Target tracking method, apparatus, device, and storage medium based on single-bit quantization

Abstract

This application discloses a target tracking method, apparatus, device, and storage medium based on single-bit quantization. The method includes acquiring echo data of each radar node in a multi-radar node system for a target; performing single-bit quantization on each echo data to obtain single-bit data; estimating the target's range information and signal angle of arrival (AOA) relative to each radar node based on each single-bit data; determining the target's position information relative to each radar node based on each range information and AOA; and fusing the position information to obtain the target's tracking point. This application achieves high-precision detection and tracking of marine monitoring targets by employing single-bit quantization technology and multi-base point fusion processing, significantly improving data processing speed and anti-interference capability, while reducing the demand for storage and transmission resources, and ensuring reliability and real-time performance in complex environments.

Description

Technical Field

[0001] This application relates to the field of radar signal processing technology, and in particular to a target tracking method, apparatus, device and storage medium based on single-bit quantization. Background Technology

[0002] In modern maritime surveillance and coastal patrol, ships are the primary targets, and their precise positioning and tracking are crucial for maritime traffic safety, coastal defense monitoring, and marine resource management. Currently, single-radar-node systems are commonly used in modern maritime surveillance and coastal patrol for target detection and tracking. However, existing single-radar-node systems face challenges in handling complex marine environments and multi-target scenarios, including insufficient resolution and limited data processing capabilities, making it difficult to meet the demands for high precision and real-time performance. Furthermore, traditional radar systems typically require significant storage and transmission bandwidth to process high-bit-rate signal data, limiting their application in resource-constrained environments. The difficulty in achieving accurate point cloud imaging and continuous track tracking of targets such as ships, especially under adverse weather and low visibility conditions, significantly degrades the reliability and accuracy of single-radar-node systems.

[0003] Therefore, existing technologies still need to be improved and enhanced. Summary of the Invention

[0004] The technical problem to be solved by this application is to provide a target tracking method, apparatus, device and storage medium based on single-bit quantization, which addresses the shortcomings of the existing technology.

[0005] To address the aforementioned technical problems, the first aspect of this application provides a target tracking method based on single-bit quantization, wherein the target tracking method based on single-bit quantization specifically includes:

[0006] Acquire echo data of each radar node in a multi-radar node system for the target;

[0007] Each echo data is quantized into a single bit to obtain the single-bit data of each radar node;

[0008] The distance information of the target relative to each radar node is estimated based on the single-bit data of each radar node, and the signal angle of arrival of each radar node is estimated based on the single-bit data of each radar node.

[0009] Based on the distance information of the target relative to each radar node and the signal angle of arrival corresponding to each radar node, the position information of the target relative to each radar node is determined.

[0010] The target's position information relative to each radar node is fused to obtain the target's tracking point, and the target's tracking trajectory is formed based on the tracking point.

[0011] The target tracking method based on single-bit quantization is described in which the radar nodes in the multi-radar node system are arranged at intervals, and adjacent radar nodes are geographically separated.

[0012] The target tracking method based on single-bit quantization, wherein the single-bit quantization process is as follows:

[0013]

[0014] κ=B / T

[0015] λ = 1 / f c

[0016]

[0017] Among them, s one (t) represents a single bit of data, s IF (t) represents the echo data, real{g} represents the real part of the complex number, imag{g} represents the imaginary part of the complex number, sign(·) represents the sign operation, and A0 represents the signal amplitude. f represents the phase of the echo data. a The frequency of the echo data is represented by t, and the time-domain sampling is represented by t. κ represents the frequency modulation slope, B represents the signal frequency modulation bandwidth, T represents the signal frequency modulation period, c represents the speed of light, and f c Let R represent the carrier frequency, λ represent the carrier wavelength, mod(·) represents the integer operation, R represent the distance information, v represent the speed information, and f represent the velocity information. D f represents the velocity frequency. R Indicates distance frequency.

[0018] The target tracking method based on single-bit quantization, wherein estimating the distance information of the target relative to each radar node based on single-bit data from each radar node specifically includes:

[0019] T-point Fast Fourier Transform is performed on the fast time dimension of the single-bit data of each radar node to obtain the range frequency;

[0020] The distance information of the target relative to each radar node is calculated based on the distance frequency.

[0021] The target tracking method based on single-bit quantization, wherein fusing the target's position information relative to each radar node to obtain the target's tracking point specifically includes:

[0022] In a multi-radar node system, a radar node is selected as the target radar node, and the coordinate system of the selected target radar node is used as the target coordinate system.

[0023] The target's position information relative to each of the other radar nodes is transformed to the target coordinate system to obtain the transformed position information of the target relative to each of the other radar nodes;

[0024] The target's position information relative to the target coordinate radar and the target's transformed position information relative to each of the other radar nodes are fused to obtain the target's tracking point.

[0025] The target tracking method based on single-bit quantization, wherein at least one specific radar node in the multi-radar node system is equipped with a coprime array, the coprime array comprising a first subarray, a second subarray, and a third subarray arranged sequentially in a straight line; the first subarray comprises N array elements with an element spacing of Ld; the second subarray comprises... The first subarray consists of 1 array element with an element spacing of Md; the third subarray consists of 1 L array element with an element spacing of Nd; the adjacent elements of the first and second subarrays overlap, and the adjacent elements of the second and third subarrays overlap, wherein N, M, and L are pairwise coprime.

[0026] The target tracking method based on single-bit quantization further includes:

[0027] P-point Fast Fourier Transform is performed on the slow time dimension of the single-bit data of each radar node to obtain the velocity frequency.

[0028] Calculate the target's velocity information relative to each radar node based on the velocity frequency;

[0029] The velocity information of each radar node is fused to obtain the velocity information corresponding to the tracking point, and the velocity information is marked on the tracking point.

[0030] A second aspect of this application provides a target tracking device based on single-bit quantization, wherein the target tracking device based on single-bit quantization specifically includes:

[0031] The acquisition module is used to acquire the echo data of each radar node in the multi-radar node system for the target;

[0032] The quantization module is used to perform single-bit quantization on each echo data to obtain single-bit data for each radar node.

[0033] The estimation module is used to estimate the distance information of the target relative to each radar node based on the single-bit data of each radar node, and to estimate the signal angle of arrival of each radar node based on the single-bit data of each radar node.

[0034] The determination module is used to determine the position information of the target relative to each radar node based on the distance information of the target relative to each radar node and the signal angle of arrival corresponding to each radar node;

[0035] The fusion module is used to fuse the target's position information relative to each radar node to obtain the target's tracking point, and to form the target's tracking trajectory based on the tracking point.

[0036] A third aspect of this application provides a computer-readable storage medium storing one or more programs that can be executed by one or more processors to implement the steps in the target tracking method based on single-bit quantization as described above.

[0037] A fourth aspect of this application provides a terminal device, which includes: a processor and a memory;

[0038] The memory stores a computer-readable program that can be executed by the processor;

[0039] When the processor executes the computer-readable program, it implements the steps in any of the target tracking methods based on single-bit quantization described above.

[0040] Beneficial effects:

[0041] 1. This application simplifies radar echo signals into single-bit data through single-bit quantization. While maintaining the accuracy of signal processing, it can significantly reduce the amount of data, reduce the need for data storage and transmission, improve data processing speed, and make real-time monitoring and processing possible.

[0042] 2. This application quantizes radar echo signals using single-bit quantization, which also improves the system's anti-interference capability, making the radar system more stable and reliable in complex marine environments.

[0043] 3. This application employs a multi-radar node system to track targets, and fuses the position information and signal angle of arrival (AOA) of each radar node to determine the target's tracking point, thereby generating more accurate target point cloud images and trajectory information. This not only enhances the accuracy of target detection and tracking stability, especially in complex or dynamically changing environments, but also strengthens the system's redundancy and robustness, maintaining monitoring continuity and accuracy even in the event of partial node failure. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1A flowchart of a target tracking method based on single-bit quantization provided in an embodiment of this application.

[0046] Figure 2 This is a schematic diagram of a coprime matrix provided in an embodiment of this application.

[0047] Figure 3 A flowchart illustrating the signal angle of arrival estimation method provided in this application embodiment.

[0048] Figure 4 This is a comparison chart of monostatic radar track 1 (left is multi-bit, right is single-bit).

[0049] Figure 5 This is a comparison chart of monostatic radar tracks 2 (left is multi-bit, right is single-bit).

[0050] Figure 6 This is a comparison chart of monostatic radar tracks 3 (left is multi-bit, right is single-bit).

[0051] Figure 7 This is a comparison chart of bistatic radar track 1 (left is multi-bit, right is single-bit).

[0052] Figure 8 This is a schematic diagram of a target tracking device based on single-bit quantization provided in an embodiment of this application.

[0053] Figure 9 A schematic block diagram of the terminal device provided in the embodiments of this application. Detailed Implementation

[0054] This application provides a target tracking method, apparatus, device, and storage medium based on single-bit quantization. To make the objectives, technical solutions, and effects of this application clearer and more explicit, the following detailed description is provided with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit this application.

[0055] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0056] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0057] It should be understood that the sequence number and size of each step in this embodiment do not imply the order of execution. The execution order of each process is determined by its function and internal logic, and should not constitute any limitation on the implementation process of this application embodiment.

[0058] The application content will be further explained below with reference to the accompanying drawings and the description of the embodiments.

[0059] This embodiment provides a target tracking method based on single-bit quantization, such as Figure 1 As shown, the method includes:

[0060] S10. Acquire the echo data of each radar node in the multi-radar node system for the target.

[0061] Specifically, a multi-radar node system includes at least two radar nodes deployed at different locations (e.g., along a coastline), meaning that at least two radar nodes are spaced apart and adjacent radar nodes are geographically separated. Furthermore, the radar nodes in a multi-radar node system work collaboratively to achieve more comprehensive detection coverage, thereby improving the detection range and angular resolution of targets (e.g., ship targets).

[0062] Each radar node periodically transmits a chirp signal at a pulse repetition interval (PRI). The chirp signal is a frequency-modulated continuous wave (FMCW), which is a complex sine wave whose frequency increases linearly with time.

[0063]

[0064] κ=B / T

[0065] Among them, s t (t) represents a complex sinusoidal signal, f c A0 represents the carrier frequency, and A0 represents the signal amplitude. Let B represent the initial phase, B represent the signal frequency modulation bandwidth, T represent the frequency modulation period, κ represent the frequency modulation slope, and t represent the time-domain sampling. It represents the imaginary unit.

[0066] Each radar node receives the echo signal reflected from the target, which has a corresponding time delay and a certain attenuation. For a target a with a radial distance of R and a velocity of v, its echo signal is:

[0067]

[0068] τ a =(2(R+vt)) / c

[0069] Among them, s r (t) represents the echo signal, c represents the speed of light, and τ a Indicates an intermediate variable.

[0070] Furthermore, after acquiring the echo signal, the received echo signal can be mixed to obtain an intermediate frequency signal, which in turn yields the echo data. The echo data can be represented as:

[0071]

[0072] κ=B / T

[0073] λ = 1 / f c

[0074] Where A0 represents the signal amplitude. f represents the phase of the echo data. a The frequency of the echo data is represented by t, and the time-domain sampling is represented by t. κ represents the frequency modulation slope, B represents the signal frequency modulation bandwidth, T represents the signal frequency modulation period, c represents the speed of light, and f cLet R represent the carrier frequency, λ represent the carrier wavelength, mod(·) represents the integer operation, R represent the distance information, v represent the speed information, and f represent the velocity information. D f represents the velocity frequency. R Indicates distance frequency.

[0075] In one implementation, the multi-radar node system includes at least one specific radar node, which is equipped with a coprime array. Specifically, as shown... Figure 2 and Figure 3 As shown, the first subarray is represented by "△", the second subarray by "○", and the third subarray by "◇". The first subarray includes N array elements with an element spacing of Ld; the second subarray includes... The first subarray consists of three subarrays, each with an element spacing of Md. The third subarray consists of L elements with an element spacing of Nd, where N, M, and L are pairwise coprime. The first, second, and third subarrays are located on a straight line. The second subarray follows the first subarray, and the last element of the first subarray overlaps with the first element of the second subarray, meaning that adjacent elements of the first and second subarrays overlap. Similarly, the third subarray follows the second subarray, and the last element of the second subarray overlaps with the first element of the third subarray, meaning that adjacent elements of the second and third subarrays overlap.

[0076] This application embodiment strengthens the coprime constraint between subarrays by connecting three subarrays end to end to form a triple extended coprime array, which greatly reduces the probability of overlapping fuzzy angle sets. This effectively avoids directional ambiguity when estimating the directions of multiple signal sources, thereby improving DoA estimation performance and thus improving the target detection and positioning accuracy of millimeter-wave radar systems under single snapshot conditions.

[0077] Furthermore, the aperture of the first subarray is close to the spatial aperture of the third subarray, and the aperture of the second subarray is close to the aperture of the first subarray (for example, the difference between the aperture of the second subarray and the aperture of the first subarray is within a preset range). In this way, compared with an array of two subarrays, the additional third subarray does not increase the risk of DoA estimation fuzziness leakage, and the probability of fuzzy angles of the three subarrays coinciding is lower than that of a traditional coprime array with only two subarrays, thereby greatly reducing the probability of fuzzy angle set overlap.

[0078] like Figure 2 As shown, the positions of the elements of the coprime array are:

[0079]

[0080] Where W = N + M * +L-2 represents the total number of array elements; P represents a coprime array, p i This represents the element at position i in P. Indicates the starting element position of the second subarray. This indicates the starting element position of the third subarray.

[0081] Furthermore, for the coprime array provided in the embodiments of this application, when there are K far-field incoherent sources from different angles θ1, θ2, ..., θ K Upon arrival at the array, the received signal of a single snapshot array is modeled as follows:

[0082]

[0083] Where y represents the array received signal of the coprime array, and A p =[a(θ1),a(θ2),...,a(θ)] K [)] represents the array manifold matrix of coprime linear arrays P. The steering vector representing the k-th source, where λ is the wavelength; x = [x1, x2, ..., x...]. K [ ] represents the signal amplitude, n represents the Gaussian white noise vector, p i Let represent the element spacing between the i-th element and the initial element, where i = 1, 2, ..., W-1. Therefore, the sample covariance matrix of the signals received by the T snapshot arrays can be represented as:

[0084]

[0085] Where y represents the array received signal of the coprime array, y H Represents the conjugate of y, n H Indicates the conjugate of n. Represents the autocorrelation matrix of the signal; This represents the sum of the cross-correlation matrix between different signals and the signal-noise cross-correlation matrix; Represents the noise autocorrelation matrix. This represents the received signal from the k-th source. express . conjugate.

[0086] Furthermore, in the coprime array provided in this embodiment, since the three subarrays of the triple extended coprime array are pairwise coprime, the fuzzy angles of the same angle do not coincide between any two subarrays. Therefore, for any angle θ... k The fuzzy angle set of subarrays i and j and They will not overlap, that is:

[0087]

[0088] Furthermore, since the fuzzy positions of the angle on the sparse uniform linear array are uniformly distributed in the frequency domain, for any angle θ... k If θk The set of fuzzy angles in the i-th subarray and θ r If there are two overlapping fuzzy angles θ1 and θ2 in the j-th subarray, then for θ1, there is a common fuzzy angle θ2 in both subarrays, and for any angle θ... k The fuzzy angle set of subarrays i and j and They will not overlap. Therefore, for any two directions, the sets of fuzzy angles generated by different subarrays will have at most one overlapping angle, i.e.

[0089]

[0090] Furthermore, if two directions have overlapping fuzzy angles in two subarrays, then those overlapping angles will not overlap with fuzzy angles in the remaining subarrays:

[0091]

[0092] in,

[0093] Therefore, compared to a coprime array consisting of only two subarrays, the triple extended coprime array, composed of three sets of coprime subarrays, significantly reduces the probability of overlapping ambiguity angle sets between multiple subarrays. This enables the triple extended coprime array to effectively avoid directional ambiguity when estimating the directions of multiple signal sources, thus exhibiting higher direction estimation accuracy in practical applications.

[0094] The coprime array proposed in this application is based on direct DoA processing of single-shot signals, without relying on other sparse arrays based on multi-shot virtual array elements. Thus, the coprime array directly processes physical array elements, and the data dimension is smaller than that of virtual array elements. Furthermore, the coprime array can be directly used for single-shot DoA estimation, which is more in line with the requirements of actual engineering (vehicle-mounted point cloud imaging processes two-dimensional compressed single-shot high signal-to-noise ratio signals).

[0095] Furthermore, it should be noted that each radar node in the multi-radar node system of this application embodiment can adopt an existing radar array, such as a coprime array composed of two subarrays, or an extended coprime array, etc.

[0096] S20. Perform single-bit quantization on each echo data to obtain single-bit data for each radar node.

[0097] Specifically, single-bit quantization converts echo data into single-bit information to reduce the data volume. In other words, the data volume of a single bit of data is less than that of the echo data. The single-bit quantization process can be represented as follows:

[0098]

[0099] Among them, s one (t) represents a single bit of data, s IF (t) represents the echo data, real{g} represents the real part of the complex number, imag{g} represents the imaginary part of the complex number, sign(·) represents the sign operation, and t represents time-domain sampling.

[0100] S30. Estimate the distance information of the target relative to each radar node based on the single-bit data of each radar node, and calculate the signal angle of arrival of each radar node based on the single-bit data of each radar node.

[0101] Specifically, the frequency f of the echo data a It includes the Doppler frequency caused by distance and velocity, with the velocity-induced Doppler frequency f. D Much smaller than the distance frequency f R The frequency resolution is even smaller than that of time-domain sampling, making it difficult to estimate velocity information from the fast time dimension. Therefore, it is possible to obtain f by performing a Fast Fourier Transform (FFT) on all sampling points. R This allows us to obtain the distance information of the target:

[0102]

[0103] Although the Doppler frequency f caused by velocity D The distance is very small, but because there is a tiny distance change between each pulse, it can be measured by the phase change between each pulse. That is, f can be obtained by performing an FFT between pulses. D The target's velocity information can be obtained by reverse calculation using the formula:

[0104]

[0105] Based on this, in one implementation, estimating the target's distance information relative to each radar node based on single-bit data from each radar node specifically includes:

[0106] T-point Fast Fourier Transform is performed on the fast time dimension of the single-bit data of each radar node to obtain the range frequency;

[0107] The distance information of the target relative to each radar node is calculated based on the distance frequency.

[0108] Specifically, in s one (t) Perform T-point FFT in fast time dimension:

[0109]

[0110] Among them, S range(f) denotes the fast time dimension Fast Fourier Transform, where f represents the fast time dimension.

[0111] After performing a T-point FFT in the fast time dimension, the range frequency can be obtained. Then, based on the relationship between the range frequency and the range information, the range information of the target relative to each radar node can be calculated.

[0112] Furthermore, after obtaining single-bit data, a P-point FFT can be performed in the slow time dimension to determine the speed information. The P-point FFT in the slow time dimension can be represented as:

[0113]

[0114] Among them, S doppler (f,p) represents a P-point Fast Fourier Transform performed in the slow time dimension, where p represents the slow time dimension.

[0115] The velocity-induced Doppler frequency f can be obtained by performing a P-point FFT in a slow time dimension. D Then, based on the velocity information and the Doppler frequency f caused by the velocity... D The relationship can be used to calculate speed information.

[0116] Perform unit-mean constant false alarm rate (CFAR) detection on it. For the (i,j)th cell to be detected, select the set of reference cells around it. Calculate the average energy of the reference cell as an estimate of the clutter power:

[0117]

[0118] Where, N ref This represents the number of reference units, where (m,n) represents the coordinates of the reference units.

[0119] Set P F The threshold factor is expressed as the false alarm rate:

[0120]

[0121] The threshold value of the unit under test is:

[0122] T(i,j)=γC(i,j)

[0123] Traverse S doppler All the units to be detected are compared with the threshold T to perform target detection. According to the Neyman-Pearson criterion, when the amplitude of the detected unit is greater than the threshold, it indicates that the target exists in the detected unit. The data of all elements in the detected unit are extracted into a single snapshot spatial vector for subsequent DoA estimation.

[0124] In one implementation, the estimation process for the signal angle of arrival can be as follows:

[0125] Consider the existence of K far-field incoherent sources from different angles θ1, θ2, ..., θ K Upon arrival at the array, the array receives the signal and models it as follows:

[0126] y = Ax + n

[0127] Where y represents the array received signal, A = [a(θ1), a(θ2), ..., a(θ)] K ] represents the array manifold matrix, Let x represent the steering vector of the k-th source, and λ represent the wavelength; x = [x1, x2, ..., x...]. K ] represents the signal amplitude vector; n represents the white Gaussian noise vector.

[0128] The sample covariance matrix of the signals received by the T snapshot arrays is:

[0129]

[0130] in, Let represent a diagonal matrix containing K principal eigenvalues, and It includes the remaining eigenvalues. Accordingly, and These are designated to represent the estimated signal subspace and noise subspace, respectively.

[0131] Of course, in practical applications, when the coprime array is as described above, the covariance matrix of the coprime array under a single snapshot is:

[0132]

[0133]

[0134] Among them, y H Represents the conjugate of y, n H Indicates the conjugate of n. Represents the autocorrelation matrix of the signal; This represents the sum of the cross-correlation matrix between different signals and the signal-noise cross-correlation matrix; Represents the noise autocorrelation matrix. This represents the received signal from the k-th source. express conjugate, p i This represents the element spacing between the i-th element and the starting element, where i = 1, 2, ..., W-1.

[0135] When using the IAA (Iterative Adaptive Approach) for DoA estimation, we first assume the interference matrix of the k-th source is:

[0136] Q k =E{(ya(θ)} k )x k )(ya(θ k )x k ) H}

[0137] =yy H -|x k | 2 a(θ k )a(θ k ) H k = 1, 2, ..., K

[0138] Where E{·} represents the mathematical expectation.

[0139] Secondly, construct about Weighted least squares cost function:

[0140]

[0141] Furthermore, the closed-form solution obtained by minimizing the least squares cost function is:

[0142]

[0143] Then, substituting the interference matrix of the k-th source into the closed-form solution, the closed-form solution can be simplified to:

[0144]

[0145] in, It represents the inverse of the covariance matrix of the received signal from the array.

[0146] To obtain DoA estimates within a certain angular range, a model is constructed for the proposed array. Complete guiding vector matrix Guide vector matrix It can be a diagonal matrix with the steering vector of the signal source as its diagonal elements, i.e., the steering vector matrix. It can be

[0147]

[0148] Then, based on the guiding vector matrix The relationship between the estimated signal amplitude, signal amplitude, covariance matrix, and steering vector matrix is ​​as follows:

[0149]

[0150] Estimating the covariance matrix using the power spectrum and the complete steering vector matrix:

[0151]

[0152] in, The power spectrum is a diagonal matrix, with the main diagonal elements consisting of |x|. 2 Composition. Initial power spectrum of the received signal. Estimation using CBF:

[0153]

[0154] in, Indicates the initial power spectrum. Represents the guiding vector matrix . conjugate.

[0155] Furthermore, after estimating the signal amplitude, the covariance matrix is ​​reconstructed based on the estimated signal amplitude. Then, the signal amplitude is recalculated based on the reconstructed covariance matrix until the final signal amplitude reaches the preset termination condition. The termination condition is pre-set and can be a preset number of estimations or a condition where the difference between two adjacent estimated signal amplitudes is less than a preset difference threshold. In this embodiment, the termination condition is that the difference between two adjacent estimated signal amplitudes is less than the preset difference threshold; that is, the termination condition is:

[0156]

[0157] Where, x (t) Let x represent the signal amplitude estimated in the t-th estimation. (t-1) ε represents the signal amplitude estimated in the t-1th iteration, and ε represents the preset error threshold.

[0158] For example, the process of estimating the signal angle of arrival can be shown in Table 1.

[0159] Table 1. Single-shot DoA estimation process

[0160]

[0161]

[0162] S40. Based on the distance information of the target relative to each radar node and the signal angle of arrival corresponding to each radar node, determine the position information of the target relative to each radar node.

[0163] Specifically, the position information refers to the target's coordinates within the coordinate system of the radar node. After acquiring the range information and signal angle of arrival, the target's position relative to each radar node can be calculated using the radar node's location as the origin.

[0164] S50: The target's position information relative to each radar node is fused to obtain the target's tracking point, and the target's tracking trajectory is formed based on the tracking point.

[0165] Specifically, the position information of the tracking point is obtained by fusing the position information of each radar node. The coordinate system of the tracking point can be the coordinate system of one of the multiple radar nodes, or it can be a tracking coordinate system different from the coordinate systems of each radar node. In this embodiment, the coordinate system of the target radar node among the multiple radar nodes is used as the coordinate system of the tracking point. That is, the position information of each radar node (excluding the target radar node) can be transformed into the coordinate system of the target radar node, and then the position information of all radar nodes in the target radar node's coordinate system is fused to obtain the coordinate information of the tracking point.

[0166] For example, the fusion of the target's position information relative to each radar node to obtain the target's tracking point specifically includes:

[0167] In a multi-radar node system, a radar node is selected as the target radar node, and the coordinate system of the selected target radar node is used as the target coordinate system.

[0168] The target's position information relative to each of the other radar nodes is transformed to the target coordinate system to obtain the transformed position information of the target relative to each of the other radar nodes;

[0169] The target's position information relative to the target coordinate radar and the target's transformed position information relative to each of the other radar nodes are fused to obtain the target's tracking point.

[0170] Specifically, the target radar node can be any one of the radar nodes in a multi-radar node system. After acquiring the target radar node, the position information of the other radar nodes is transformed to the target coordinate system. For example, the radar nodes in the multi-radar node system include a left radar node and a right radar node. The horizontal displacement of the right radar node relative to the left radar node is (Δx, Δy), and the deflection angle of the right radar node relative to the left radar node is Δθ. Taking the left radar node and the right radar node as the coordinate origins, the polar coordinates of the point cloud of the left radar node and the polar coordinates of the point cloud of the right radar node are respectively expressed as:

[0171]

[0172] Among them, RL θ represents the distance information of the target relative to the left radar node. L R represents the angle of arrival of the target relative to the left radar node. R θ represents the distance information of the target relative to the left radar node. R x represents the angle of arrival of the target relative to the left radar node. L Represents the coordinates in the x-direction, y L Represents the coordinates in the y-direction, x R Represents the coordinates in the x-direction, y R This represents the coordinate in the y-direction.

[0173] Therefore, when the coordinate system of the left radar node is taken as the target coordinate system, the transformed position information obtained after transforming the position information corresponding to the right radar node to the target coordinate system can be:

[0174]

[0175] Where, x′ R Represents the transformed coordinates in the x-direction, y-direction... R This represents the transformed coordinates in the y-direction.

[0176] Furthermore, when fusing the target's position information relative to the target coordinate radar and the target's transformed position information relative to each of the other radar nodes, a weighted method, an average method, or random selection can be used. In this embodiment, an average method is used for fusion. For example, after obtaining the transformed position information corresponding to the right radar node and the position information of the left radar node as in the example above, the average value of the transformed position information corresponding to the right radar node and the position information of the left radar node is calculated to obtain the position information of the target's tracking point, wherein the position information of the target's tracking point is:

[0177]

[0178] in, This represents the back coordinate of the tracking point in the x-direction. This represents the back coordinate of the tracking point in the y-direction.

[0179] Furthermore, after acquiring the tracking point, velocity information can be marked on the tracking point. In other words, the method also includes:

[0180] P-point Fast Fourier Transform is performed on the slow time dimension of the single-bit data of each radar node to obtain the velocity frequency.

[0181] Calculate the target's velocity information relative to each radar node based on the velocity frequency;

[0182] The velocity information of each radar node is fused to obtain the velocity information corresponding to the tracking point, and the velocity information is marked on the tracking point.

[0183] Specifically, the process for determining the speed information can be referred to the above description. Furthermore, the speed information fusion method can be the same as the location information fusion method, both using an average value method, or the speed information fusion method can be different from the location information fusion method, such as using a random selection method for speed information and a weighted method for location information. In this embodiment, both the speed information fusion method and the location information fusion method use an average value method.

[0184] Furthermore, to enable the target tracking method based on single-bit quantization provided in this application to effectively monitor and track target ships, a specific example is given here.

[0185] In this specific example, a bistatic radar system consisting of two TI AWR2944 radars was deployed on the shore. The horizontal spacing between the two radar nodes in the bistatic radar system was set to 7 meters. The target ship's movement range was set to be between 5 and 50 meters offshore. Both radar nodes used linear frequency modulated continuous wave (LFMCW) signals with a bandwidth of 384 MHz and a carrier frequency of 77 GHz, equipped with a 12-channel array. Data was sampled using a 16-bit analog-to-digital converter (ADC), and single-bit data was extracted by retaining the first bit of each sampling point. Experiments were conducted under the above conditions, with only the left radar node enabled and with both the left and right radar nodes enabled simultaneously. Specifically:

[0186] (1) Place an unmanned boat (i.e., the target vessel) on the lake surface and remotely control the unmanned boat to navigate on the lake surface according to the predetermined trajectory via wireless signal;

[0187] (2) Three experiments were conducted with only the left radar system activated, and one experiment was conducted simultaneously with the left radar system activated. In each experiment, high-bit echo data was collected and quantized into single-bit data. The single-bit and high-bit radar positioning algorithms were run respectively to generate the unmanned vessel's track map. The comparison map of the single-base track 1 is shown below. Figure 4 As shown, the comparison diagram of single-base track 2 is as follows: Figure 5 As shown, the comparison diagram of single-base track 3 is as follows: Figure 6 As shown, the comparison diagram of the bistatic track 1 is as follows: Figure 7 As shown;

[0188] (3) Calculate the relative angle difference and position difference between the single-bit positioning algorithm and the multi-bit positioning algorithm for each experiment to obtain the experimental results shown in Table 2. The formulas for calculating the angle error and position error are as follows:

[0189]

[0190] Table 2 Experimental Results (Single Bit vs. 16 Bit):

[0191]

[0192]

[0193] In addition, track fusion of bistatic radar improves the detection range and reliability of target ships, increasing the detection range by about 2 / 3.

[0194] Based on the above-described target tracking method based on single-bit quantization, this embodiment provides a target tracking device based on single-bit quantization, such as... Figure 8 As shown, the target tracking device based on single-bit quantization specifically includes:

[0195] The acquisition module 100 is used to acquire the echo data of each radar node in the multi-radar node system for the target;

[0196] The quantization module 200 is used to perform single-bit quantization on each echo data to obtain single-bit data of each radar node.

[0197] The estimation module 300 is used to estimate the distance information of the target relative to each radar node based on the single-bit data of each radar node, and to estimate the signal angle of arrival of each radar node based on the single-bit data of each radar node.

[0198] The determination module 400 is used to determine the position information of the target relative to each radar node based on the distance information of the target relative to each radar node and the signal angle of arrival corresponding to each radar node.

[0199] The fusion module 500 is used to fuse the position information of the target relative to each radar node to obtain the target's tracking point, and to form the target's tracking trajectory based on the tracking point.

[0200] Based on the above-described target tracking method based on single-bit quantization, this embodiment provides a computer-readable storage medium storing one or more programs that can be executed by one or more processors to implement the steps in the target tracking method based on single-bit quantization as described in the above embodiment.

[0201] Based on the above-described target tracking method based on single-bit quantization, this application also provides a terminal device, such as... Figure 9As shown, it includes at least one processor 20; a display screen 21; and a memory 22, and may also include a communications interface 23 and a bus 24. The processor 20, display screen 21, memory 22, and communications interface 23 can communicate with each other via the bus 24. The display screen 21 is configured to display a preset user guide interface in the initial setup mode. The communications interface 23 can transmit information. The processor 20 can invoke logical instructions in the memory 22 to execute the methods described in the above embodiments.

[0202] Furthermore, the logical instructions in the aforementioned memory 22 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0203] The memory 22, as a computer-readable storage medium, can be configured to store software programs, computer-executable programs, such as program instructions or modules corresponding to the methods in the embodiments of this disclosure. The processor 20 executes functional applications and data processing by running the software programs, instructions, or modules stored in the memory 22, thereby implementing the methods in the above embodiments.

[0204] The memory 22 may include a program storage area and a data storage area. The program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 22 may include high-speed random access memory (RAM) and non-volatile memory. Examples include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, as well as transient storage media.

[0205] Furthermore, the specific process of loading and executing multiple instruction processors in the aforementioned storage medium and terminal device has been described in detail in the above method, and will not be repeated here.

[0206] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A target tracking method based on single-bit quantization, characterized in that, The target tracking method based on single-bit quantization specifically includes: Acquire echo data of each radar node in a multi-radar node system for the target; Each echo data is quantized into a single bit to obtain the single-bit data of each radar node; The distance information of the target relative to each radar node is estimated based on the single-bit data of each radar node, and the signal angle of arrival of each radar node is estimated based on the single-bit data of each radar node. Based on the distance information of the target relative to each radar node and the signal angle of arrival corresponding to each radar node, the position information of the target relative to each radar node is determined. The target's position information relative to each radar node is fused to obtain the target's tracking point, and the target's tracking trajectory is formed based on the tracking point; The single-bit quantization process is as follows: κ=B / T λ=1 / f c Among them, s one (t) represents a single bit of data, s IF (t) represents the echo data, real{g} represents the real part of the complex number, imag{g} represents the imaginary part of the complex number, sign(·) represents the sign operation, and A0 represents the signal amplitude. f represents the phase of the echo data. a The frequency of the echo data is represented by t, and the time-domain sampling is represented by t. κ represents the frequency modulation slope, B represents the signal frequency modulation bandwidth, T represents the signal frequency modulation period, c represents the speed of light, and f c Let R represent the carrier frequency, λ represent the carrier wavelength, mod(·) represents the integer operation, R represent the distance information, v represent the speed information, and f represent the velocity information. D f represents the velocity frequency. R Indicates distance frequency; The estimation of the target's distance information relative to each radar node based on single-bit data from each radar node specifically includes: T-point Fast Fourier Transform is performed on the fast time dimension of the single-bit data of each radar node to obtain the range frequency; The distance information of the target relative to each radar node is calculated based on the distance frequency; The method further includes: P-point Fast Fourier Transform is performed on the slow time dimension of the single-bit data of each radar node to obtain the velocity frequency. Calculate the target's velocity information relative to each radar node based on the velocity frequency; The velocity information of each radar node is fused to obtain the velocity information corresponding to the tracking point, and the velocity information is marked on the tracking point.

2. The target tracking method based on single-bit quantization according to claim 1, characterized in that, The radar nodes in the multi-radar node system are arranged at intervals, and adjacent radar nodes are geographically separated.

3. The target tracking method based on single-bit quantization according to claim 1, characterized in that, The fusion of the target's position information relative to each radar node to obtain the target's tracking point specifically includes: In a multi-radar node system, a radar node is selected as the target radar node, and the coordinate system of the selected target radar node is used as the target coordinate system. The target's position information relative to each of the other radar nodes is transformed to the target coordinate system to obtain the transformed position information of the target relative to each of the other radar nodes; The target's position information relative to the target radar node and the target's position information relative to the other radar nodes are fused to obtain the target's tracking point.

4. The target tracking method based on single-bit quantization according to claim 1, characterized in that, The multi-radar node system contains at least one specific radar node, which is equipped with a coprime array. The coprime array includes a first subarray, a second subarray, and a third subarray arranged sequentially in a straight line. The first subarray includes N array elements with an element spacing of Ld. The second subarray includes... The first subarray consists of 1 array element with an element spacing of Md; the third subarray consists of 1 L array element with an element spacing of Nd; the adjacent elements of the first and second subarrays overlap, and the adjacent elements of the second and third subarrays overlap, wherein N, M, and L are pairwise coprime.

5. A target tracking device based on single-bit quantization, characterized in that, The target tracking device based on single-bit quantization specifically includes: The acquisition module is used to acquire the echo data of each radar node in the multi-radar node system for the target; The quantization module is used to perform single-bit quantization on each echo data to obtain single-bit data for each radar node. The estimation module is used to estimate the distance information of the target relative to each radar node based on the single-bit data of each radar node, and to estimate the signal angle of arrival of each radar node based on the single-bit data of each radar node. The determination module is used to determine the position information of the target relative to each radar node based on the distance information of the target relative to each radar node and the signal angle of arrival corresponding to each radar node; The fusion module is used to fuse the position information of the target relative to each radar node to obtain the target's tracking point, and to form the target's tracking trajectory based on the tracking point; The single-bit quantization process is as follows: κ=B / T λ=1 / f c Among them, s one (t) represents a single bit of data, s IF (t) represents the echo data, real{g} represents the real part of the complex number, imag{g} represents the imaginary part of the complex number, sign(·) represents the sign operation, and A0 represents the signal amplitude. f represents the phase of the echo data. a The frequency of the echo data is represented by t, and the time-domain sampling is represented by t. κ represents the frequency modulation slope, B represents the signal frequency modulation bandwidth, T represents the signal frequency modulation period, c represents the speed of light, and f c Let R represent the carrier frequency, λ represent the carrier wavelength, mod(·) represents the integer operation, R represent the distance information, v represent the speed information, and f represent the velocity information. D f represents the velocity frequency. R Indicates distance frequency; The estimation of the target's distance information relative to each radar node based on single-bit data from each radar node specifically includes: T-point Fast Fourier Transform is performed on the fast time dimension of the single-bit data of each radar node to obtain the range frequency; The distance information of the target relative to each radar node is calculated based on the distance frequency; The fusion module is also used for: P-point Fast Fourier Transform is performed on the slow time dimension of the single-bit data of each radar node to obtain the velocity frequency. Calculate the target's velocity information relative to each radar node based on the velocity frequency; The velocity information of each radar node is fused to obtain the velocity information corresponding to the tracking point, and the velocity information is marked on the tracking point.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the steps in the target tracking method based on single-bit quantization as described in any one of claims 1-4.

7. A terminal device, characterized in that, include: Processor and memory; The memory stores a computer-readable program that can be executed by the processor; When the processor executes the computer-readable program, it implements the steps of the target tracking method based on single-bit quantization as described in any one of claims 1-4.

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