the present application provides a method for dynamically selecting a reference base station, comprising:

[0006] using a historical position of the mobile device as a target assumed position, determining an assumed distance between the mobile device and each of the base stations based on the target assumed position, and determining a geometric dilution of precision based on the assumed distance; the geometric dilution of precision representing a geometric position relationship between the mobile device and each of the base stations;

[0007] determining link quality based on a channel response parameter of each of the base stations when receiving a signal sent by a mobile device;

[0008] A Hadamard product between the geometric dilution of precision and the link quality of each base station is calculated, and a reference base station for realizing positioning of the mobile device at the current moment is selected from all the base stations according to each Hadamard product.

[0009] In an optional embodiment, determining a geometric dilution of precision based on the assumed distance includes:

[0010] Constructing an observation matrix based on the assumed distances between the mobile device and each of the base stations;

[0011] The geometric dilution of precision between each of the base stations and the mobile device is determined respectively according to the measurement matrix.

[0012] In an optional embodiment, the calculating a Hadamard product between the geometric dilution of precision and the link quality of each base station, and selecting, from all the base stations based on each Hadamard product, a reference base station for implementing positioning of the mobile device at the current moment, includes:

[0013] Constructing a geometric dilution of precision matrix and a link quality matrix according to the geometric dilution of precision and the link quality of each base station, and normalizing the geometric dilution of precision matrix and the link quality matrix;

[0014] Calculating, according to the normalized geometric dilution of precision matrix and the link quality matrix, a Hadamard product value of the geometric dilution of precision matrix and the link quality matrix corresponding to each base station;

[0015] The base station corresponding to the minimum value of each Hadamard product value is used as a reference base station for realizing the positioning of the mobile device at the current moment.

[0016] In a second aspect, the present application provides a positioning method in combination with dynamic selection of reference base stations, comprising:

[0017] Using the aforementioned reference base station dynamic selection method, a reference base station is selected from multiple base stations for realizing the positioning of the mobile device at the current moment;

[0018] Calculating and calibrating the time difference of arrival of each non-reference base station relative to the reference base station;

[0019] constructing a hyperbola equation based on each of the arrival time differences;

[0020] The hyperbola equation is solved to obtain the current position of the mobile device.

[0021] In an optional implementation manner, calibrating the time difference of arrival of each non-reference base station relative to the reference base station includes:

[0022] The calibration deviation of the arrival time difference is determined by the initial position of the mobile device, and the calibration deviation in the arrival time difference is removed. Then, the noise introduced by the reference base station contained in the arrival time difference is eliminated by a multiple difference method to obtain the calibrated arrival time difference.

[0023] In an optional implementation, solving the hyperbola equation to obtain the current position of the mobile device includes:

[0024] Taking the positioning result of the mobile device at the previous moment as the initial position, iteratively calculating the deviation value of the initial position relative to the actual position of the mobile device according to the Taylor algorithm;

[0025] The sum of the initial position and the deviation value is used as a solution to the hyperbola equation to obtain the current position of the mobile device.

[0026] In an optional embodiment, the iterative calculation of the deviation value of the initial position relative to the actual position of the mobile device according to the Taylor algorithm includes:

[0027] Performing Taylor expansion on the hyperbolic equation at the initial position, and converting the expanded hyperbolic equation into a system of linear equations;

[0028] The linear equation group is iteratively solved by the least square method to obtain a deviation value of the initial position relative to the actual position of the mobile device.

[0029] In an optional embodiment, after taking the sum of the initial position and the deviation value as a solution to the hyperbola equation to obtain the current position of the mobile device, the method further includes:

[0030] Using a Kalman filter algorithm to predict the predicted position of the mobile device at the current moment using the positioning result of the mobile device at the previous moment;

[0031] The current position obtained after iteration of the Taylor algorithm is used as the measurement position, and the measurement position is subjected to Kalman filtering in combination with the predicted position to obtain the final positioning result of the mobile device at the current moment.

[0032] In a third aspect, the present application provides a fusion positioning system incorporating dynamic selection of reference base stations, comprising a mobile device and several base stations in communication connection;

[0033] The mobile device is used to adopt the aforementioned reference base station dynamic selection method to select a reference base station from each of the base stations for realizing the positioning of the mobile device at the current moment; and adopt the aforementioned positioning method combined with the dynamic selection of reference base stations to determine its own positioning result at the current moment based on the reference base station.

[0034] In a fourth aspect, the present application provides a mobile device comprising a processor and a memory, wherein the memory stores a computer program, and the processor is used to execute the computer program to implement the aforementioned reference base station dynamic selection method, and / or the aforementioned positioning method combined with dynamic selection of reference base stations.

[0035] The embodiments of the present application have the following beneficial effects:

[0036] The embodiment of the present application determines the geometric position relationship and channel status of the mobile device relative to each base station based on the geometric precision factor and link quality, and then determines the optimal base station to select a reference base station for reliable positioning at the current moment, thereby effectively reducing the error of the reference base station under the dynamic trajectory and improving the subsequent positioning accuracy; and compared with the positioning solution in the prior art that only relies on a single fixed base station, the solution of dynamically selecting the reference base station during the positioning process provided by this embodiment avoids the problem of positioning failure caused by a single reference base station being blocked by obstacles. Therefore, even if the external environment changes (such as the movement of obstacles), the selection of the reference base station can be quickly adjusted to ensure the reliability and stability of the positioning results in different application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] To more clearly illustrate the technical solution of this application, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of this application and should not be considered as limiting the scope of protection of this application. Those skilled in the art can also derive other relevant drawings based on these drawings without inventive effort.

[0038] Figure 1 A schematic diagram of the structure of a fusion positioning system in combination with dynamic selection of reference base stations in an embodiment of the present application is shown;

[0039] Figure 2 A schematic diagram of a flow chart of a method for dynamically selecting a reference base station in an embodiment of the present application is shown;

[0040] Figure 3 A schematic diagram of a flow chart of a positioning method in combination with dynamic selection of reference base stations in an embodiment of the present application is shown;

[0041] Figure 4Another flow chart of a positioning method in combination with dynamic selection of reference base stations in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0043] The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but rather merely represents selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative effort are within the scope of protection of the present application.

[0044] Hereinafter, the terms "including", "having" and their cognates, which may be used in various embodiments of the present application, are intended only to indicate specific features, numbers, steps, operations, elements, components or combinations of the foregoing items, and should not be understood as first excluding the existence of one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing items or the possibility of adding one or more features, numbers, steps, operations, elements, components or combinations of the foregoing items.

[0045] Furthermore, the terms “first,” “second,” “third,” etc., are merely used for distinguishing descriptions and are not to be understood as indicating or implying relative importance.

[0046] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those skilled in the art to which the various embodiments of the present application belong. The terms (such as those defined in generally used dictionaries) will be interpreted as having the same meaning as in the context of the relevant technical field and will not be interpreted as having an idealized meaning or an overly formal meaning unless clearly defined in the various embodiments of the present application.

[0047] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments may be combined with each other.

[0048] TDOA (Time Difference of Arrival) is a positioning technology that determines the location of the signal source by measuring the time difference between the signal arriving at multiple receivers.

[0049] Range Difference of Arrival (RDOA) refers to the distance difference between a mobile device and different base stations in a multi-base station positioning system.

[0050] GDOP (Geometric Dilution of Precision) is defined as the ratio of geometric positioning error to measurement error. It is used to measure the impact of the geometric configuration of the positioning system on positioning accuracy.

[0051] The Hadamard product is a matrix operation method that refers to the new matrix obtained by multiplying the corresponding elements of two matrices of the same dimension.

[0052] like Figure 1 As shown, an embodiment of the present application provides a fused positioning system (hereinafter referred to as the positioning system or system) that combines dynamic selection of reference base stations. Exemplarily, the positioning system includes a communicatively connected mobile device 110 and a plurality of base stations 120 (illustrated as base station 1, base station 2, ..., base station n, where n is an integer greater than 1). Every two devices in the positioning system can communicate with each other. The number of base stations 120 can be customized based on actual needs and is not limited in this embodiment.

[0053] The mobile device 110 includes but is not limited to smart phones (such as Android phones, IOS phones, etc.), personal computers, tablet computers, PDAs, e-readers, mobile Internet devices (MIDs), wearable smart devices, or other devices with communication functions.

[0054] In this embodiment, the positioning system uses the difference in signal propagation time when the mobile device transmits a signal to each base station to determine the position of the mobile device; that is, by recording the signal arrival time and calculating the time difference between different signals, the position information of the mobile device relative to each base station is inferred. Among them, the mobile device used to be positioned carries a UWB communication module; the base station is a device installed in a fixed position and also carries a UWB communication module. The position of the base station is known and serves as a positioning reference point in the entire positioning system. The positioning system in this embodiment can be widely used in indoor positioning, industrial automation, logistics tracking and other fields, and has the characteristics of high precision, multi-device collaboration and adaptability to complex environments.

[0055] In this embodiment, the mobile device is used to send data frames to several base stations through the internal UWB communication module; each base station is used to receive the data frame, record the receiving time point when the data frame is received, and return the feedback data frame to the mobile device, and the feedback data frame carries multiple information items including the receiving time point.

[0056] The positioning system or the mobile device itself determines the time difference between the target data frames arriving at each base station based on the time points at which the target data frames are received by multiple base stations. The mobile device's location (i.e., positioning result) is then determined based on this time difference. In other words, the positioning solution for the mobile device can be performed within the mobile device or by other devices within the positioning system (such as a cloud server). In other words, this embodiment does not limit the execution entity used to determine the positioning result for the mobile device, and specific configurations can be made based on actual needs.

[0057] Taking the example of a mobile device implementing its own positioning (i.e., performing the positioning calculation within the mobile device), the mobile device receives feedback data frames from each base station via its internal UWB communication module. Based on information such as the reception timestamp contained in the feedback data frames, the mobile device determines the time difference of arrival (TDOA) of each base station relative to a selected reference base station. This TDOA value is used to accurately locate the mobile device at the current moment. The reference base station is one of multiple base stations in the positioning system.

[0058] It is worth noting that during the trajectory tracking process, the signal needs to be corrected and optimized to avoid the influence of system errors caused by hardware, so as to obtain unbiased target positioning. In addition, during the positioning of the mobile device, in order to ensure that the reference base station can also adapt to the changes in geographical and signal factors caused by the position of the mobile device during dynamic positioning, this embodiment determines the reference base station during the mobile process by comprehensively considering the geometric precision factor and link quality, and then realizes the positioning of the mobile device based on the selected reference base station to reduce the impact of multipath interference. Among them, link quality is to evaluate the link quality between the base station and the mobile device.

[0059] In actual application scenarios, the reference base station is adaptively adjusted as the mobile device's location and communication conditions change. When the environment or usage scenario changes, the reference base station can be reselected to maintain the stability of system performance, thereby ensuring high reliability of positioning in different scenarios or locations, reducing dependence on fixed scenarios and strict base station layout, saving deployment costs, and shortening the construction period.

[0060] That is, this embodiment first selects a reference base station for realizing the positioning of the mobile device at the current moment based on the geometric precision factor and link quality, and then performs positioning solution based on the arrival time difference (i.e., TDOA value) of each non-reference base station relative to the reference base station to determine the location information of the mobile device at the current moment.

[0061] Based on this, this embodiment also provides a reference base station dynamic selection method. The aforementioned positioning system or the UWB module inside the mobile device in the positioning system can use this reference base station dynamic selection method to select a reference base station from multiple candidate base stations (each base station in the positioning system is regarded as a candidate base station) to achieve accurate positioning of the mobile device at the current moment.

[0062] It can be understood that the positioning result of the mobile device at each moment can first be selected from all candidate base stations through the dynamic reference base station selection method. The reference base station at the current moment is selected, and the arrival time difference between the mobile device and each base station at the current moment is calculated based on the reference base station. Then, the position of the mobile device at that moment is solved based on the arrival time difference. In other words, each positioning of the mobile device during the movement process requires the selection of a reference base station that meets the positioning requirements at the current moment. Different reference base stations can be selected corresponding to positioning requirements at different moments. Therefore, this embodiment improves the accuracy of the reference base station selection by dynamically selecting the reference base station, thereby improving the accuracy and stability of subsequent positioning.

[0063] Compared to existing technologies, the reference base stations used to locate mobile devices in this embodiment are no longer fixed. Instead, they adapt to changes in the target's location and the communication conditions between the target and the base stations. This adaptability is particularly effective in complex or dynamic environments, ensuring the positioning system maintains high reliability in various scenarios and minimizing the impact of multipath effects during signal propagation on positioning.

[0064] For example, Figure 2 As shown, taking the mobile device itself as an example of realizing positioning, the mobile device may specifically include the following steps when executing the reference base station dynamic selection method:

[0065] S210 , using the historical position of the mobile device as the target assumed position, determining the assumed distance between the mobile device and each base station according to the target assumed position, and determining the geometric precision dilution based on the assumed distance.

[0066] In this embodiment, the change in the position of the mobile device during movement will cause a change in the relative geometric position. Under a fixed base station position, the geometric dilution of precision (GDOP value) can reflect the positioning quality of different reference base stations in the application scenario.

[0067] First, all base stations in the positioning system are considered candidate reference base stations to obtain a geometric dilution of precision matrix (one base station is selected as a candidate reference base station at a time, and the remaining base stations are non-candidate reference base stations). To calculate the GDOP value of a mobile device point in the scene, the arrival distance difference (RDOA value) can be calculated based on the historical location of the mobile device (the historical location is the location coordinates of the mobile device at a relatively recent historical moment. In this embodiment, the location coordinates of the mobile device at the previous moment can be selected as the historical location) and the assumed distance between the mobile device and each base station. The arrival distance difference between each non-candidate reference base station and the mobile device can be expressed as:

[0068]

[0069] Where, For the i The difference in arrival distance between non-candidate reference base stations and mobile devices, ;coordinate( x, y, z ) is the three-dimensional coordinate of the historical location of the mobile device, coordinate ( ， ， ) is the i The three-dimensional coordinates of non-candidate reference base stations, coordinates ( ， ， ) is the three-dimensional coordinate of the candidate reference base station; the parameter item ( ) is the i The assumed distance between the non-candidate reference base stations and the historical location of the mobile device. Similarly, the parameter item ( ) is the assumed distance between the candidate reference base station and the historical location of the mobile device.

[0070] Taking the total differential of both ends of the above formula gives:

[0071]

[0072] Where, For the i The assumed distances between the non-candidate reference base stations and the historical location of the mobile device; is the assumed distance between the candidate reference base station and the historical location of the mobile device.

[0073] Furthermore, the geometric dilution of precision (GDOP) can be determined based on the aforementioned arrival distance difference. This GDOP characterizes the geometric relationship between the mobile device and all candidate base stations. It measures the impact of the relative distribution of base stations and mobile devices within the positioning system on positioning accuracy. A smaller GDOP value indicates higher positioning accuracy. The GDOP value depends on the geometric distribution of base stations. Generally, if all candidate base stations are evenly distributed and have wide coverage, the GDOP value is low. Conversely, if base stations within the positioning system are concentrated or have narrow coverage, the GDOP value is high.

[0074] In one example, an observation matrix is ​​first constructed based on the assumed distances between the mobile device and each candidate base station; the observation matrix is ​​used to determine the geometric position relationship between the mobile device and each candidate base station; and the geometric dilution of precision between each candidate base station and the mobile device is then determined based on the observation matrix.

[0075] Specifically, the total differential formula of the above arrival distance difference can be rewritten into matrix form:

[0076] ;

[0077] Where, ; K represents the differential of the arrival distance difference between each non-candidate reference base station from the 4th non-candidate reference base station to the i-1th non-candidate reference base station and the mobile device.

[0078]

[0079] Where, and are the RDOA value and the observation matrix respectively; M represents the geometric position relationship between each non-candidate reference base station from the 3rd non-candidate reference base station to the i-1th non-candidate reference base station and the mobile device.

[0080] Then, based on the above formula, the geometric dilution of precision (i.e., GDOP value) in the positioning system can be obtained through the observation matrix constructed above:

[0081]

[0082] Where, G represents the GDOP value; , and Respectively represent the position errors of the mobile device in the x, y, and z axes; Indicates ranging error; stands for the trace of a matrix; T stands for transpose.

[0083] S220 , determining link quality based on a channel response parameter of each base station when receiving a signal sent by the mobile device.

[0084] The movement of mobile devices also changes the environmental noise and multipath effects, which can further alter the links between base stations and mobile devices. This is because the movement of the mobile device causes the signal's response to environmental obstacles to change. For example, when a mobile device approaches reflective surfaces on the side of certain base stations, the links between these base stations and the mobile device are more likely to be affected by multipath. If this effect occurs in the link between a reference base station and a mobile device, it will cause errors in the TDOA values ​​obtained from all reference base stations. Therefore, to mitigate this effect during positioning, it is necessary to evaluate the links between base stations and mobile devices and select reference base stations based on high-quality links.

[0085] It is worth noting that the indicators used to evaluate link quality (i.e., channel response parameters) include but are not limited to the total signal energy of each path when each base station in the positioning system receives the signal, the signal energy of the first path when receiving the signal, the ratio of the signal energy of the first path to the total signal energy, and a weighted combination of one or more of the total signal energy, the signal energy of the first path when receiving the signal, and the ratio of the signal energy of the first path to the total signal energy.

[0086] In this embodiment, the channel response parameter is illustrated using the total signal energy of each path when each base station receives a signal as an example. Specifically, the received signal strength can be used to characterize the total signal energy, and thus the link quality. By comparing the signal strengths received by different base stations and selecting the base station with higher signal strength as the reference base station, the impact of multipath interference on positioning accuracy can be reduced. The received signal strength represents the signal power level and is specifically related to channel parameters such as the number of multipaths, delay, unit impulse function, and signal impulse response during signal propagation.

[0087] For example, if the signal or data frame sent by the mobile device to each base station via UWB technology is , the channel impulse response is , then the signal or data frame received by each base station for:

[0088]

[0089] Where, It can be expressed as:

[0090]

[0091] Where, t Indicates the moment; For the The amplitude of each path is closely related to path loss and multipath interference. For the i The delay of the path, is the unit impulse function, N is the number of multipath channels. Based on the above formula, the mathematical representation of the total energy of the received signal can be:

[0092]

[0093] Where, T is the duration of the pulse signal.

[0094] The energy of the received signal is positively correlated with the link quality; the higher the energy of the received signal, the better the link quality; conversely, the lower the energy of the received signal, the worse the link quality.

[0095] S230 , calculating the Hadamard product between the geometric dilution of precision and the link quality of each base station, and selecting a reference base station for implementing positioning of the mobile device at the current moment from all base stations based on each Hadamard product.

[0096] It's understandable that relying solely on the geometric dilution of precision and link quality alone cannot accurately assess the required reference base station, so a reasonable fusion of the two is necessary. Because link quality can represent the measurement error in the GDOP definition, this embodiment multiplies the base station's GDOP value and the link quality between the base station and the mobile device to represent the geometric positioning error of this positioning.

[0097] To unify the dimensions, both the GDOP value and the link quality must first be normalized. In practical applications, since smaller GDOP values ​​are preferred, while higher link quality is preferred, the evaluation trends of the two must be aligned during normalization. Furthermore, UWB power is typically limited to -41.3dBm / MHz, while the GDOP value is a positive number; therefore, the opposite sign of the two can be used to offset each other. A GDOP matrix and a link quality matrix can be constructed based on the GDOP of each base station and its link quality, respectively, and then normalized.

[0098] Exemplarily, a geometric dilution of precision matrix is ​​constructed based on the geometric dilutions of precision of all base stations, and a link quality matrix is ​​constructed based on the link qualities of all base stations. Then, the geometric dilution of precision matrix and the link quality matrix are normalized respectively to obtain normalized geometric dilution of precision matrix and link quality matrix:

[0099]

[0100] Where, and They are the geometric dilution of precision matrix and link quality matrix of each base station data integration respectively.

[0101] It can be understood that the normalization process is to divide each element in the original geometric dilution of precision matrix G (i.e. the geometric dilution of precision corresponding to each base station) by the maximum value max(G) to obtain the normalized geometric dilution of precision matrix; the original link quality matrix Each element in (i.e., the link quality corresponding to each base station) is divided by the maximum value max ( ) to obtain the normalized link quality matrix. The values ​​of all elements in the normalized geometric dilution of precision matrix and the link quality matrix are within the same target range. For example, the target range is [0, 1].

[0102] Then, based on the normalized geometric dilution of precision matrix and link quality matrix, the Hadamard product values ​​of the geometric dilution of precision matrix and the link quality matrix corresponding to each base station are calculated respectively; the base station corresponding to the minimum value of each Hadamard product value is used as the reference base station for realizing the positioning of the mobile device at the current moment.

[0103] That is, this embodiment calculates the Hadamard product between the geometric dilution of precision and the link quality corresponding to each base station, and selects a reference base station from multiple base stations based on the Hadamard product value.

[0104] Then, the final selected reference base station can be determined by the following formula:

[0105]

[0106] Where, Base station collection , represents the Hadamard product.

[0107] It can be understood that, among the Hadamard products of the geometric dilution of precision and the link quality of each base station, the base station corresponding to the minimum value of the Hadamard product is the reference base station used to achieve positioning of the mobile device at the current moment.

[0108] Obviously, when this embodiment uses the geometric dilution of precision and the received signal strength to comprehensively evaluate the selection of reference base stations, it analyzes the TDOA positioning impact caused by the movement of mobile devices from two perspectives: geometric geographic location (represented by GDOP) and link quality (represented by received signal strength). Then, each base station used as a reference base station is evaluated based on these two factors. Finally, the evaluation results of the two factors are integrated and used as the basis for selecting the reference base station.

[0109] Furthermore, during the dynamic selection of reference base stations, this embodiment determines the optimal base station based on the geometric position of the mobile device relative to each base station and the channel state. This results in a more reasonable measurement baseline, effectively reducing reference base station errors under dynamic trajectories and improving subsequent positioning accuracy. Compared to traditional positioning solutions that rely on a large number of fixed base stations, dynamic reference base station selection during positioning reduces reliance on fixed scenarios and strict base station layouts. In practical applications, there's no need to deploy numerous fixed base stations around a site, thus reducing deployment costs, shortening the system construction cycle, and providing greater flexibility for expansion and adjustment during subsequent maintenance. Furthermore, when the external environment or usage scenario changes (such as the appearance of new obstacles or the relocation of existing obstacles), the reference base stations can be repositioned or reconfigured accordingly to maintain overall system performance stability and avoid a sharp drop in positioning performance due to the failure of a single or a small number of fixed base stations.

[0110] Then, after dynamically selecting a reference base station for realizing positioning of the mobile device at the current moment from a plurality of candidate base stations, the positioning system may position the mobile device based on the selected reference base station.

[0111] For example, Figure 3 As shown, the embodiment of the present application further provides a positioning method combined with dynamic selection of reference base stations, the method comprising the following steps:

[0112] S310 , adopting a reference base station dynamic selection method to select a reference base station from multiple base stations for implementing positioning of the mobile device at the current moment.

[0113] Based on the method for dynamically selecting a reference base station in the aforementioned embodiment, a reference base station is selected from a plurality of candidate base stations to achieve accurate positioning of the mobile device at the current moment.

[0114] It can be understood that during the movement of a mobile device, if it is necessary to determine the positioning at each moment, it is necessary to select a reference base station for achieving positioning at the corresponding moment based on the aforementioned reference base station dynamic selection method each time. As a result, during the movement of the mobile device, the reference base station selected for each positioning may be different.

[0115] S320: Calculate and calibrate the arrival time difference of each non-reference base station relative to the reference base station.

[0116] S330: Construct a hyperbola equation based on each arrival time difference, solve the hyperbola equation, and obtain the current position of the mobile device.

[0117] In this embodiment, based on the selected reference base station, the time difference of arrival (ie, TDOA value) of each non-reference base station relative to the reference base station is calculated, and the current position of the mobile device is determined based on the TDOA value.

[0118] In one example, after receiving a signal or target data frame from a mobile device, each base station records the time of receipt of the signal or target data frame and then returns a feedback data frame to the mobile device, which includes parameters such as the reception time. After receiving the feedback data frames from each base station, the mobile device calculates the time difference of arrival (TDOA) between the mobile device and each base station based on the feedback data frames. It then calculates the distance difference of arrival (RDOA) based on the time difference of arrival.

[0119] Exemplarily, the arrival time difference of each non-reference base station relative to the reference base station is calculated first; a hyperbola equation is constructed according to each arrival time difference; the hyperbola equation is solved, and the solution of the hyperbola equation is used as the current position of the mobile device.

[0120] That is, the TDOA value is the time difference between the data frame (or signal) from the mobile device to the reference base station and the non-reference base station. For example, the TDOA value of the i-th base station is the time it takes for the signal to reach the i-th base station ( ), and the time when the signal arrives at the reference base station ( ) of the difference ( ). That is, the arrival time difference of any non-reference base station is the time difference between the arrival of the same signal sent by the mobile device at the non-reference base station and the reference base station, that is, .

[0121] Based on the TDOA value of each non-reference base station relative to the reference base station, the RDOA value (i.e., arrival distance difference) is calculated. A hyperbolic equation group is established based on the RDOA value, and the position of the mobile device at the current moment is obtained by solving the hyperbolic equation group.

[0122] Among them, each TDOA value corresponds to a hyperbolic trajectory centered on the reference base station and the non-reference base station, and the intersection of multiple hyperbolas is the position of the mobile device.

[0123] It's important to note that the TDOA value calculation is essentially the difference in arrival time between two base stations. This operation introduces noise into the differential TDOA data. In addition to interference and noise during communication, UWB positioning often suffers from systematic bias relative to the true position. To eliminate this systematic bias in UWB positioning and suppress the noise introduced by the reference base station, the TDOA value must be calibrated before positioning.

[0124] As an optional implementation, before constructing the hyperbolic equation system using the time difference of arrival (TDOA) in this embodiment, the time difference of arrival (TDOA) value can be determined based on the initial position of the mobile device. Each TDOA value can then be calibrated to obtain a reliable TDOA value, facilitating the subsequent generation of a reliable RDOA value and hyperbolic equation system. The TDOA value calibration process involves first fixing the mobile device at a known position for a period of time, collecting multiple data points during this period, and generating initial TDOA values ​​using an arbitrarily selected initial reference base station. The standard deviation of the TDOA value is then calculated, and the initial TDOA value is calibrated using the standard deviation.

[0125] For example, the mobile device is fixed at a specific location (i.e., the mobile device is located at a fixed location, which is used as the mobile device's initial location). A 3000ms calibration period is set before positioning (the specific duration of this calibration period can be set based on actual needs), and K positioning data are collected. During this period, the mobile device remains stationary at a known location. A base station is randomly selected from multiple candidate base stations as the initial reference base station. The initial time difference of arrival (TDOA) of each non-initial reference base station (excluding the initial reference base station) relative to the initial reference base station is determined. Specifically, the time difference between the reception time of each non-initial reference base station and the reception time of the initial reference base station is calculated to obtain multiple initial TDOA values.

[0126] Assume that the timestamp matrices received by each base station during the calibration period are , which can be further expressed as: .

[0127] Wherein, L represents the 4th to ( i-1 ) timestamp matrix corresponding to each base station, Represents the real UWB timestamp. The noise in the timestamp data corresponding to different base stations is Therefore, the TDOA value can be expressed as (that is, the mathematical expression formula of the TDOA value):

[0128] ;

[0129] in, is the true TDOA value of UWB without noise, is the superimposed noise.

[0130] It is worth noting that the initial reference base station selected here can be any one of multiple candidate base stations. Since the noise mean is 0, the average TDOA value within the calibration time can be obtained as:

[0131]

[0132] The base station position and the static position are used as prior information to obtain the reference time difference , so the calibration deviation of TDOA can be calculated as:

[0133]

[0134] In the subsequent positioning process, after each timestamp is obtained, the calibration deviation is subtracted from the timestamp data to obtain the TDOA value with the systematic error removed. That is, the calibration deviation within each arrival time difference is first determined by the initial position of the mobile device, and the calibration deviation within each arrival time difference is removed to eliminate the systematic error within the arrival time difference.

[0135] As a feasible implementation, subsequent positioning requires the use of the standard deviation of TDOA for error estimation. The TDOA value itself not only contains the systematic errors described in the above embodiments but also introduces noise from the reference base station, which increases the accuracy of the error estimation. Therefore, to suppress the noise error introduced by the reference base station, this embodiment also uses a multiple-difference method to eliminate the noise from the reference base station.

[0136] Exemplarily, this embodiment may utilize a multiple difference method to eliminate the noise introduced by the reference base station contained in the initial arrival time difference obtained in the aforementioned embodiment after eliminating the system error, and obtain a calibrated arrival time difference, which is used to construct a set of hyperbolic equations.

[0137] Specifically, from the mathematical expression formula of the above TDOA value, it can be seen that the TDOA values ​​corresponding to different base stations contain not only the noise of the base station but also the noise of the reference base station. Therefore, taking any two base stations (such as i Base stations, i +1 base station) can be obtained as:

[0138]

[0139]

[0140] Based on the above description, since the mobile device is stationary (i.e., fixed at a known location), the standard deviation obtained is the standard deviation of the noise in the TDOA value. Adding the two standard deviations of the TDOA of the two base stations above gives:

[0141]

[0142] Similarly, if the two base stations are used as a pair to generate TDOA values, that is, the noise is the noise in the data of these two base stations, the standard deviation of the TDOA values ​​is:

[0143]

[0144] Combining the above formulas, we can separate the noise of the reference base station and obtain:

[0145]

[0146] Therefore, before using TDOA values ​​to locate a mobile device, the calibration parameter C can be used to obtain a TDOA value that has been freed of systematic errors. The standard deviation of the TDOA value can then be used to subtract the noise of the reference base station from the freed TDOA value to obtain a more accurate TDOA value. In other words, the TDOA calibration process in this embodiment includes removing both systematic errors and reference base station noise.

[0147] Furthermore, after obtaining a more accurate TDOA value through the above-mentioned TDOA calibration process, a hyperbolic equation group can be constructed and solved based on the TDOA value to realize the positioning of the mobile device.

[0148] Exemplarily, the process of solving the hyperbolic equation group can be to use the positioning result of the mobile device at the previous moment as the initial position, iteratively calculate the deviation value of the initial position relative to the actual position of the mobile device based on the Taylor algorithm; and use the sum of the initial position and the deviation value as the solution of the hyperbolic equation to obtain the current position of the mobile device.

[0149] Among them, the positioning result of the mobile device at the previous moment can also be based on the reference base station dynamic selection method described in the aforementioned embodiment (that is, the same as S210-S230). After a reference base station is selected, the positioning method combined with the dynamic selection of the reference base station described in the aforementioned embodiment (that is, the same as S310-S330) is used to determine the positioning result of the mobile device at the previous moment based on the reference base station.

[0150] It is worth noting that to ensure the accuracy of mobile device positioning, this embodiment can iteratively calculate the deviation of the mobile device's initial position relative to its true position based on the Taylor algorithm, thereby obtaining a more accurate positioning result based on this deviation. The core concept of the Taylor algorithm is to linearize complex nonlinear problems, linearize the nonlinear positioning equation near the initial position, and gradually approximate the true position. The initial position of the mobile device is obtained by positioning the mobile device using the reference base station dynamically selected in the above embodiment to achieve the positioning of the mobile device at the current moment.

[0151] Specifically, the hyperbolic equation constructed from the denoised TDOA values ​​is Taylor expanded at the initial position of the mobile device, and the expanded hyperbolic equation is converted into a system of linear equations. This system of linear equations is iteratively solved using the least squares method to obtain the deviation of the mobile device's initial position relative to its true position. In other words, the solution to this system of linear equations is the deviation of the mobile device's initial position relative to its true position. This system of linear equations is iteratively solved to obtain the optimal solution, which is used as the final deviation of the initial position relative to the mobile device's true position.

[0152] For reference, assume that the initial position of the mobile device is , the deviation of the initial position relative to the true position is , then according to the Taylor series expansion:

[0153]

[0154] in, The initial positions correspond to The RDOA value of each base station, is the propagation speed of electromagnetic waves in vacuum, is the descending gradient.

[0155] Simplifying the above formula, we can get:

[0156]

[0157] Where:

[0158] ;

[0159] ;

[0160] .

[0161] The variables corresponding to the position of the mobile device can be solved by the least squares method as follows:

[0162]

[0163] In the formula, Q is the covariance matrix of the total error, and the above formula is iterated until the variable is less than the threshold Time , end the iteration to get the final deviation value ( ). Among them, the threshold The specific value of can be set according to actual needs and is not limited in this embodiment.

[0164] The sum of the initial position and the final deviation value obtained by iteration is used as the positioning result of the mobile device at the current position, that is:

[0165] .

[0166] This embodiment dynamically selects a reference base station, calibrates the TDOA value generated based on the dynamically selected reference base station, and uses the Taylor algorithm to iteratively optimize the initial position obtained based on the calibrated TDOA value, ultimately obtaining a high-precision positioning result for the mobile device. This embodiment effectively improves positioning accuracy by combining the advantages of TDOA positioning and Taylor series expansion, so that in the process of dynamic trajectory positioning of the signal, the positioning error of the positioning result obtained based on the dynamic selection of the reference base station is significantly lower than the positioning result error of a fixed single reference base station.

[0167] In one implementation, this embodiment may further optimize the positioning result obtained above using a Kalman filter algorithm to obtain a more accurate positioning result.

[0168] For example, Figure 4 As shown, the process of optimizing the positioning result by using the Kalman filter algorithm in this embodiment includes the following steps:

[0169] S410: Using a Kalman filter algorithm and a positioning result of the mobile device at a previous moment, the predicted position of the mobile device at the current moment is predicted.

[0170] S420: The current position obtained after the iteration of the Taylor algorithm is used as the measured position, and the measured position is processed by Kalman filtering in combination with the predicted position to obtain the final positioning result of the mobile device at the current moment.

[0171] In this embodiment, a Kalman filter is used to optimize the aforementioned positioning results. The Kalman filter algorithm is used to predict the current state based on the previous state (i.e., the current positioning result is predicted based on the previous positioning result), and a priori estimates of the error covariance are calculated. Then, based on the state-space model of the linear dynamic system, the positioning result is gradually optimized by iteratively updating the difference between the predicted value (the predicted value of the current positioning result) and the current value (the current positioning result obtained by iteratively using the Taylor algorithm in the aforementioned embodiment). The positioning result at the previous moment is the reference base station selected according to the method for dynamically selecting a reference base station in the aforementioned embodiment for achieving positioning of the mobile device at the previous moment, and the positioning result of the mobile device at the previous moment is determined based on this reference base station.

[0172] In order to maintain the continuity of coordinate data, the continuous motion trajectory of the mobile device during movement is divided into a set of approximate discrete points with a small period interval, and the state recursion of the Kalman filter is combined with the position estimation method to further optimize the processing. Assume that the system state at time t-1 is , the covariance matrix is , and Represent the position and velocity at time t-1 respectively, and the time interval between the two positioning is ; then the system state at time t is the system state at the current time.

[0173] It is worth noting that It is not the output of the Taylor algorithm and cannot be directly obtained. Therefore, this embodiment uses the principle that the speed at adjacent positioning moments is approximately constant and obtains the speed by using the positioning results of the first two moments, that is:

[0174]

[0175] The standard Kalman filter for dynamic trajectory tracking consists of two main steps: prediction and update. In the prediction step, the state of the previous moment (i.e. ) for the current state (i.e. ) to make predictions and obtain a priori estimates of the error covariance:

[0176]

[0177] in, represents the state transition matrix, and They are the predicted value of the state covariance matrix at time t and the estimated value of the state covariance matrix at time t-1. is the covariance matrix of the noise in the prediction process.

[0178] The update step is then responsible for feeding back the correction, incorporating the new measurements into the prior estimate to obtain an improved posterior estimate, and the final dynamic tracking result will be smoothed:

[0179]

[0180] Where, is the estimated value of the state covariance matrix at time t, which will be used for the next prediction; is the covariance matrix of the noise in the prediction process; This is the final positioning result; is the estimated value of the final positioning result; For measurement values ​​and state quantities The corresponding relationship between them is the unit matrix I here; is the Kalman gain; R is the covariance matrix of the noise in the measurement process.

[0181] This embodiment optimizes the positioning results through the above-mentioned Kalman filter algorithm and outputs the final positioning results, so that in dynamic scenarios, the positioning results can be smoothed using Kalman filtering, thereby effectively reducing noise interference and maintaining the continuity of coordinate data, thereby obtaining a smoother motion trajectory and ensuring the smoothness of the positioning results.

[0182] The present application also provides a mobile device. Exemplarily, the mobile device includes a processor and a memory, wherein the memory stores a computer program, and the processor runs the computer program to enable the mobile device to execute the above-mentioned reference base station dynamic selection method or the above-mentioned positioning method combined with the dynamic selection of the reference base station.

[0183] The processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, including at least one of a central processing unit (CPU), a graphics processing unit (GPU), a network processor (NP), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor, etc., and can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0184] The memory may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), and electrically erasable programmable read-only memory (EEPROM). The memory is used to store computer programs, and the processor can execute the computer programs accordingly after receiving an execution instruction.

[0185] The present application also provides a computer storage medium for storing the computer program used in the mobile device. The computer storage medium may be a readable storage medium, a non-volatile storage medium, or a volatile storage medium. For example, the computer storage medium may include, but is not limited to, various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0186] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and structure diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in an alternative implementation, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the structure diagram and / or flowchart, and the combination of boxes in the structure diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0187] In addition, the functional modules or units in the various embodiments of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0188] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a smart phone, personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application.

[0189] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A method for dynamically selecting a reference base station, characterized in that: include: using a historical position of the mobile device as a target assumed position, determining an assumed distance between the mobile device and each of the base stations according to the target assumed position, and determining a geometric dilution of precision based on the assumed distance; The geometric dilution of precision represents the geometric position relationship between the mobile device and each of the base stations; determining link quality based on a channel response parameter of each of the base stations when receiving a signal sent by a mobile device; A Hadamard product between the geometric dilution of precision and the link quality of each base station is calculated, and a reference base station for realizing positioning of the mobile device at the current moment is selected from all the base stations according to each Hadamard product.

2. The method for dynamic reference base station selection according to claim 1, wherein: Determining a geometric dilution of precision based on the assumed distance includes: Constructing an observation matrix based on the historical location of the mobile device and the assumed distances between the mobile device and the base stations; The geometric dilution of precision between each of the base stations and the mobile device is determined respectively according to the measurement matrix.

3. The method for dynamic selection of reference base stations according to claim 1, wherein: The calculating a Hadamard product between the geometric dilution of precision and the link quality of each base station, and selecting a reference base station for implementing positioning of the mobile device at a current moment from all the base stations based on each Hadamard product, includes: Constructing a geometric dilution of precision matrix and a link quality matrix according to the geometric dilution of precision and the link quality of each base station, and normalizing the geometric dilution of precision matrix and the link quality matrix; Calculating, according to the normalized geometric dilution of precision matrix and the link quality matrix, a Hadamard product value of the geometric dilution of precision matrix and the link quality matrix corresponding to each base station; The base station corresponding to the minimum value of each Hadamard product value is used as a reference base station for realizing the positioning of the mobile device at the current moment.

4. A positioning method combined with dynamic selection of reference base stations, characterized in that: include: Adopting the reference base station dynamic selection method according to any one of claims 1 to 3, selecting a reference base station for realizing positioning of the mobile device at the current moment from a plurality of base stations; Calculating and calibrating the time difference of arrival of each non-reference base station relative to the reference base station; constructing a hyperbola equation based on each of the arrival time differences; The hyperbola equation is solved to obtain the current position of the mobile device.

5. The positioning method according to claim 4, characterized in that: The calibrating the arrival time difference of each non-reference base station relative to the reference base station includes: The calibration deviation of the arrival time difference is determined by the initial position of the mobile device, and the calibration deviation in the arrival time difference is removed. Then, the noise introduced by the reference base station contained in the arrival time difference is eliminated by a multiple difference method to obtain the calibrated arrival time difference.

6. The positioning method according to claim 4 or 5, characterized in that: Solving the hyperbola equation to obtain the current position of the mobile device includes: Taking the positioning result of the mobile device at the previous moment as the initial position, iteratively calculating the deviation value of the initial position relative to the actual position of the mobile device according to the Taylor algorithm; The sum of the initial position and the deviation value is used as a solution to the hyperbola equation to obtain the current position of the mobile device.

7. The positioning method according to claim 6, characterized in that: The iterative calculation of the deviation value of the initial position relative to the actual position of the mobile device according to the Taylor algorithm includes: Performing Taylor expansion on the hyperbolic equation at the initial position, and converting the expanded hyperbolic equation into a system of linear equations; The linear equation group is iteratively solved by the least square method to obtain a deviation value of the initial position relative to the actual position of the mobile device.

8. The positioning method according to claim 6, wherein: After taking the sum of the initial position and the deviation value as a solution to the hyperbola equation to obtain the current position of the mobile device, the method further includes: Using a Kalman filter algorithm to predict the predicted position of the mobile device at the current moment using the positioning result of the mobile device at the previous moment; The current position obtained after iteration of the Taylor algorithm is used as the measurement position, and the measurement position is subjected to Kalman filtering in combination with the predicted position to obtain the final positioning result of the mobile device at the current moment.

9. A fusion positioning system combined with dynamic selection of reference base stations, characterized in that: including a mobile device and several base stations for communication connection; The mobile device is configured to select a reference base station from each of the base stations for implementing positioning of the mobile device at a current moment by using the reference base station dynamic selection method according to any one of claims 1 to 3; And, adopt the positioning method combined with dynamic selection of reference base stations as described in any one of claims 4 to 8, and determine the positioning result of itself at the current moment based on the reference base stations.

10. A mobile device, characterized in that: The mobile device includes a processor and a memory, the memory stores a computer program, and the processor is used to execute the computer program to implement the reference base station dynamic selection method described in any one of claims 1-3, and / or the positioning method combined with dynamic selection of reference base stations described in any one of claims 4-8.

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