High-speed target tracking methods, devices, electronic equipment, and media based on LFMCW radar

Abstract

This invention provides a high-speed target tracking method, device, electronic device, and storage medium based on LFMCW radar. It estimates the target state at the current moment based on the echo data of LFMCW radar; determines the transmission waveform at the next moment based on the target state at the current moment; and tracks the target based on the transmission waveform at each moment. This can meet the different transmission waveform requirements at different stages of radar-target intersection and improve the tracking accuracy of high-speed intersecting targets.

Description

Technical Field

[0001] This invention relates to the field of high-speed target tracking technology, and in particular to a high-speed target tracking method, device, electronic device and storage medium based on LFMCW radar. Background Technology

[0002] In short-range target radar detection scenarios, tracking high-speed targets at close range is a key focus, requiring radar to track the target's range and velocity with high precision. Linear Frequency Modulated Continuous Wave (LFMCW) radar detects targets by transmitting continuous waves whose frequency changes linearly with time. Due to its large bandwidth, it easily achieves high range and velocity resolution, has no range blind zone, and features a simple system structure, small size, light weight, low operating voltage, and easy integration. The high requirement for transmit-receive isolation also makes LFMCW radar more suitable for short-range target detection.

[0003] Currently, LFMCW radars typically use a fixed transmission waveform for target detection. However, in practical applications, different stages of high-speed target encounters present different mission requirements for the radar system. For example, during the process of a target approaching or moving away from the radar, due to the high speed of the target, a stronger signal is usually required to achieve a higher echo signal-to-noise ratio, given a fixed radar transmission power. This necessitates a longer transmission time. As the target gets closer and more closely intersects with the radar, the distribution of observation points becomes denser, meaning the radar's observation frequency is higher, and more comprehensive target information is acquired under the same conditions. This requires both the transmission and signal processing times to be as short as possible. Therefore, LFMCW radars using a fixed transmission waveform cannot meet the requirements of different stages of high-speed target encounters in practical applications, affecting target tracking accuracy. Summary of the Invention

[0004] This invention provides a high-speed target tracking method, device, electronic device, and storage medium based on LFMCW radar, which solves the problem that traditional high-speed target tracking methods based on LFMCW radar use LFMCW radar with a fixed transmission waveform to track targets, making it difficult to meet the different stages of high-speed target intersection in practical applications and affecting target tracking accuracy.

[0005] This invention provides a high-speed target tracking method based on LFMCW radar, comprising:

[0006] Estimate the target status at the current moment based on the echo data from the LFMCW radar;

[0007] The transmission waveform for the next moment is determined based on the target state at the current moment;

[0008] The target is tracked based on the waveform emitted at each moment.

[0009] According to the present invention, a high-speed target tracking method based on LFMCW radar is provided, wherein determining the transmission waveform at the next moment based on the target state at the current moment includes:

[0010] Iterate through all waveforms in the preset waveform library and calculate the cost function corresponding to each waveform as the transmitted waveform at the next moment;

[0011] The cost function values ​​are matched with the additional constraints in ascending order.

[0012] If the waveform corresponding to the cost function value satisfies the additional constraint conditions, then the waveform is set as the transmission waveform at the next moment.

[0013] According to the present invention, a high-speed target tracking method based on LFMCW radar is provided, wherein calculating the cost function corresponding to each waveform as the transmitted waveform at the next moment includes:

[0014]

[0015] In the formula, Let D(·) be the cost function, representing the difference between two matrices; P(k+1|k+1) is the prediction covariance matrix at time k+1. Let θ be the expected covariance matrix. k The waveform selected for each moment.

[0016] According to the present invention, a high-speed target tracking method based on LFMCW radar is provided, wherein the method for obtaining the prediction covariance matrix includes:

[0017] P(k+1|k+1)=[IK(k+1)H(k+1)]P(k+1|k)

[0018] In the formula, K(k+1) is the Kalman filter gain, H(k+1) is the linearized observation matrix, P(k+1|k) is the one-step prediction covariance matrix, and I is the identity matrix.

[0019] The high-speed target tracking method based on LFMCW radar provided by the present invention further includes:

[0020] If none of the waveforms corresponding to all cost function values ​​satisfy the additional constraints, then the waveform at the current moment will be used as the transmission waveform at the next moment.

[0021] According to the present invention, a high-speed target tracking method based on LFMCW radar includes additional constraints, such as not generating second-order migration conditions across range cells.

[0022] According to the present invention, a high-speed target tracking method based on LFMCW radar is provided, wherein estimating the target state at the current moment based on the echo data of LFMCW radar includes:

[0023] Acquire echo data from the LFMCW radar;

[0024] Extended Kalman filtering is applied to the echo data of the LFMCW radar.

[0025] The target state at the current moment is estimated based on the echo data from the filtered LFMCW radar.

[0026] The present invention also provides a high-speed target tracking device based on LFMCW radar, comprising:

[0027] The estimation module is used to estimate the target status at the current moment based on the echo data from the LFMCW radar.

[0028] The determination module is used to determine the transmission waveform at the next moment based on the target state at the current moment;

[0029] The tracking module is used to track the target based on the waveform emitted at each moment.

[0030] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the high-speed target tracking method based on LFMCW radar as described above.

[0031] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the high-speed target tracking method based on LFMCW radar as described above.

[0032] The present invention provides a high-speed target tracking method, device, electronic equipment and storage medium based on LFMCW radar. It estimates the target state at the current moment based on the echo data of LFMCW radar; determines the transmission waveform at the next moment based on the target state at the current moment; and tracks the target based on the transmission waveform at each moment. This can meet the different transmission waveform requirements at different stages of radar-target intersection and improve the tracking accuracy of high-speed intersecting targets. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1 This is one of the flowcharts illustrating the high-speed target tracking method based on LFMCW radar provided by the present invention;

[0035] Figure 2 This is the second flowchart illustrating the high-speed target tracking method based on LFMCW radar provided by this invention.

[0036] Figure 3 This is the third flowchart illustrating a high-speed target tracking method based on LFMCW radar.

[0037] Figure 4 The target distance tracking result diagram based on agile waveforms provided by this invention;

[0038] Figure 5 The target velocity tracking result diagram based on agile waveforms provided by this invention;

[0039] Figure 6 The target distance tracking result diagram based on a fixed waveform provided by the present invention;

[0040] Figure 7 The target velocity tracking result diagram based on a fixed waveform provided by the present invention;

[0041] Figure 8 A graph showing the variation of the transmission frame period and the target distance during target tracking based on agile waveforms, provided by this invention.

[0042] Figure 9 The graph showing the variation of the transmission frame period and the target distance during target tracking based on a fixed waveform is provided by this invention.

[0043] Figure 10 A diagram showing the location of observation points during target tracking based on agile waveforms, provided by this invention.

[0044] Figure 11 The observation point location diagram provided by this invention for target tracking based on a fixed waveform;

[0045] Figure 12 This is a schematic diagram of the high-speed target tracking device based on LFMCW radar provided by the present invention;

[0046] Figure 13 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0048] Figure 1 A flowchart of a high-speed target tracking method based on LFMCW radar provided in an embodiment of the present invention is shown below. Figure 1 As shown, the high-speed target tracking method based on LFMCW radar provided in this embodiment of the invention includes:

[0049] Step 101: Estimate the target status at the current moment based on the echo data from the LFMCW radar;

[0050] In this embodiment of the invention, estimating the target state at the current moment based on the echo data of the LFMCW radar includes:

[0051] Step 1011: Acquire echo data from the LFMCW radar;

[0052] Step 1012: Perform extended Kalman filtering on the echo data of the LFMCW radar;

[0053] Step 1013: Estimate the target state at the current moment based on the echo data of the filtered LFMCW radar.

[0054] In this embodiment of the invention, the receiving end processes the echo data to obtain the target's measurement value, and uses the existing state and measurement information to perform extended Kalman filtering to make an optimal estimate of the state at the current moment.

[0055] Step 102: Determine the transmission waveform for the next moment based on the target status at the current moment;

[0056] Step 103: Track the target based on the waveform emitted at each moment.

[0057] Currently, LFMCW radars typically use a fixed transmission waveform for target detection. However, in practical applications, different stages of high-speed target encounters present different mission requirements for the radar system. For example, during the process of a target approaching or moving away from the radar, due to the high speed of the target, a stronger signal is usually required to achieve a higher echo signal-to-noise ratio, given a fixed radar transmission power. This necessitates a longer transmission time. As the target gets closer and more closely intersects with the radar, the distribution of observation points becomes denser, meaning the radar's observation frequency is higher, and more comprehensive target information is acquired under the same conditions. This requires both the transmission and signal processing times to be as short as possible. Therefore, LFMCW radars using a fixed transmission waveform cannot meet the requirements of different stages of high-speed target encounters in practical applications, affecting target tracking accuracy.

[0058] The high-speed target tracking method based on LFMCW radar provided in this invention estimates the target state at the current moment based on the echo data of LFMCW radar; determines the transmission waveform at the next moment based on the target state at the current moment; and tracks the target based on the transmission waveform at each moment. This method can meet the different transmission waveform requirements at different stages of radar-target intersection and improve the tracking accuracy of high-speed intersecting targets.

[0059] Based on any of the above embodiments, such as Figure 2 As shown, the step of determining the transmission waveform at the next moment based on the target state at the current moment specifically includes:

[0060] Step 201: Traverse all waveforms in the preset waveform library and calculate the cost function corresponding to each waveform as the transmission waveform at the next moment;

[0061] Step 202: Match the cost function values ​​with the additional constraints in ascending order;

[0062] Step 203: If the waveform corresponding to the cost function value satisfies the additional constraint conditions, then set the waveform as the transmission waveform at the next moment;

[0063] Step 204: If the waveforms corresponding to all cost function values ​​do not satisfy the additional constraints, then the waveform at the current moment is taken as the transmission waveform at the next moment.

[0064] In this embodiment of the invention, additional constraints include conditions that do not generate second-order migration conditions across distance cells.

[0065] At the end of the radar's encounter with the target, the large tangential velocity results in significant radial acceleration. Transmitting a fixed waveform for detection causes a second-order range-cell migration problem. In this case, the signal energy cannot be effectively concentrated in the range-Doppler cells, leading to substantial measurement errors. Therefore, this invention incorporates additional constraints to prevent second-order range-cell migration. Specifically, when selecting the waveform at each moment, the possibility of signal energy failing to be effectively concentrated in the range-Doppler cells must be considered to meet tracking accuracy requirements.

[0066] The key to target tracking during high-speed target rendezvous lies in employing appropriate waveform selection criteria to meet the detection performance requirements of such processes. Existing waveform selection criteria are all based on the assumption that higher tracking accuracy is always better. However, in practical applications, higher tracking accuracy often requires more data and greater computational complexity, creating a trade-off between tracking accuracy and system real-time performance. Reducing the amount of data processed and the computational complexity while achieving the desired tracking accuracy is more suitable for radar systems with high real-time requirements.

[0067] To address this issue, this invention introduces a waveform selection criterion for the expected covariance matrix, while adding additional constraints such as preventing the target from exhibiting second-order migration across distance units. The waveform selection criterion aims to choose a suitable waveform that makes the estimated accuracy of the target parameters approach the desired tracking accuracy, rather than simply pursuing the minimum tracking error.

[0068] In this embodiment of the invention, calculating the cost function corresponding to each waveform as the transmitted waveform at the next moment includes:

[0069]

[0070] In the formula, Let D(·) be the cost function, representing the difference between two matrices; P(k+1|k+1) is the prediction covariance matrix at time k+1. Let θ be the expected covariance matrix. k The waveform selected for each moment.

[0071] In this embodiment of the invention, the method for obtaining the predicted covariance matrix includes:

[0072] P(k+1|k+1)=[IK(k+1)H(k+1)]P(k+1|k)

[0073] In the formula, K(k+1) is the Kalman filter gain, H(k+1) is the linearized observation matrix, P(k+1|k) is the one-step prediction covariance matrix, and I is the identity matrix.

[0074] That is, selecting the optimal waveform so that P(k+1|k+1; θ) at the next time stepk The closest approximation to the expected covariance matrix The following cost function is defined to characterize the difference between the two.

[0075]

[0076] In this embodiment of the invention, the covariance matrix P(k+1|k+1; θ) can be obtained by calculation methods such as finding the difference of the determinants, finding the difference of their traces, and finding the joint mean square error of their diagonal elements. k The waveform selection criterion is related to the observation covariance noise matrix R(k+1) at the next time step, and R(k+1) is determined by the accuracy of the observations at the next time step. Therefore, the waveform selection criterion under this condition is...

[0077]

[0078] Specifically, the system iterates through each transmitted waveform in the established waveform library, calculates the cost function corresponding to each waveform under the current waveform selection criterion, sorts these cost functions, considers additional constraints, selects the optimal waveform, and updates the parameters of the tracking system until the tracking ends.

[0079] In three-dimensional space, due to the high speed of the target and the short rendezvous time, it is assumed to be moving at a constant velocity in a straight line. Therefore, in the discrete-time system, t... k The position of the target at any given time (x) k ,y k ,z k ) can be represented as

[0080] x k =x0+v x t k =x0+v x kT

[0081] y k =y0+v y t k =y0+v y kT

[0082] z k =z0+v z t k =z0+v z kT

[0083] Where (x0, y0, z0) is the initial position of the target, v x ,v y and v z These represent the velocity components along each coordinate axis of the target, and T is the observation interval.

[0084] The above three state expressions can be expressed in recursive form as follows:

[0085]

[0086]

[0087]

[0088] Therefore, the motion state of the target can be represented in vector form as follows:

[0089]

[0090] The state equation of the target can be written as

[0091] x(k+1)=F(k)x(k)+Γ(k)v(k)

[0092] Where Γ(K) is the process noise distribution matrix, and v(k) is the process noise vector, determined by the target motion model. Assuming the target moves at a constant velocity in a straight line, and disregarding the influence of process noise, Γ(k)v(k) is set to zero. This equation characterizes the target's motion state and is independent of observation. X(k) is the state vector at time k, X(k+1) is the state vector at time k+1, and F(k) is the system's state transition matrix, which can be expressed as...

[0093]

[0094] The measurement equations are assumptions made during the radar measurement process. For a linear system, the measurement equations can be expressed as follows:

[0095] z(k+1)=H(k+1)x(k+1)+w(k+1)

[0096] In the formula, H(k+1) is the measurement matrix, used to select a portion of the state variables in the state vector X(k+1) as observations. W(k+1) is zero-mean Gaussian white noise with covariance R(k+1), which is related to the signal-to-noise ratio and radar parameters at the current moment in practical applications.

[0097] Since the change in the target's measured value is non-linear, the measurement equation can be expressed as:

[0098]

[0099] In the formula r k+1 and These are the radial distance and radial velocity between the target and the radar, respectively, which can be expressed as:

[0100]

[0101]

[0102] The measurement equation represents the observed quantity. In practical applications, the measurement vector z(k+1) is not calculated by this equation, but is obtained by processing the received radar echo data.

[0103] One-step prediction of the target state is

[0104]

[0105] One-step prediction of covariance is

[0106] P(k+1|k)=F(k)P(k|k)F'(k)+Q(k)

[0107] In the formula, Q(k) is the process noise covariance, P(k|k) is the prediction covariance matrix at time k, and P(k+1|k) is the one-step prediction covariance matrix, which can be used to characterize whether the prediction is accurate. The smaller the covariance, the more accurate the prediction.

[0108] Similarly, the measurement prediction can be obtained as

[0109]

[0110] In the formula

[0111]

[0112]

[0113] The covariance matrix of the new information has the following covariance:

[0114] S(k+1)=H(k+1)P(k+1|k)H'(k+1)+R(k+1)

[0115] S(k+1), also known as the prediction covariance matrix of the measurement, can be used to characterize the uncertainty of the prediction. The smaller the prediction covariance, the more accurate the measurement value.

[0116] Kalman filter gain is

[0117] K(k+1)=P(k+1|k)H'(k+1)S -1 (k+1)

[0118] To obtain the linearized observation matrix H(k+1), the Jacobian matrix of the nonlinear measurement matrix needs to be calculated.

[0119]

[0120] in

[0121]

[0122] h 14 =0,h 15 =0,h 16 =0

[0123]

[0124]

[0125]

[0126] h 24 =h 11 ,h 25 =h 12 ,h 26 =h 13

[0127] The state update equation at time k+1 is:

[0128]

[0129] That is, the estimate at time k+1. Equal to the predicted state value at that moment In addition, a correction term related to the new information is added. K(k+1) is the gain of the correction term, reflecting the contribution of the latest observation information to the state estimate.

[0130] The covariance matrix at time k+1 is

[0131] P(k+1|k+1)=[IK(k+1)H(k+1)]P(k+1|k)

[0132] P(k+1|k+1) is the prediction covariance matrix at time k+1, which can be used to characterize whether the prediction is accurate. The smaller the covariance, the more accurate the prediction. Therefore, this matrix is ​​generally used for waveform selection.

[0133] In the tracking system, parameters that change with the transmitted waveform parameters, such as the noise covariance matrix and the state transition matrix, are updated, and then the loop for selecting the waveform at the next moment is started until the tracking ends.

[0134] This invention provides a high-speed target tracking method based on waveform agility, using LFMCW radar as an example. Based on extended Kalman filtering, it adds a waveform selection template based on expected covariance to the traditional target tracking process to meet the complex requirements of the entire target rendezvous process.

[0135] Based on any of the above embodiments, this invention example sets the radar at the origin of the coordinate system, the initial (x0, y0, z0) of the target is (5, 60, 0) m, and the target moves in uniform linear motion along the y-axis at a speed of v0 = 2000 m / s. The modulation start frequency of the LFMCW radar is set to 76 GHz, the sampling frequency to 100 MHz, and it is assumed that the radar can support a maximum modulation frequency of 100 MHz / μs, while retaining the maximum modulation slope when establishing the waveform library. Using a two-dimensional grid, based on the two variables N (fast-time sampling points) and M (slow-time accumulation periods), an LFM signal waveform library Φ1 = {N∈(2...} is established, containing sixteen waveforms. 6 ,2 7 ,2 8 ,2 9 ),M∈(2 6 ,2 7 ,2 8 ,2 9 The trace of the expected covariance matrix is ​​set to 3 × 10⁻⁶. -5 The signal-to-noise ratio of the received raw signal at the initial tracking moment is set to -25dB.

[0136] like Figure 3 As shown, the specific steps of the high-speed target tracking method based on LFMCW radar provided in this embodiment of the invention are as follows:

[0137] (1) The measurement value at the current moment and the state value at the previous moment;

[0138] (2) Calculate the cost function for each waveform in the waveform library;

[0139] (3) Sort the waveforms in the waveform library according to the selection priority based on the cost function;

[0140] (4) Extract the next waveform in order of priority;

[0141] (5) Determine whether all waveforms have been captured. If yes, execute (6); otherwise, keep the transmitted waveform from the previous moment.

[0142] (6) Determine whether the current waveform satisfies the additional constraints. If yes, execute (7); otherwise, maintain the transmission waveform of the previous moment.

[0143] (7) As the transmission waveform at the next moment;

[0144] (8) Track the equation update.

[0145] The high-speed target tracking method based on waveform agility in this embodiment of the invention is used to track the distance and velocity of the target, and the results are compared with those obtained by tracking the target using a fixed waveform. The initial waveform and the fixed waveform of the waveform agility are both Φ={N=512,M=512} waveforms with the best theoretical estimation accuracy. Figure 4 and Figure 5 The figures show the estimation errors of distance and velocity before and after using the waveform agile target tracking method and extended Kalman filtering, respectively. The root mean square errors of distance estimation before and after filtering are 0.0364m and 0.0059m, respectively, and the root mean square errors of velocity estimation before and after filtering are 0.9983m / s and 0.5524m / s, respectively. As can be seen from the figure and the change of root mean square error, the fluctuation of the measurement error of target parameters is significantly reduced after filtering.

[0146] Figure 6 and Figure 7 To assess the estimation errors of distance and velocity before and after Kalman filtering when using a fixed waveform for target tracking, the root mean square errors (RMS) of distance estimation before and after filtering are 0.3584 m and 0.0298 m, respectively, while the RMS errors of velocity estimation are 5.4845 m / s and 5.5057 m / s, respectively. It can be seen that at the last two observation points, both the target's velocity and distance measurements exhibit significant errors. This is because the target is at the very end of the intersection, with a high tangential velocity, resulting in a large radial acceleration. Although the fixed waveform theoretically offers high measurement accuracy, its long accumulation time leads to a second-order range cell migration problem, preventing effective concentration of signal energy across the range-Doppler cells and resulting in substantial measurement errors. Therefore, from the perspective of the overall RMS error estimation during the intersection process, waveform agility demonstrates a clear advantage over the fixed waveform.

[0147] The real-time performance of the data output at the rendezvous end is analyzed below. Figure 8 and Figure 9 The graphs show the transmission frame period results for both the agile waveform and fixed waveform methods. Figure 8 As can be seen, the frame period of the radar transmitted waveform becomes shorter and shorter as the target moves closer, allowing for more real-time measurement results at the rendezvous end. Figure 9 To ensure a fixed waveform, the transmission frame period remains constant. When the radial distance to the target is within 10m, the transmission frame period is more than 10 times that of the waveform agility.

[0148] Figure 10 and Figure 11 The images show the target's actual position at the observation point under both methods throughout the rendezvous process. It can be seen that at the end of the rendezvous, the waveform agility method, due to the shorter frame period of the transmitted waveform, results in a denser distribution of observation points, a higher frequency of radar observations, and more comprehensive target information acquired under the same conditions. It also makes it easier to observe information about the target near the rendezvous point. From this perspective, waveform agility has irreplaceable advantages over fixed waveforms.

[0149] The high-speed target tracking method based on LFMCW radar provided in this invention can adaptively select the optimal transmission waveform at the current moment to track the target as it approaches from a distance. This ensures that the target is detected as early as possible at long distances and outputs target parameter estimation results with higher real-time performance at close distances. In addition, the method of switching transmission waveform parameters can avoid problems such as second-order cross-range cell migration, thereby meeting the complex detection performance requirements throughout the entire target rendezvous process.

[0150] The high-speed target tracking device based on LFMCW radar provided by the present invention will be described below. The high-speed target tracking device based on LFMCW radar described below can be referred to in correspondence with the high-speed target tracking method based on LFMCW radar described above.

[0151] Figure 12 A schematic diagram of a high-speed target tracking device based on LFMCW radar provided in an embodiment of the present invention is shown below. Figure 12 As shown, the high-speed target tracking device based on LFMCW radar provided in this embodiment of the invention includes:

[0152] The estimation module 1201 is used to estimate the target status at the current moment based on the echo data of the LFMCW radar.

[0153] The determination module 1202 is used to determine the transmission waveform at the next moment based on the target state at the current moment;

[0154] The tracking module 1203 is used to track the target based on the waveform emitted at each moment.

[0155] The high-speed target tracking device based on LFMCW radar provided in this embodiment of the invention estimates the target state at the current moment based on the echo data of LFMCW radar; determines the transmission waveform at the next moment based on the target state at the current moment; and tracks the target based on the transmission waveform at each moment. This can meet the different transmission waveform requirements at different stages of radar-target intersection and improve the tracking accuracy of high-speed intersecting targets.

[0156] Figure 13 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 13As shown, the electronic device may include a processor 1310, a communications interface 1320, a memory 1330, and a communication bus 1340. The processor 1310, communications interface 1320, and memory 1330 communicate with each other via the communication bus 1340. The processor 1310 can call logical instructions in the memory 1330 to execute a high-speed target tracking method based on LFMCW radar. This method includes: estimating the target state at the current moment based on the echo data from the LFMCW radar; determining the transmission waveform at the next moment based on the target state at the current moment; and tracking the target based on the transmitted waveform at each moment.

[0157] Furthermore, the logical instructions in the aforementioned memory 1330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes 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.

[0158] On the other hand, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the high-speed target tracking method based on LFMCW radar provided by the above methods. The method includes: estimating the target state at the current moment based on the echo data of LFMCW radar; determining the transmission waveform at the next moment based on the target state at the current moment; and tracking the target based on the transmission waveform at each moment.

[0159] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0160] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention 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; and these 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 the present invention.

Claims

1. A high-speed target tracking method based on LFMCW radar, characterized in that, include: Estimate the target status at the current moment based on the echo data from the LFMCW radar; The transmission waveform for the next moment is determined based on the target state at the current moment; The target is tracked based on the waveform emitted at each moment; Determining the transmission waveform at the next moment based on the target state at the current moment includes: Iterate through all waveforms in the preset waveform library and calculate the cost function corresponding to each waveform as the transmitted waveform at the next moment; The cost function values ​​are matched with the additional constraints in ascending order. If the waveform corresponding to the cost function value satisfies the additional constraint condition, then the waveform is set as the transmission waveform at the next moment; The additional constraints include not generating second-order migration conditions across distance-Doppler units, meaning that when selecting waveforms at each time step, it is necessary to consider whether there will be a situation where signal energy cannot be effectively concentrated on the distance-Doppler units.

2. The high-speed target tracking method based on LFMCW radar according to claim 1, characterized in that, The calculation of the cost function corresponding to each waveform as the transmitted waveform at the next moment includes: ； In the formula, Let cost function be This indicates finding the difference between two matrices; yes The prediction covariance matrix at time 1, Let be the expected covariance matrix. The waveform selected for each moment.

3. The high-speed target tracking method based on LFMCW radar according to claim 2, characterized in that, The method for obtaining the predicted covariance matrix includes: ； In the formula, It is the Kalman filter gain. For linearized observation matrices, It is a step to predict the covariance matrix. It is an identity matrix.

4. The high-speed target tracking method based on LFMCW radar according to claim 1, characterized in that, Also includes: If none of the waveforms corresponding to all cost function values ​​satisfy the additional constraints, then the waveform at the current moment will be used as the transmission waveform at the next moment.

5. The high-speed target tracking method based on LFMCW radar according to claim 1, characterized in that, The estimation of the target state at the current moment based on the echo data of the LFMCW radar includes: Acquire echo data from the LFMCW radar; Extended Kalman filtering is applied to the echo data of the LFMCW radar. The target state at the current moment is estimated based on the echo data from the filtered LFMCW radar.

6. A high-speed target tracking device based on LFMCW radar, characterized in that, include: The estimation module is used to estimate the target status at the current moment based on the echo data from the LFMCW radar. The determination module is used to determine the transmission waveform for the next moment based on the target state at the current moment. This includes: traversing all waveforms in a preset waveform library and calculating the cost function corresponding to each waveform as the transmission waveform for the next moment; matching the cost function values ​​sequentially with additional constraints in ascending order; if the waveform corresponding to the cost function value satisfies the additional constraints, then setting that waveform as the transmission waveform for the next moment; the additional constraints include not generating a second-order migration condition across range-Doppler cells, i.e., when selecting a waveform at each moment, it is necessary to consider whether there will be a situation where signal energy cannot be effectively concentrated on the range-Doppler cells. The tracking module is used to track the target based on the waveform emitted at each moment.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the high-speed target tracking method based on LFMCW radar as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the high-speed target tracking method based on LFMCW radar as described in any one of claims 1 to 5.

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