Instantaneous time difference of arrival estimation method, apparatus and device, and storage medium

Abstract

The invention provides an instantaneous time difference of arrival estimation method and device, equipment and a storage medium, and the method comprises the steps: carrying out the polynomial modeling of a time-varying time difference of arrival, obtaining a preset time difference of arrival model, converting a time difference of arrival estimation problem into a model parameter estimation problem, and obtaining a time difference of arrival estimation model. The model parameters of the preset time difference of arrival model are solved by using the N-1 groups of adjacent frame data, N is greater than or equal to 3, and after the model parameters are solved, any instantaneous time difference of arrival estimator can be solved by using the preset time difference of arrival model, so that the displacement influence caused by asynchronous receiving of anchor point signals by the moving target can be effectively reduced, and the accuracy of the moving target is improved. And the accuracy of time difference of arrival estimation is improved.

Description

Technical Field

[0001] The present application relates to the field of wireless positioning technology, and in particular to an instantaneous arrival time difference estimation method, device, equipment and storage medium. Background Art

[0002] Wireless positioning systems play an important role in many fields such as industrial automation, smart healthcare and smart transportation. Although the Global Navigation Satellite System (GNSS) is widely used, it is not available in satellite-denied environments such as urban canyons and indoors, and it is vulnerable to attacks. Therefore, regional positioning systems based on wireless signals such as Bluetooth, WIFI, and ultra-wideband (UWB) have become a research hotspot to meet the positioning needs in satellite-denied environments.

[0003] Wireless positioning systems usually consist of anchor points with known locations and targets to be positioned. Currently, solutions based on Time Difference of Arrival (TDOA) are widely used in time-division broadcast positioning systems.

[0004] Current time difference of arrival estimation methods are usually based on the quasi-static assumption, that is, the displacement of the target within the signal reception time interval is negligible. However, when the target moves at high speed or the anchor point transmission frequency is limited, this assumption will lead to low accuracy of the time difference of arrival estimation, thereby reducing the accuracy of target positioning. Summary of the invention

[0005] In view of this, the present application provides an instantaneous arrival time difference estimation method, device, equipment and storage medium to solve the deficiencies in the related art.

[0006] In a first aspect of the present application, a method for estimating an instantaneous arrival time difference is provided, comprising:

[0007] Acquire N frames of data received by the mobile target, wherein each frame of data includes a time-division broadcast signal and a receiving timestamp asynchronously received by the mobile target from at least two anchor points, and N is greater than or equal to 3;

[0008] Determine N-1 groups of adjacent frame data from the N frames of data, each group of adjacent frame data at least including a previous frame receiving timestamp, a previous frame transmitting timestamp, a previous frame clock error, a next frame receiving timestamp, a next frame transmitting timestamp, and a next frame clock error of a first anchor point and a second anchor point;

[0009] Determine estimated values ​​of model parameters in a preset arrival time difference model based on the N-1 groups of adjacent frame data, wherein the preset arrival time difference model is obtained based on a Taylor series expansion of a time-varying nonlinear function of a distance from an anchor point to the moving target;

[0010] Substitute the target time into the preset arrival time difference model to obtain the arrival time difference of the mobile target at the first anchor point and the second anchor point at the target time.

[0011] According to an embodiment of the present application, the time-division broadcast signal of each anchor point includes the location information of the anchor point, and the method further includes:

[0012] The mobile target is positioned according to the arrival time difference and the position information in the time-division broadcast signal of the first anchor point and the position information in the time-division broadcast signal of the second anchor point received by the mobile target at the target time.

[0013] According to one embodiment of the present application, the method further includes:

[0014] The mobile target is positioned according to a plurality of arrival time differences of the mobile target for a plurality of groups of first anchor points and second anchor points at the target time.

[0015] According to one embodiment of the present application, the method further includes:

[0016] Performing Taylor series expansion on time-varying nonlinear functions of the distances from the mobile target to the first anchor point and the second anchor point under global time to obtain a first polynomial model and a second polynomial model, wherein the distances from the mobile target to the first anchor point and the second anchor point are represented by signal arrival time TOA;

[0017] Respectively converting the first polynomial model and the second polynomial model from global time to the local time of the mobile target to obtain a third polynomial model and a fourth polynomial model;

[0018] The preset arrival time difference model is obtained according to the difference between the third polynomial model and the fourth polynomial model, and the polynomial coefficients in the preset arrival time difference model are the model parameters.

[0019] According to one embodiment of the present application, the method further includes:

[0020] For any adjacent frames, respectively determine a first relational expression between the local time of the first anchor point and the local time of the moving target and a second relational expression between the local time of the second anchor point and the local time of the moving target in a previous frame;

[0021] respectively determining, in a subsequent frame, a third relational expression between the local time of the first anchor point and the local time of the moving target and a fourth relational expression between the local time of the second anchor point and the local time of the moving target;

[0022] A linear equation for calculating the model parameters is determined based on the first relationship, the second relationship, the third relationship, the fourth relationship, and a Taylor series expansion of a time-varying nonlinear function of the distance from the mobile target to the first anchor point and the second anchor point at the local time of the mobile target.

[0023] According to an embodiment of the present application, determining estimated values ​​of model parameters in a preset arrival time difference model according to the N-1 groups of adjacent frame data includes:

[0024] For each group of adjacent frame data in the N-1 groups of adjacent frame data, substitute the previous frame receiving timestamp, the previous frame transmitting timestamp, the previous frame clock error, the next frame receiving timestamp, the next frame transmitting timestamp and the next frame clock error of the first anchor point and the second anchor point contained in the adjacent frame data into the linear equation to obtain a first linear equation;

[0025] Combining the first linear equations to obtain a linear equation system including N-1 first linear equations;

[0026] The linear equations are solved using a statistical estimation algorithm to obtain estimated values ​​of the model parameters.

[0027] According to an embodiment of the present application, the linear equation used to calculate the model parameters contains combined noise, and the combined noise includes a timestamp measurement error and a clock error estimation error of a time-division broadcast signal of an anchor point.

[0028] In a second aspect of the present application, there is provided an instantaneous arrival time difference estimation device, comprising:

[0029] An acquisition unit, configured to acquire N frames of data received by the mobile target, wherein each frame of data includes a time-division broadcast signal asynchronously received by the mobile target from at least two anchor points and a receiving timestamp, and N is greater than or equal to 3;

[0030] A first determining unit is used to determine N-1 groups of adjacent frame data from the N frames of data, each group of adjacent frame data at least including a previous frame receiving timestamp, a previous frame transmitting timestamp, a previous frame clock error, a next frame receiving timestamp, a next frame transmitting timestamp and a next frame clock error of a first anchor point and a second anchor point;

[0031] A second determination unit is used to determine an estimated value of a model parameter in a preset arrival time difference model according to the N-1 groups of adjacent frame data, wherein the preset arrival time difference model is obtained based on a Taylor series expansion of a time-varying nonlinear function of a distance from an anchor point to the moving target;

[0032] The estimation unit is used to substitute the target time into the preset arrival time difference model to obtain the arrival time difference of the mobile target at the first anchor point and the second anchor point at the target time.

[0033] In a third aspect of the present application, an electronic device is provided, including a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor is used to execute the machine executable instructions to implement the steps of the method proposed in the above embodiment.

[0034] In a fourth aspect of the present application, a machine-readable storage medium is provided, wherein the machine-readable storage medium stores machine-executable instructions, and when the machine-executable instructions are executed by a processor, the steps of the method proposed in the above embodiment are implemented.

[0035] In a fifth aspect of the present application, a computer program product is provided, comprising a computer program / instruction, which implements the steps of the method proposed in the above embodiment when executed by a processor.

[0036] It can be seen from the above technical solution that by polynomial modeling of the time-varying arrival time difference, a preset arrival time difference model is obtained, and the arrival time difference estimation problem is converted into a model parameter estimation problem. The model parameters of the preset arrival time difference model are solved using N-1 groups of adjacent frame data, where N is greater than or equal to 3. After solving the model parameters, the preset arrival time difference model can be used to calculate any instantaneous arrival time difference estimate, thereby effectively reducing the displacement effect caused by the asynchronous reception of the anchor point signal by the mobile target and improving the accuracy of the arrival time difference estimation.

[0037] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flowchart of an instantaneous arrival time difference estimation method provided in an embodiment of the present application;

[0039] Figure 2 It is a schematic diagram of a MAC layer protocol to which anchor broadcasting is compliant provided in an embodiment of the present application;

[0040] Figure 3 This is a schematic diagram of instantaneous arrival time difference estimation provided by an embodiment of the present application;

[0041] Figure 4 It is a flow chart of a method for estimating instantaneous arrival time difference and locating a target provided in an embodiment of the present application;

[0042] Figure 5 is a structural schematic diagram of an instantaneous arrival time difference estimation device provided in an embodiment of the present application;

[0043] Figure 6 It is a schematic diagram of the hardware structure of an electronic device shown in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0044] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0045] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0046] In order to enable those skilled in the art to better understand the technical solutions provided by the embodiments of the present application and to make the above-mentioned purposes, features and advantages of the embodiments of the present application more obvious and understandable, the technical solutions in the embodiments of the present application are further described in detail below in conjunction with the accompanying drawings.

[0047] Wireless positioning systems are widely used in industrial automation, smart healthcare, smart transportation and other fields. The most widely used wireless positioning system is the Global Navigation Satellite System (GNSS). However, since the satellite signal is weak and easily blocked, it is not available in satellite-denied environments such as urban canyons and indoor scenes, and it is vulnerable to attacks. In recent years, regional positioning systems composed of wireless signals such as Bluetooth, WIFI, and ultra-wideband UWB (Ultra Wide Band) have gradually attracted attention and attracted a lot of research. It is expected to provide accurate and continuous positioning services in satellite-denied environments.

[0048] In terms of multiple access mode selection, code division multiple access is easily affected by the near-far effect, while frequency division multiple access occupies too much spectrum resources and has high deployment complexity. Therefore, in recent years, positioning systems that use time division multiple access, such as time division broadcast positioning systems, have gradually received widespread attention and research. In terms of the selection of measurement observations, the scheme based on arrival time TOA (Time of Arrival) requires time synchronization between the anchor point and the target; although the TOF (Time of flight) scheme based on flight time does not require time synchronization, it requires several two-way communications, which increases the communication burden of the system. In contrast, the scheme based on arrival time difference TDOA (Time Difference of Arrival) does not require time synchronization between the anchor point and the target, and only requires one-way communication to save communication overhead, so it is widely used in time division broadcast positioning systems. In particular, the downlink arrival time difference scheme has the advantages of saving spectrum resources without active transmission by the target, and can achieve local self-positioning, and the system can support unlimited capacity targets.

[0049] However, current downlink time difference of arrival estimation schemes are all based on the quasi-static assumption, that is, the displacement of the target within the receiving time interval is considered negligible. However, in many practical applications, the anchor point transmission frequency is limited and the target is in a high-speed moving state. The displacement of the target within the receiving time interval cannot be ignored in the time difference of arrival estimation. Ignoring this displacement will lead to low accuracy of the time difference of arrival estimation, thereby reducing the accuracy of target positioning.

[0050] In addition, the current positioning of mobile targets in asynchronous networks is solved jointly by solving the time synchronization and positioning problems based on sequential arrival time observations. However, due to the need to consider the dynamics of the target and non-ideal clocks, a large number of additional variables need to be introduced, which reduces the performance of the positioning itself.

[0051] In view of this, an embodiment of the present application discloses an instantaneous arrival time difference estimation to address the deficiencies in the related art.

[0052] like Figure 1 As shown, Figure 1 1 is a flow chart of a method for estimating an instantaneous arrival time difference provided in an embodiment of the present application. The method for estimating an instantaneous arrival time difference may include the following steps:

[0053] S101: Acquire N frames of data received by a mobile target, wherein each frame of data includes a time-division broadcast signal asynchronously received by the mobile target from at least two anchor points and a receiving timestamp, and N is greater than or equal to 3.

[0054] In an embodiment of the present application, there are at least two anchor points in the asynchronous network, and the mobile target can asynchronously receive the time-division broadcast signal from the above anchor points in each frame, and respectively record the timestamp of receiving the anchor point time-division broadcast signal, that is, the receiving timestamp, wherein asynchronous reception means that when the mobile target receives signals from different anchor points, these signals do not arrive at the same time.

[0055] N frames of data received by the mobile target may be acquired, where N is a preset value and is greater than or equal to 3.

[0056] In an embodiment of the present application, each anchor point may broadcast signals to the outside in a time-division manner, and a mobile target may asynchronously receive the time-division broadcast signals of each anchor point at different time points and at different locations.

[0057] The embodiments of the present application do not specifically limit the type of anchor point. By way of example, the anchor point may be a base station, a wireless access point, or the like.

[0058] In some embodiments, each anchor point may periodically broadcast a signal in a time-division manner.

[0059] like Figure 2 As shown, Figure 2 Schematic diagram of a MAC layer protocol for anchor broadcast provided in an embodiment of the present application. The minimum repeating unit of the time-division broadcast signal is called a superframe, and its length is T f , is divided into multiple time slots of equal length within the superframe, and the length of each time slot is T s Each anchor point occupies an independent time slot and broadcasts the time division broadcast signal to the outside at the start time of the time slot. For example, anchor point i is at the start time T of time slot i in the pth frame. i (p) The time division broadcast signal is broadcasted externally, and the mobile target u can ui (p) The time-division broadcast signal of the pth frame from anchor point i is received at time.

[0060] like Figure 3 As shown, Figure 3 This is a schematic diagram of instantaneous arrival time difference estimation provided by an embodiment of the present application, wherein the dotted line portion is the motion trajectory of the mobile target, and each anchor point can periodically broadcast signals in a time-division manner. Anchor point 1 broadcasts time-division broadcast signal 1 externally at the start time of time slot i in the p-th frame, and the mobile target receives the time-division broadcast signal 1 of the p-th frame from anchor point 1 at position 1. Anchor point 2 broadcasts time-division broadcast signal 2 externally at the start time of time slot j in the p-th frame, and the mobile target receives the time-division broadcast signal 2 of the p-th frame from anchor point 2 at position 2. By analogy, anchor point M broadcasts time-division broadcast signal M externally at the start time of time slot N in the p-th frame, and the mobile target receives the time-division broadcast signal M of the p-th frame from anchor point M at position M.

[0061] S102: Determine N-1 groups of adjacent frame data from the N frames of data, each group of adjacent frame data at least including a previous frame receiving timestamp, a previous frame transmitting timestamp, a previous frame clock error, a next frame receiving timestamp, a next frame transmitting timestamp and a next frame clock error of a first anchor point and a second anchor point.

[0062] Determine N-1 groups of adjacent frame data from the obtained N frame data. That is, determine N-1 groups of continuous frame pairs from the N frame data, for example, assuming that N is 4, the N frames are the sth frame, the s+1th frame, the s+2th frame, and the s+3th frame, wherein the sth frame and the s+1th frame are adjacent frames, the s+1th frame and the s+2th frame are adjacent frames, and the s+2th frame and the s+3th frame are adjacent frames, then the sth frame data and the s+1th frame data can be determined as the first group of adjacent frame data, the s+1th frame data and the s+2th frame data can be determined as the second group of adjacent frame data, and the s+2th frame data and the s+3th frame data can be determined as the third group of adjacent frame data.

[0063] Each anchor point in the asynchronous network pre-implements clock synchronization, but there will still be a certain synchronization error. The time-division broadcast signal of each anchor point at least contains the transmission timestamp of the time-division broadcast signal transmitted by the anchor point and the clock error between the local time of the anchor point and the global time.

[0064] Regarding adjacent frames, adjacent frames may include a previous frame and a next frame, where the previous frame refers to the previous frame in the adjacent frames, and the next frame refers to the next frame in the adjacent frames. For example, if the sth frame and the s+1th frame are adjacent frames, then the sth frame is the previous frame, and the s+1th frame is the next frame.

[0065] For each group of adjacent frame data in the N-1 groups of adjacent frame data, the group of adjacent frame data can be divided into the previous frame data and the next frame data. The previous frame data at least includes the previous frame receiving timestamp, the previous frame transmitting timestamp and the previous frame clock error of the first anchor point, and the previous frame receiving timestamp, the previous frame transmitting timestamp and the previous frame clock error of the second anchor point. The previous frame receiving timestamp of the first / second anchor point here refers to the receiving timestamp recorded when the mobile target receives the time-division broadcast signal of the previous frame in the adjacent frames from the first / second anchor point.

[0066] The next frame data at least includes the next frame reception timestamp, the next frame transmission timestamp and the next frame clock error of the first anchor point, and the next frame reception timestamp, the next frame transmission timestamp and the next frame clock error of the second anchor point. The next frame reception timestamp of the first / second anchor point here refers to the reception timestamp recorded when the mobile target receives the time-division broadcast signal of the next frame in the adjacent frames from the first / second anchor point.

[0067] In some embodiments, for a target frame, the time-division broadcast signal of each anchor point includes a transmission timestamp of the time-division broadcast signal transmitted by the anchor point and a clock error and variance between the local time of the anchor point at the initial moment of the target frame and the global time.

[0068] S103: Determine estimated values ​​of model parameters in a preset arrival time difference model based on the N-1 groups of adjacent frame data, wherein the preset arrival time difference model is obtained based on a Taylor series expansion of a time-varying nonlinear function of a distance from an anchor point to the moving target.

[0069] For a mobile target, its distance to each anchor point is a time-varying nonlinear function, and the nonlinear function can be expressed by a polynomial model in a short time through Taylor series expansion. The preset arrival time difference model is obtained based on the Taylor series expansion of the time-varying nonlinear function of the distance from the anchor point to the mobile target. The preset arrival time difference model contains unknown polynomial coefficients, which are the model parameters.

[0070] The l-order coefficient of the model parameter can be l = 0, 1, 2, ..., L-1. In order to ensure accurate characterization of the arrival time difference changes in a relatively short period of time under normal circumstances and improve the accuracy of the instantaneous arrival time difference estimation, this application limits the value range of the l-order coefficient of the model parameter to l = 0, 1, 2 through pre-calculation.

[0071] In some embodiments, N is determined according to the value of the l-th order coefficient of the model parameter.

[0072] In some embodiments, the l-order coefficient of the model parameter can be selected as l = 0, 1, and L = 2. For the case of L = 2, at least two linear equations need to be combined to solve the model parameters, otherwise the model parameters will not have a unique solution. Therefore, in this application, it is necessary to determine the estimated value of the model parameter in the preset arrival time difference model based on at least 2 sets of adjacent frame data, and N = 3.

[0073] In some embodiments, the l-order coefficient of the model parameter can be selected as l = 0, 1, 2, and L = 3. For the case of L = 3, at least three linear equations need to be combined to solve the model parameters, otherwise the model parameters will not have a unique solution. Therefore, in this application, it is necessary to determine the estimated values ​​of the model parameters in the preset arrival time difference model based on at least 3 sets of adjacent frame data, that is, N = 4.

[0074] The estimated values ​​of the model parameters in the preset arrival time difference model may be determined according to N-1 groups of adjacent frame data.

[0075] In some embodiments, for each group of N-1 groups of adjacent frame data, the previous frame reception timestamp, previous frame transmission timestamp, previous frame clock error, next frame reception timestamp, next frame transmission timestamp and next frame clock error of the first anchor point and the second anchor point contained in the adjacent frame data can be substituted into a preset linear equation for calculating model parameters, thereby obtaining a linear equation group containing N-1 linear equations for calculating model parameters after substituting actual data.

[0076] Among them, the above-mentioned preset linear equation for calculating model parameters is obtained based on the timing relationship between the local time of the first anchor point and the local time of the mobile target in adjacent frames and the timing relationship between the local time of the second anchor point and the local time of the mobile target.

[0077] The linear equations are solved using a statistical estimation algorithm to obtain estimated values ​​of the model parameters.

[0078] The embodiments of the present application do not specifically limit the above statistical estimation algorithm. Exemplarily, the above statistical estimation algorithm may be a weighted least squares algorithm, an iterative reweighted least squares method, a ridge regression, or the like.

[0079] S104: Substitute the target time into the preset arrival time difference model to obtain the arrival time difference of the mobile target at the first anchor point and the second anchor point at the target time.

[0080] The preset arrival time difference model contains unknown polynomial coefficients, which are model parameters. After the estimated values ​​of the model parameters are obtained by solving S103, any target time can be substituted into the preset arrival time difference model to obtain the estimated arrival time difference of the mobile target for the first anchor point and the second anchor point at the target time.

[0081] In some embodiments, the mobile target may be positioned based on the arrival time difference.

[0082] In some embodiments, the position of each anchor point in the asynchronous network is known and fixed, and the time-division broadcast signal of each anchor point includes the position information of the anchor point.

[0083] The mobile target may be positioned according to the arrival time difference and the position information in the time-division broadcast signal of the first anchor point and the position information in the time-division broadcast signal of the second anchor point received by the mobile target at the target time.

[0084] For example, the distance difference between the mobile target and the first anchor point and the second anchor point can be calculated based on the arrival time difference. If the position information of the first anchor point and the second anchor point is known, the mobile target can be located through triangulation or other positioning algorithms.

[0085] In some embodiments, multiple groups of instantaneous arrival time difference estimation values ​​of the mobile target at the same time may be obtained, that is, multiple arrival time differences of the mobile target for multiple groups of first anchor points and second anchor points at the target time may be obtained.

[0086] The mobile target is positioned according to a plurality of arrival time differences of the mobile target for a plurality of groups of first anchor points and second anchor points at a target time.

[0087] In this embodiment, after solving the model parameters, the preset arrival time difference model can be used to calculate any instantaneous arrival time difference estimate, and the mobile target can be positioned based on multiple groups of instantaneous arrival time difference estimates of the mobile target at the same time, thereby improving the accuracy of target positioning.

[0088] The multi-lateral positioning method based on arrival time difference in static scenes (quasi-static assumption) has been well studied and will not be elaborated here.

[0089] In some embodiments, there are at least four anchor points in the asynchronous network, and multiple arrival time differences of the mobile target for multiple groups of first anchor points and second anchor points at the target time can be obtained.

[0090] The mobile target is two-dimensionally positioned according to a plurality of arrival time differences of the mobile target for a plurality of groups of first anchor points and second anchor points at a target time.

[0091] For example, Figure 3 As shown, there may be four anchor points in the asynchronous network, namely anchor point 1, anchor point 2, anchor point i and anchor point M, and multiple groups of first anchor points and second anchor points may include anchor point 1 and anchor point 2, anchor point 1 and anchor point i, anchor point 1 and anchor point M, anchor point 2 and anchor point i, anchor point 2 and anchor point M, and anchor point i and anchor point M. The mobile target may be two-dimensionally positioned according to multiple arrival time differences of the mobile target for the above multiple groups of first anchor points and second anchor points at the target time.

[0092] In some embodiments, there are at least five anchor points in the asynchronous network, and multiple arrival time differences of the mobile target for multiple groups of first anchor points and second anchor points at the target time can be obtained.

[0093] The mobile target is three-dimensionally positioned according to a plurality of arrival time differences of the mobile target for a plurality of groups of first anchor points and second anchor points at a target time.

[0094] In an embodiment of the present application, by acquiring N frames of data received by the mobile target, wherein each frame of data includes a time-division broadcast signal and a reception timestamp asynchronously received by the mobile target from at least two anchor points, and N is greater than or equal to 3, N-1 groups of adjacent frame data are determined from the N frames of data, and each group of adjacent frame data at least includes a previous frame reception timestamp, a previous frame transmission timestamp, a previous frame clock error, a next frame reception timestamp, a next frame transmission timestamp, and a next frame clock error of a first anchor point and a second anchor point; based on the N-1 groups of adjacent frame data, estimated values ​​of model parameters in a preset arrival time difference model are determined, wherein the preset arrival time difference model is obtained based on a Taylor series expansion of a time-varying nonlinear function of a distance from an anchor point to the mobile target; the target time is substituted into the preset arrival time difference model to obtain the arrival time difference of the mobile target at the target time for the first anchor point and the second anchor point. By modeling the time-varying arrival time difference through polynomials, a preset arrival time difference model is obtained, and the arrival time difference estimation problem is converted into a model parameter estimation problem. The model parameters of the preset arrival time difference model are solved using N-1 groups of adjacent frame data, where N is greater than or equal to 3. After solving the model parameters, the preset arrival time difference model can be used to calculate any instantaneous arrival time difference estimate, thereby effectively reducing the displacement effect caused by the asynchronous reception of anchor point signals by the mobile target and improving the accuracy of the instantaneous arrival time difference estimation.

[0095] In some embodiments, for a mobile target, its distance to each anchor point (expressed by signal arrival time TOA) is a time-varying nonlinear function, and the nonlinear function can be expressed by a polynomial model in a shorter time through Taylor expansion.

[0096] Taking the mobile target u and the first anchor point as anchor point i as an example, the TOA between the two at global time t is shown in formula (1) (i.e., the first polynomial model corresponding to the first anchor point):

[0097]

[0098] Among them, τ ui (t) represents the arrival time TOA of the signal from anchor point i to mobile target u at global time t, c represents the propagation speed of the signal in the propagation medium, which is usually close to the speed of light in wireless communication, and R ui (t) represents the distance from anchor point i to mobile target u at global time t, and L represents the order of the Taylor expansion polynomial model.

[0099] τ ui (t) Convert from global time t to local time t of mobile target u u , we get formula (2) (i.e., the third polynomial model corresponding to the first anchor point).

[0100]

[0101] in, represents the local time t of the moving target u u The coefficients of the lower polynomial model, L is the polynomial order.

[0102] Then the actual distance d from the moving target u to the anchor point i is ui (t u ) can be written as:

[0103]

[0104] in,

[0105] Assuming that the second anchor point is anchor point j, the actual distance d from the moving target u to anchor point j can be obtained in the same way ji (t u ).

[0106] Therefore, the distance difference d between the moving target u and the anchor point i and the anchor point j is u；ij It can be written as:

[0107]

[0108] The distance difference d u；ij Dividing by the propagation speed c of the signal in the propagation medium, the preset arrival time difference model can be obtained, where: γ u；ij The polynomial coefficients representing the preset arrival time difference model, that is, the model parameters of the preset arrival time difference model.

[0109] In some embodiments, for any adjacent frames, a first relational expression between the local time of the first anchor point and the local time of the moving target and a second relational expression between the local time of the second anchor point and the local time of the moving target are respectively determined in a previous frame;

[0110] respectively determining, in a subsequent frame, a third relational expression between the local time of the first anchor point and the local time of the moving target and a fourth relational expression between the local time of the second anchor point and the local time of the moving target;

[0111] A linear equation for calculating the model parameters is determined based on the first relationship, the second relationship, the third relationship, the fourth relationship, and a Taylor series expansion of a time-varying nonlinear function of the distance from the mobile target to the first anchor point and the second anchor point at the local time of the mobile target.

[0112] Specifically, take the moving target u, the first anchor point as anchor point i, and the second anchor point as anchor point j as an example.

[0113] The timestamp of the time-division broadcast signal of the mth frame transmitted by anchor point i is T i (m) , the receiving timestamp of the corresponding mobile target u is The known signal propagation time is recorded as The other frame marking methods are similar and will not be described here.

[0114] Taking the mth frame time-division broadcast signal transmitted by anchor point i as an example, non-ideal clock error is considered, but clock error estimation error and timestamp measurement noise are not considered for the time being. The local time of anchor point i and the local time of mobile target u in the mth frame are converted to global time, so as to obtain the temporal relationship between the local time of anchor point i and the local time of mobile target u in the mth frame, that is, the first relation.

[0115] The temporal relationship between the local time of anchor point i and the local time of mobile target u is as follows:

[0116]

[0117] Among them, φ i (m) represents the clock error (clock synchronization error) between the local time and the global time of anchor point i at the initial moment of the mth frame, α u and β u is the correction parameter used to convert the local time of the mobile object u to the global time.

[0118] In some embodiments, the time-division broadcast signal of each anchor point includes the clock error and variance between the local time of the anchor point at the initial time of the target frame and the global time. For example, the time-division broadcast signal of the mth frame transmitted by anchor point i includes the clock error φ between the local time of anchor point i at the initial time of the mth frame and the global time i (m) With variance The clock synchronization error satisfies the zero-mean Gaussian distribution, that is,

[0119] In some embodiments, the non-ideal clock error can be modeled as an affine model in a shorter time period as follows:

[0120] t=α u t u +β u (6)

[0121] Where t represents the global time, t u represents the local time of the mobile target u, α u and β uis the correction parameter used to convert the local time of the mobile target u to the global time. For an ideal clock that is completely synchronized with the global time, [α u ,β u ]=[1,0].

[0122] Similarly, the temporal relationship between the local time of anchor point j and the local time of mobile target u in the nth frame can be obtained, that is, the second relationship, as shown below:

[0123]

[0124] Subtracting formula (5) from formula (7) can eliminate the unknown parameter β u , we get formula (8), as shown below:

[0125]

[0126] To eliminate the unknown parameter α u , and considering the p-th frame message transmitted by anchor point i and the q-th frame message transmitted by anchor point j, we can get the following formula:

[0127]

[0128] Dividing formula (8) by formula (9) can eliminate the unknown parameter α u , and we get the following formula:

[0129]

[0130] Formula (10) can be rearranged to obtain:

[0131]

[0132] Substituting the TOA polynomial model of formula (2) into formula (11) yields:

[0133]

[0134] in, and They are γ ui and γ uj The l-order coefficients (l=0,1,2,...,L-1). The specific expressions are:

[0135]

[0136] Formula (12) contains the unknown number γ ui and γ uj The part satisfies the following formula:

[0137]

[0138] in, satisfy:

[0139]

[0140] Note that if Then formula (12) is the model parameter γ in the preset arrival time difference model u；ij The equation of .

[0141] If the traditional arrival time difference estimation method is used, that is, the TOA observations in the same frame are subtracted, the obtained formula (12) is singular and unsolvable. Therefore, the present application designs a frame error time difference (i.e., adjacent frame time difference) strategy to construct a linear equation, and sets m=q=s, n=p=s+1, that is, the time difference is made between the sth frame of anchor point i and the s+1th frame of anchor point j, and the time difference is made between the s+1th frame of anchor point i and the sth frame of anchor point j. This strategy can ensure that under the time-division broadcast protocol defined in the present application, It is strictly valid when l (l-order coefficient) = 0, 1, 2, which ensures the accurate characterization of the arrival time difference changes in a short period of time under normal circumstances.

[0142] When m=q=s, n=p=s+1, the linear equation for calculating the model parameters in the preset arrival time difference model can be shown as follows:

[0143]

[0144] in,

[0145] for It is strictly true when l (l-order coefficient) = 0, 1, 2. Specifically, the l-order coefficient can be selected as l = 0, 1, and the corresponding polynomial order is L = 2. The l-order coefficient can also be selected as l = 0, 1, 2, and the corresponding polynomial order is L = 3.

[0146] Combine K (K is greater than or equal to L) linear equations as shown in formula (17) to construct a linear equation system, so as to ensure that the constructed linear equation system is non-singular and has a unique solution. Since a linear equation as shown in formula (17) requires the use of a set of adjacent frame data. Therefore, in an embodiment of the present application, when the polynomial order L=2, at least 2 sets of adjacent frame data need to be obtained, so that this strategy can ensure that the constructed linear equation system is non-singular and has a unique solution compared to the traditional method.

[0147] When the polynomial order L=3, at least three sets of adjacent frame data need to be obtained, so that compared with the traditional method, this strategy can ensure that the constructed linear equation system is non-singular and has a unique solution.

[0148] In this embodiment, multi-frame data is used to eliminate unknown correction parameters used to convert the local time of the mobile target to the global time, and a linear equation for calculating the model parameters in the preset arrival time difference model is constructed through the frame error time difference (adjacent frame time difference) strategy, so that the model parameters of the preset arrival time difference model can be solved using N-1 groups of adjacent frame data. After the model parameters are solved, the preset arrival time difference model can be used to calculate any instantaneous arrival time difference estimate, and the mobile target can be positioned according to the arrival time difference, thereby effectively reducing the displacement effect caused by the asynchronous reception of the anchor point signal by the mobile target, improving the accuracy of the instantaneous arrival time difference estimation, and thus improving the accuracy of target positioning.

[0149] In some embodiments, for each group of adjacent frame data in the N-1 groups of adjacent frame data, the previous frame receiving timestamp of the first anchor point and the second anchor point contained in the adjacent frame data, the previous frame transmitting timestamp, the previous frame clock error, the next frame receiving timestamp, the next frame transmitting timestamp and the next frame clock error are substituted into a linear equation for calculating model parameters in a preset arrival time difference model to obtain a first linear equation;

[0150] Combine N-1 first linear equations to obtain a linear equation system;

[0151] The linear equations are solved using a statistical estimation algorithm to obtain estimated values ​​of the model parameters.

[0152] Specifically, assuming that the first anchor point is anchor point i, the second anchor point is anchor point j, and a pair of adjacent frame data includes the s-th frame data (previous frame data) and the s+1-th frame data (next frame data). The receiving timestamp recorded when the mobile target receives the time-division broadcast signal of the s-th frame from anchor point i and anchor point j (corresponding to the receiving timestamps in formula (17) respectively) is and ), the emission timestamps of anchor point i and anchor point j in the sth frame (corresponding to T in formula (17) respectively i (s) and T j (s) ) and the clock error between the local time and the global time of anchor point i and anchor point j at the initial time of the sth frame (corresponding to φ in formula (17) i (s) and ), and the receiving timestamp recorded when the mobile target receives the time-division broadcast signal of the s+1th frame from anchor point i and anchor point j (corresponding to the timestamps in formula (17) and ), the transmission timestamps of anchor point i and anchor point j in the s+1th frame (corresponding to T in formula (17) respectively i (s+1) and Tj (s+1) ) and the clock error between the local time and the global time of anchor point i and anchor point j at the initial time of the sth frame (corresponding to φ in formula (17) i (s+1) and ) is substituted into formula (17) to obtain the first linear equation. The first linear equation can be shown as follows:

[0153]

[0154] in, Represents the constant term in the calculated least squares model, which is a constant composed of observations. Represents the parameter coefficient, which is calculated using the obtained timestamp and clock error.

[0155] The N-1 first linear equations are combined to obtain a linear equation system. The linear equation system can be shown as follows:

[0156] b u；ij =A u；ij γ u；ij (19)

[0157] By solving the above linear equations using the weighted least squares algorithm, we can get the model parameter γ u；ij The estimated value of .

[0158] In some embodiments, the model parameter γ u；ij After obtaining the estimated value, the instantaneous arrival time difference (or distance difference) at the moment can be estimated according to the preset arrival time difference model, where the preset arrival time difference model is shown in formula (4).

[0159] In practical applications, it is necessary to consider the timestamp measurement error and the clock error estimation error of the anchor point's time-division broadcast signal to improve the accuracy of the instantaneous arrival time difference estimation and the accuracy of subsequent positioning.

[0160] In some embodiments, the linear equation used to calculate the model parameters contains combined noise, wherein the combined noise includes a timestamp measurement error and a clock error estimation error of the anchor point time-division broadcast signal.

[0161] In some embodiments, the linear equation used to calculate the model parameters in the preset arrival time difference model can be as follows:

[0162]

[0163] in, is the combined noise, including the timestamp measurement error and the clock error estimation error of the anchor point time-division broadcast signal. The timestamp superscript indicates the corresponding signal number, and the combined noise superscript indicates the linear equation program number.

[0164] For each set of adjacent frame data in the N-1 sets of adjacent frame data, the previous frame receiving timestamp, the previous frame transmitting timestamp, the previous frame clock error, the next frame receiving timestamp, the next frame transmitting timestamp and the next frame clock error of the first anchor point and the second anchor point contained in the adjacent frame data are substituted into formula (20) to obtain the second linear equation. The second linear equation can be shown as follows:

[0165]

[0166] Combining the N-1 second linear equations, another linear equation system is obtained. The linear equation system can be shown as follows:

[0167]

[0168] in,

[0169]

[0170] Among them, [b u；ij ] s and [η u；ij ] s Represents the column vector b u；ij and η u；ij The sth element of u；ij ] s,l Represents the matrix A u；ij The element in the sth row and lth column of .

[0171] By solving the above linear equations using the weighted least squares algorithm, we can get the model parameter γ u；ij The specific formula for the estimated value of can be shown as follows:

[0172]

[0173] The corresponding covariance matrix can be expressed as:

[0174]

[0175] Among them, the covariance matrix It can be calculated by formula (25).

[0176] In some embodiments, the model parameter γ u；ijAfter the estimated value is obtained, the instantaneous arrival time difference (or distance difference) estimation can be realized according to the preset arrival time difference model, where the preset arrival time difference model is shown in formula (4). The corresponding estimated value variance can be shown as follows:

[0177]

[0178] In this embodiment, the timestamp measurement error and the clock difference estimation error of the time-division broadcast signal of the anchor point are taken into account, so that the accuracy of the instantaneous arrival time difference estimation and the accuracy of subsequent positioning can be improved.

[0179] like Figure 4 As shown, Figure 4 It is a flow chart of an instantaneous arrival time difference estimation and target positioning method provided in an embodiment of the present application.

[0180] There are multiple anchor points in an asynchronous network. Each anchor point can broadcast signals to the outside periodically in a time-division manner. The time-division broadcast signal of each anchor point includes the transmission timestamp of the time-division broadcast signal transmitted by the anchor point, the location information of the anchor point, and the clock error between the local time of the anchor point and the global time.

[0181] The mobile target can asynchronously receive the time-division broadcast signal of each anchor point at different time points and locations, and record the receiving timestamp.

[0182] Determine whether N frames of data received by the mobile target are obtained.

[0183] In some embodiments, N is determined according to the value of the l-th order coefficient of the model parameter of the preset arrival time difference model.

[0184] The distance from the mobile target to each anchor point is a time-varying nonlinear function, and the nonlinear function can be expressed by a polynomial model in a short time through Taylor series expansion. The preset arrival time difference model is obtained based on the Taylor series expansion of the time-varying nonlinear function of the distance from the anchor point to the mobile target. The preset arrival time difference model contains unknown polynomial coefficients, which are the model parameters.

[0185] The l-order coefficient of the model parameter can be l = 0, 1, 2, ..., L-1. In order to ensure accurate characterization of the arrival time difference changes in a relatively short period of time under normal circumstances and improve the accuracy of the instantaneous arrival time difference estimation, this application limits the value range of the l-order coefficient of the model parameter to l = 0, 1, 2 through pre-calculation.

[0186] In some embodiments, the l-order coefficient of the model parameter can be selected as l = 0, 1, and L = 2. For the case of L = 2, at least two linear equations need to be combined to solve the model parameters, otherwise the model parameters will not have a unique solution. Therefore, in this application, it is necessary to determine the estimated value of the model parameter in the preset arrival time difference model based on at least 2 sets of adjacent frame data, and N can be equal to 3 at this time.

[0187] In some embodiments, the l-order coefficient of the model parameter can be selected as l = 0, 1, 2, and L = 3. For the case of L = 3, at least three linear equations need to be combined to solve the model parameters, otherwise the model parameters will not have a unique solution. Therefore, in this application, it is necessary to determine the estimated values ​​of the model parameters in the preset arrival time difference model based on at least 3 sets of adjacent frame data, and N can be equal to 4 at this time.

[0188] If not, continue to obtain the data received by the mobile target.

[0189] If so, determine N-1 groups of adjacent frame data from the obtained N frames of data. For each group of adjacent frame data in the N-1 groups of adjacent frame data, substitute the previous frame receiving timestamp, the previous frame transmitting timestamp, the previous frame clock error, the next frame receiving timestamp, the next frame transmitting timestamp and the next frame clock error of the first anchor point and the second anchor point contained in the adjacent frame data into the preset linear equation for calculating the model parameters, thereby obtaining a linear equation group including N-1 linear equations for calculating the model parameters after substituting the actual data.

[0190] Among them, the preset linear equation for calculating the model parameters is obtained based on the timing relationship between the local time of the first anchor point and the local time of the mobile target in adjacent frames and the timing relationship between the local time of the second anchor point and the local time of the mobile target.

[0191] That is, the preset linear equation for calculating the model parameters is constructed based on the frame error time difference (i.e., adjacent frame time difference) strategy, that is, the time difference is made between the sth frame of anchor point i and the s+1th frame of anchor point j, and the time difference is made between the s+1th frame of anchor point i and the sth frame of anchor point j.

[0192] The linear equations are solved using the weighted least squares algorithm to obtain the estimated values ​​of the model parameters.

[0193] After solving the estimated values ​​of the model parameters, the target time is substituted into the preset arrival time difference model to obtain the arrival time difference of the mobile target at the first anchor point and the second anchor point at the target time.

[0194] Multilateration positioning is performed on the mobile target according to multiple arrival time differences of the mobile target for multiple groups of first anchor points and second anchor points at a target time.

[0195] In an embodiment of the present application, a preset arrival time difference model is obtained by polynomial modeling of the time-varying arrival time difference, and the arrival time difference estimation problem is converted into a model parameter estimation problem. The model parameters of the preset arrival time difference model are solved using N-1 groups of adjacent frame data, where N is greater than or equal to 3. After the model parameters are solved, the preset arrival time difference model can be used to calculate any instantaneous arrival time difference estimate, and the mobile target can be positioned based on multiple groups of instantaneous arrival time difference estimates at the same time, thereby effectively reducing the displacement effect caused by the mobile target asynchronously receiving the anchor point signal, improving the accuracy of the instantaneous arrival time difference estimate, and thereby improving the accuracy of target positioning.

[0196] The above content describes the method provided by the present application. The following describes the device provided by the present application:

[0197] See also Figure 5 , is a structural diagram of an instantaneous arrival time difference estimation device provided in an embodiment of the present application.

[0198] like Figure 5 As shown, the device may include:

[0199] An acquisition unit 510 is configured to acquire N frames of data received by a mobile target, wherein each frame of data includes a time-division broadcast signal asynchronously received by the mobile target from at least two anchor points and a receiving timestamp, and N is greater than or equal to 3;

[0200] A first determining unit 520 is configured to determine N-1 groups of adjacent frame data from the N frames of data, each group of adjacent frame data at least including a previous frame receiving timestamp, a previous frame transmitting timestamp, a previous frame clock error, a next frame receiving timestamp, a next frame transmitting timestamp, and a next frame clock error of a first anchor point and a second anchor point;

[0201] A second determining unit 530 is used to determine an estimated value of a model parameter in a preset arrival time difference model according to the N-1 groups of adjacent frame data, wherein the preset arrival time difference model is obtained based on a Taylor series expansion of a time-varying nonlinear function of a distance from an anchor point to the moving target;

[0202] The estimation unit 540 is configured to substitute the target time into the preset arrival time difference model to obtain the arrival time difference of the mobile target at the first anchor point and the second anchor point at the target time.

[0203] In some embodiments, the time-division broadcast signal of each anchor point includes the location information of the anchor point, and the apparatus further includes a positioning unit, wherein the positioning unit is specifically configured to:

[0204] The mobile target is positioned according to the arrival time difference and the position information in the time-division broadcast signal of the first anchor point and the position information in the time-division broadcast signal of the second anchor point received by the mobile target at the target time.

[0205] In some embodiments, the positioning unit is specifically used to:

[0206] The mobile target is positioned according to a plurality of arrival time differences of the mobile target for a plurality of groups of first anchor points and second anchor points at the target time.

[0207] In some embodiments, the apparatus further includes a third determining unit, wherein the third determining unit is specifically configured to:

[0208] Performing Taylor series expansion on time-varying nonlinear functions of the distances from the mobile target to the first anchor point and the second anchor point under global time to obtain a first polynomial model and a second polynomial model, wherein the distances from the mobile target to the first anchor point and the second anchor point are represented by signal arrival time TOA;

[0209] Respectively converting the first polynomial model and the second polynomial model from global time to the local time of the mobile target to obtain a third polynomial model and a fourth polynomial model;

[0210] The preset arrival time difference model is obtained according to the difference between the third polynomial model and the fourth polynomial model, and the polynomial coefficients in the preset arrival time difference model are the model parameters.

[0211] In some embodiments, the apparatus further includes a fourth determining unit, wherein the fourth determining unit is specifically configured to:

[0212] For any adjacent frames, respectively determine a first relational expression between the local time of the first anchor point and the local time of the moving target and a second relational expression between the local time of the second anchor point and the local time of the moving target in a previous frame;

[0213] respectively determining, in a subsequent frame, a third relational expression between the local time of the first anchor point and the local time of the moving target and a fourth relational expression between the local time of the second anchor point and the local time of the moving target;

[0214] A linear equation for calculating the model parameters is determined based on the first relationship, the second relationship, the third relationship, the fourth relationship, and a Taylor series expansion of a time-varying nonlinear function of the distance from the mobile target to the first anchor point and the second anchor point at the local time of the mobile target.

[0215] In some embodiments, the second determining unit 530 is specifically configured to:

[0216] For each group of adjacent frame data in the N-1 groups of adjacent frame data, the previous frame reception timestamp, the previous frame transmission timestamp, the previous frame clock error, the next frame reception timestamp, the next frame transmission timestamp, and the next frame clock error of the first anchor point and the second anchor point contained in the adjacent frame data are substituted into the linear equation for calculating the model parameters obtained by the fourth determination unit to obtain a first linear equation;

[0217] Combining the first linear equations to obtain a linear equation system including N-1 first linear equations;

[0218] The linear equations are solved using a statistical estimation algorithm to obtain estimated values ​​of the model parameters.

[0219] In some embodiments, the linear equation obtained by the fourth determination unit for calculating the model parameters contains combined noise, and the combined noise includes a timestamp measurement error and a clock error estimation error of the anchor point time-division broadcast signal.

[0220] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0221] The present application embodiment also provides a hardware structure. Figure 6 , Figure 6 This is a structural diagram of an electronic device provided in an embodiment of the present application. Figure 6 As shown, the hardware structure may include: a processor and a machine-readable storage medium, the machine-readable storage medium storing machine-executable instructions that can be executed by the processor; the processor is used to execute the machine-executable instructions to implement the method disclosed in the above example of this application.

[0222] Based on the same application concept as the above method, an embodiment of the present application also provides a machine-readable storage medium, on which a number of computer instructions are stored. When the computer instructions are executed by a processor, the method disclosed in the above example of the present application can be implemented.

[0223] Exemplarily, the above-mentioned machine-readable storage medium can be any electronic, magnetic, optical or other physical storage device that can contain or store information, such as executable instructions, data, etc. For example, the machine-readable storage medium can be: RAM (Random Access Memory), volatile memory, non-volatile memory, flash memory, storage drive (such as hard disk drive), solid state drive, any type of storage disk (such as optical disk, DVD, etc.), or similar storage medium, or a combination thereof.

[0224] It should be noted that, in this article, relational terms such as target and target are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0225] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for estimating instantaneous time difference of arrival, characterized in that: The method includes: Acquire N frames of data received by the mobile target, wherein each frame of data includes a time-division broadcast signal and a receiving timestamp asynchronously received by the mobile target from at least two anchor points, and N is greater than or equal to 3; Determine N-1 groups of adjacent frame data from the N frames of data, each group of adjacent frame data at least including a previous frame receiving timestamp, a previous frame transmitting timestamp, a previous frame clock error, a next frame receiving timestamp, a next frame transmitting timestamp, and a next frame clock error of a first anchor point and a second anchor point; Determine estimated values ​​of model parameters in a preset arrival time difference model based on the N-1 groups of adjacent frame data, wherein the preset arrival time difference model is obtained based on a Taylor series expansion of a time-varying nonlinear function of a distance from an anchor point to the moving target; Substitute the target time into the preset arrival time difference model to obtain the arrival time difference of the mobile target at the first anchor point and the second anchor point at the target time.

2. The method according to claim 1, characterized in that The time-division broadcast signal of each anchor point includes the location information of the anchor point, and the method further includes: The mobile target is positioned according to the arrival time difference and the position information in the time-division broadcast signal of the first anchor point and the position information in the time-division broadcast signal of the second anchor point received by the mobile target at the target time.

3. The method according to claim 1, characterized in that The method further comprises: The mobile target is positioned according to a plurality of arrival time differences of the mobile target for a plurality of groups of first anchor points and second anchor points at the target time.

4. The method according to claim 1, characterized in that: The method further comprises: Performing Taylor series expansion on time-varying nonlinear functions of the distances from the mobile target to the first anchor point and the second anchor point under global time to obtain a first polynomial model and a second polynomial model, wherein the distances from the mobile target to the first anchor point and the second anchor point are represented by signal arrival time TOA; Respectively converting the first polynomial model and the second polynomial model from global time to the local time of the mobile target to obtain a third polynomial model and a fourth polynomial model; The preset arrival time difference model is obtained according to the difference between the third polynomial model and the fourth polynomial model, and the polynomial coefficients in the preset arrival time difference model are the model parameters.

5. The method according to claim 1, characterized in that The method further comprises: For any adjacent frames, respectively determine a first relational expression between the local time of the first anchor point and the local time of the moving target and a second relational expression between the local time of the second anchor point and the local time of the moving target in a previous frame; respectively determining, in a subsequent frame, a third relational expression between the local time of the first anchor point and the local time of the moving target and a fourth relational expression between the local time of the second anchor point and the local time of the moving target; A linear equation for calculating the model parameters is determined based on the first relationship, the second relationship, the third relationship, the fourth relationship, and a Taylor series expansion of a time-varying nonlinear function of the distance from the mobile target to the first anchor point and the second anchor point at the local time of the mobile target.

6. The method according to claim 5, characterized in that Determining estimated values ​​of model parameters in a preset arrival time difference model according to the N-1 groups of adjacent frame data includes: For each group of adjacent frame data in the N-1 groups of adjacent frame data, substitute the previous frame receiving timestamp, the previous frame transmitting timestamp, the previous frame clock error, the next frame receiving timestamp, the next frame transmitting timestamp and the next frame clock error of the first anchor point and the second anchor point contained in the adjacent frame data into the linear equation to obtain a first linear equation; Combining the first linear equations to obtain a linear equation system including N-1 first linear equations; The linear equations are solved using a statistical estimation algorithm to obtain estimated values ​​of the model parameters.

7. The method according to claim 5, characterized in that The linear equation used to calculate the model parameters contains combined noise, and the combined noise includes a timestamp measurement error and a clock error estimation error of the anchor point time-division broadcast signal.

8. An instantaneous arrival time difference estimation device, characterized in that: The device includes: An acquisition unit, configured to acquire N frames of data received by the mobile target, wherein each frame of data includes a time-division broadcast signal asynchronously received by the mobile target from at least two anchor points and a receiving timestamp, and N is greater than or equal to 3; A first determining unit is used to determine N-1 groups of adjacent frame data from the N frames of data, each group of adjacent frame data at least including a previous frame receiving timestamp, a previous frame transmitting timestamp, a previous frame clock error, a next frame receiving timestamp, a next frame transmitting timestamp and a next frame clock error of a first anchor point and a second anchor point; A second determination unit is used to determine an estimated value of a model parameter in a preset arrival time difference model according to the N-1 groups of adjacent frame data, wherein the preset arrival time difference model is obtained based on a Taylor series expansion of a time-varying nonlinear function of a distance from an anchor point to the moving target; The estimation unit is used to substitute the target time into the preset arrival time difference model to obtain the arrival time difference of the mobile target at the first anchor point and the second anchor point at the target time.

9. An electronic device, characterized in that: The invention comprises a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor is used to execute the machine executable instructions to implement the method according to any one of claims 1 to 7.

10. A machine-readable storage medium, characterized in that: The machine-readable storage medium stores machine-executable instructions, and when the machine-executable instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

11. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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