On-grid sparse recovery radar target parameter estimation method and device based on echo reconstruction

Abstract

The present invention provides an On-grid sparse recovery radar target parameter estimation method and device based on echo reconstruction. The method comprises: reconstructing the target echo signal using an observation matrix, a sparse approximate solution and a residual; oversampling the transmitted signal and the reconstructed echo signal, and calculating the two-dimensional matched filter response; re-searching the target spectrum peak position, and using a second-order polynomial interpolation algorithm to obtain the time delay, Doppler frequency and amplitude parameters. The present invention reconstructs the target echo signal, oversamples the transmitted signal and the reconstructed echo signal, and calculates the two-dimensional matched filter response. After obtaining the target spectrum peak position, the time delay, Doppler frequency and amplitude parameters of the radar wave are finally obtained, which can reduce the computational complexity, improve the theoretical estimation accuracy, and facilitate engineering implementation.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of radar technology, and in particular to an on-grid sparse recovery radar target parameter estimation method and device based on echo reconstruction. Background Art

[0002] Thanks to the sparse distribution of radar echoes on the delay-Doppler plane in most detection scenarios, sparse recovery methods are often used to solve the problems of high sidelobe levels and low resolution. The currently widely used sparse recovery methods assume that the target is distributed in a finite discrete parameter (such as delay-Doppler) space, and then solve the sparse approximate solution of the observation equation to finally achieve super-resolution effects. These methods are usually called on-grid sparse methods. The range Doppler spectrum processed by the on-grid sparse recovery algorithm has a significant feature that is different from the traditional matched filtering method, that is, the target spectrum peak is very sharp, the main lobe width is very small, and other sampling points near the peak are much smaller than the peak point. The target spectrum peak and its adjacent sampling points no longer meet the assumption of being distributed on the same parabola main peak, which leads to the failure of the quadratic polynomial interpolation method. Therefore, the development of an on-grid sparse recovery radar target parameter estimation method and device based on echo reconstruction can effectively overcome the defects in the above-mentioned related technologies, which has become a technical problem that needs to be solved urgently in the industry. Summary of the invention

[0003] In view of the above problems existing in the prior art, an embodiment of the present invention provides an on-grid sparse recovery radar target parameter estimation method and device based on echo reconstruction.

[0004] In the first aspect, an embodiment of the present invention provides an On-grid sparse recovery radar target parameter estimation method based on echo reconstruction, comprising: reconstructing the target echo signal using an observation matrix, a sparse approximate solution and a residual; oversampling the transmitted signal and the reconstructed echo signal, and calculating the two-dimensional matched filter response; re-searching the target spectrum peak position, and using a second-order polynomial interpolation algorithm to obtain the delay, Doppler frequency and amplitude parameters.

[0005] Based on the content of the above method embodiment, an On-grid sparse recovery radar target parameter estimation method based on echo reconstruction is provided in an embodiment of the present invention, wherein the target echo signal is reconstructed using an observation matrix, a sparse approximate solution and a residual, including: constructing an atomic vector in the observation matrix by modulating the transmission signal through time delay and Doppler frequency, multiplying the atomic vector with the non-zero term corresponding to the target in the sparse solution vector, and adding the residual vector to obtain the target echo signal.

[0006] Based on the content of the above method embodiment, the on-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, the target echo signal includes:

[0007]

[0008]

[0009]

[0010] Among them, secho1 is the first target echo signal, L is the number of diffusion peaks, is the relative amplitude of the lth echo path, is the intermediate variable, The time delay of the lth line is τ l =n l T s The zero Doppler multipath signal, r is the residual, f l is the Doppler frequency of the lth echo path, e is the natural index, j is the complex number, nl is the number of delay points, T s is the time domain sampling interval, N is the number of time domain sampling points of the echo signal, T is the transposed symbol, s T [·] is the sampling point of the transmitted signal.

[0011] Based on the content of the above method embodiment, the on-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, the target echo signal also includes:

[0012]

[0013] Among them, s echo2 is the second target echo signal, A is the observation matrix, To represent a vector.

[0014] Based on the content of the above method embodiment, the on-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, wherein the delay is obtained by using a second-order polynomial interpolation algorithm, comprises:

[0015]

[0016] in, is the rough estimate of the target delay, is the Doppler frequency deviation grid estimate, are the sampling values ​​corresponding to the previous delay unit, the current delay unit, and the next delay unit on the target Doppler profile, respectively. |z[·]| is the modulus value of z[·]. For delay.

[0017] Based on the content of the above method embodiment, the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, wherein the Doppler frequency is obtained by using a second-order polynomial interpolation algorithm, comprises:

[0018]

[0019]

[0020] in, is the rough estimate of the target Doppler frequency, is the Doppler frequency deviation grid estimate, are the sampling value corresponding to the previous Doppler unit, the sampling value corresponding to the current Doppler unit, and the sampling value corresponding to the next Doppler unit on the target delay profile, respectively. is the Doppler frequency.

[0021] Based on the content of the above method embodiment, the on-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, wherein the amplitude parameter is obtained by using a second-order polynomial interpolation algorithm, comprises:

[0022]

[0023]

[0024]

[0025] in, is the peak value of the delay dimension, is the Doppler peak value, is the target amplitude estimate.

[0026] In the second aspect, an embodiment of the present invention provides an On-grid sparse recovery radar target parameter estimation device based on echo reconstruction, including: a first main module, used to reconstruct the target echo signal using an observation matrix, a sparse approximate solution and a residual; a second main module, used to oversample the transmitted signal and the reconstructed echo signal, and calculate the two-dimensional matched filter response; a third main module, used to re-search the target spectrum peak position, and use a second-order polynomial interpolation algorithm to obtain the delay, Doppler frequency and amplitude parameters.

[0027] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0028] at least one processor; and

[0029] at least one memory in communication with the processor, wherein:

[0030] The memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided by any one of the various implementations of the first aspect.

[0031] In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions enable a computer to execute the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided by any one of the various implementation methods of the first aspect.

[0032] The on-grid sparse recovery radar target parameter estimation method and device based on echo reconstruction provided in the embodiment of the present invention reconstructs the target echo signal, oversamples the transmitted signal and the reconstructed echo signal, calculates the two-dimensional matched filter response, obtains the target spectrum peak position, and finally obtains the time delay, Doppler frequency and amplitude parameters of the radar wave, which can reduce the calculation complexity, improve the theoretical estimation accuracy, and is conducive to engineering implementation. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 A flow chart of an On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided by an embodiment of the present invention;

[0035] Figure 2 A schematic diagram of the structure of an On-grid sparse recovery radar target parameter estimation device based on echo reconstruction provided by an embodiment of the present invention;

[0036] Figure 3 A schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention;

[0037] Figure 4 A schematic diagram of simulation results of accurate delay estimation provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In addition, the technical features in the various embodiments or single embodiments provided by the present invention can be arbitrarily combined with each other to form a feasible technical solution. This combination is not subject to the constraints of the sequence of steps and / or the structural composition mode, but must be based on the ability of ordinary technicians in this field to achieve. When the combination of technical solutions is contradictory or cannot be achieved, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0039] The embodiment of the present invention provides an on-grid sparse recovery radar target parameter estimation method based on echo reconstruction, see Figure 1 The method includes: reconstructing the target echo signal by using the observation matrix, sparse approximate solution and residual; oversampling the transmitted signal and the reconstructed echo signal, and calculating the two-dimensional matched filter response; re-searching the target spectrum peak position, and using the second-order polynomial interpolation algorithm to obtain the time delay, Doppler frequency and amplitude parameters.

[0040] Based on the content of the above method embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, which uses an observation matrix, a sparse approximate solution and a residual to reconstruct the target echo signal, includes: using the transmitted signal after time delay and Doppler frequency modulation to construct an atomic vector in the observation matrix, multiplying the atomic vector with the non-zero item corresponding to the target in the sparse solution vector, and adding it to the residual vector to obtain the target echo signal.

[0041] Based on the content of the above method embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, the target echo signal includes:

[0042]

[0043]

[0044]

[0045] Among them, s echo1 is the first target echo signal, L is the number of diffusion peaks, is the relative amplitude of the lth echo path, is the intermediate variable, The time delay of the lth line is τ l =n l T s The zero Doppler multipath signal, r is the residual, f l is the Doppler frequency of the lth echo path, e is the natural index, j is the complex number sign, n l is the delay point, T s is the time domain sampling interval, N is the number of time domain sampling points of the echo signal, T is the transposed symbol, s T [·] is the sampling point of the transmitted signal.

[0046] In another embodiment, the target echo signal is reconstructed using an observation matrix, a sparse approximate solution and a residual. First, each atomic vector in the observation matrix is ​​constructed by modulating the transmission signal through time delay and Doppler frequency, and the atomic vector is multiplied by the non-zero term corresponding to the target in the sparse solution vector, and then added to the residual vector to obtain the target echo signal. It should be noted that the atomic mismatch caused by the discrete grid assumption makes it difficult for a single atom to completely match the target signal, so it is necessary to use multiple adjacent atoms to comprehensively characterize the original target signal. From the energy point of view, the echo energy leaks to the adjacent grid. In the present invention, the echo energy is modeled into three parts, namely residual energy, main peak energy and adjacent diffusion energy, which are respectively distributed in the residual signal, the target main peak in the sparse solution vector and its adjacent elements. Therefore, when reconstructing the echo signal, it is necessary to concentrate all the scattered energy, and the specific implementation methods are mainly listed as follows.

[0047] Implementation method I: First, from the sparse solution vector Extract the relative amplitude of the target echo, including the main peak (denoted as ) and the diffusion peak (denoted as A total of L). Then the transmit signal is modulated using the relative amplitude and the target's delay and Doppler frequency, and finally the modulated signal is added to the residual to obtain the reconstructed echo signal of the target. If there are Q targets to be processed, the above process can be performed Q times. The implementation method of the modulation process is: first, the reference signal s T The time delay is shifted and recorded as (3). Then the multipath signal is Doppler modulated. The final echo signal can be expressed as (1).

[0048] Based on the content of the above method embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, the target echo signal also includes:

[0049]

[0050] Among them, s echo2is the second target echo signal, A is the observation matrix, To represent a vector.

[0051] In another embodiment, implementation method II: Assume that Q targets need to be processed simultaneously, and the difference in the echo amplitudes of these Q targets is required to be as small as possible (for example, the maximum difference is 5 dB) to reduce the impact of strong targets on weak targets. First, from the sparse solution vector Extract the relative amplitude coefficients of the echoes of Q targets (including the main peak and the diffusion peak) and fill them into From the all-zero vector of the same dimension, we get a representation vector containing Q targets Finally, the echo signal is obtained as shown in formula (4). The reference signal and the echo signal are oversampled and the two-dimensional matched filter response is calculated, aiming to recalculate the matched filter response in an oversampled manner. For the oversampling process, a method for fast calculation in the frequency domain is as follows. Denote s FD is the frequency domain column vector of the desired oversampled signal, then the oversampled frequency domain signal s′ FD It is expressed as:

[0052]

[0053] s′=IFFT(s′ FD ) (4.2)

[0054] Where α represents the oversampling ratio, N is the number of sampling points of the original signal, [αN] represents the integer closest to αN, the superscript “T” represents transposition, IFFT(·) represents inverse Fourier transform, and s′ represents the time domain signal after oversampling.

[0055] The calculation of the output response of the two-dimensional matched filter can be realized in two ways in the present invention:

[0056] Calculation method I: mutual fuzzy function method, that is

[0057]

[0058] Where τ represents the delay, f D represents the Doppler frequency, s echo [·] is the sampling point of the echo signal, s T * [·] is the conjugate of the transmitted signal sampling data.

[0059] Implementation method II: Directly use the conjugate transpose A of the observation matrix H With the target echo data vector s echo Multiply, that is

[0060] x ψ =A H s echo1or x ψ =A H s echo2 (4.4)

[0061] Then x ψ By rearranging the vectors, we can get the two-dimensional matched filter output response.

[0062] Based on the content of the above method embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, wherein the delay is obtained by using a second-order polynomial interpolation algorithm, includes:

[0063]

[0064] in, is the rough estimate of the target delay, is the Doppler frequency deviation grid estimate, are the sampling values ​​corresponding to the previous delay unit, the current delay unit, and the next delay unit on the target Doppler profile, respectively. |z[·]| is the modulus value of z[·]. For delay.

[0065] In another embodiment, the echo spectrum peak position is searched again, and the delay, Doppler frequency and amplitude parameters are estimated using a second-order polynomial interpolation method. The calculation formula for the precise estimation is shown in formula (5).

[0066] Based on the content of the above method embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, wherein the Doppler frequency is obtained by using a second-order polynomial interpolation algorithm, comprises:

[0067]

[0068]

[0069] in, is the rough estimate of the target Doppler frequency, is the Doppler frequency deviation grid estimate, are the sampling value corresponding to the previous Doppler unit, the sampling value corresponding to the current Doppler unit, and the sampling value corresponding to the next Doppler unit on the target delay profile, respectively. is the Doppler frequency.

[0070] In another embodiment, the Doppler frequency The calculation formula for the precise estimation is shown in formula (6).

[0071] Based on the content of the above method embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention, wherein the amplitude parameter is obtained by using a second-order polynomial interpolation algorithm, includes:

[0072]

[0073]

[0074]

[0075] in, is the peak value of the delay dimension, is the Doppler peak value, is the target amplitude estimate.

[0076] In another embodiment, the delay dimension peak The estimated calculation formula is shown in formula (9), the Doppler peak The estimated calculation formula is shown in formula (10).

[0077] The on-grid sparse recovery radar target parameter estimation method based on echo reconstruction provided in the embodiment of the present invention reconstructs the target echo signal, oversamples the transmitted signal and the reconstructed echo signal, calculates the two-dimensional matched filter response, obtains the target spectrum peak position, and finally obtains the time delay, Doppler frequency and amplitude parameters of the radar wave, which can reduce the calculation complexity, improve the theoretical estimation accuracy, and is conducive to engineering implementation.

[0078] The effects of various embodiments of the present invention can be verified through the simulation experiments of the following embodiments. In the simulation, the detection scenario of external radiation source radar is taken as an example. Because the signal used is usually a third-party radiation source such as communication or broadcasting, the signal waveform is not specially designed for radar detection, and the waveform sidelobe is high. In addition, the monitoring signal contains strong direct waves and a large amount of ground clutter or sea clutter. The performance of traditional clutter suppression methods is limited. The sidelobes of residual clutter and strong target echoes can easily cover weak targets. Therefore, this is a very representative application scenario of sparse representation. In the simulation experiment, the signal bandwidth β = 10kHz, the sampling duration T = 20 seconds, Δt = 1 / β (s), Δf = 1 / T (Hz). Set the delay grid amount to a variable evenly distributed in -0.5 to 0.5 times the sampling interval, that is, Δn t ~U(-0.5,0.5)(Δt). The Doppler frequency is off the grid by Δn f =0.266(Δf). The matched filter output signal-to-noise ratio was set to (10:0.5:30) dB, and 10,000 Monte Carlo simulations were performed at each signal-to-noise ratio.

[0079] For details, please refer to Figure 4 , the horizontal axis represents the coherent accumulation output signal-to-noise ratio, and the vertical axis represents the standard deviation of the delay estimation, where SB refers to the sampling boundary, which represents the upper limit of the delay estimation error of the sampling time axis quantization effect under high signal-to-noise ratio. That is, at the effective signal-to-noise ratio, the discrete delay estimate n0T that can be determined s Still at ±T of the true peak position t0 s / 2 fluctuation, T s is the sampling time interval in the time domain. The effective signal-to-noise ratio refers to the output signal-to-noise ratio when the signal can be effectively detected after interference accumulation. In the embodiment of the present invention, the effective signal-to-noise ratio is above about 15dB. When the signal-to-noise ratio is lower than this, the parameter estimation is seriously affected by the background noise floor and is not considered within the scope of the present invention. It can be clearly seen from the simulation results that if the quadratic interpolation method is used directly to estimate the delay parameters after the sparse recovery process, the estimation accuracy is poor. However, after using the method proposed in the present invention, the parameter estimation accuracy is significantly improved. The simulations of the Doppler frequency and amplitude parameters are consistent with Figure 4 The above results show that the On-grid sparse recovery radar target parameter fine estimation method based on echo reconstruction proposed in the present invention has excellent parameter fine estimation performance and is very easy to implement in engineering.

[0080] The implementation basis of each embodiment of the present invention is to implement programmed processing through a device with a processor function. Therefore, in engineering practice, the technical solutions and functions of each embodiment of the present invention can be encapsulated into various modules. Based on this reality, on the basis of the above embodiments, an embodiment of the present invention provides an On-grid sparse recovery radar target parameter estimation device based on echo reconstruction, which is used to execute the On-grid sparse recovery radar target parameter estimation method based on echo reconstruction in the above method embodiment. See Figure 2 The device includes: a first main module, which is used to reconstruct the target echo signal by using the observation matrix, the sparse approximate solution and the residual; a second main module, which is used to oversample the transmission signal and the reconstructed echo signal and calculate the two-dimensional matched filter response; a third main module, which is used to re-search the target spectrum peak position and use the second-order polynomial interpolation algorithm to obtain the time delay, Doppler frequency and amplitude parameters.

[0081] The on-grid sparse recovery radar target parameter estimation device based on echo reconstruction provided by the embodiment of the present invention adopts Figure 2 Several modules in the system reconstruct the target echo signal, oversample the transmitted signal and the reconstructed echo signal, calculate the two-dimensional matched filter response, obtain the target spectrum peak position, and finally obtain the time delay, Doppler frequency and amplitude parameters of the radar wave, which can reduce the calculation complexity, improve the theoretical estimation accuracy, and facilitate engineering implementation.

[0082] It should be noted that the device in the device embodiment provided by the present invention can be used to implement the method in the above method embodiment as well as the method in other method embodiments provided by the present invention. The only difference is that the corresponding functional modules are set, and the principle is basically the same as the principle of the above device embodiment provided by the present invention. As long as the technical personnel in the field refer to the specific technical solutions in other method embodiments on the basis of the above device embodiment, obtain the corresponding technical means and the technical solutions composed of these technical means by combining technical features, the device in the above device embodiment can be improved on the premise of ensuring the practicality of the technical solution, thereby obtaining the corresponding device class embodiment, which is used to implement the methods in other method class embodiments. For example:

[0083] Based on the content of the above-mentioned device embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation device based on echo reconstruction provided in the embodiment of the present invention also includes: a first sub-module, used to realize the reconstruction of the target echo signal using the observation matrix, sparse approximate solution and residual, including: using the transmitted signal through time delay and Doppler frequency modulation to construct an atomic vector in the observation matrix, multiplying the atomic vector with the non-zero item corresponding to the target in the sparse solution vector, and adding it to the residual vector to obtain the target echo signal.

[0084] Based on the content of the above device embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation device based on echo reconstruction provided in the embodiment of the present invention further includes: a second submodule, which is used to realize the target echo signal, including:

[0085]

[0086]

[0087]

[0088] Among them, s echo1 is the first target echo signal, L is the number of diffusion peaks, is the relative amplitude of the lth echo path, is the intermediate variable, The time delay of the lth line is τ l =n l T s The zero Doppler multipath signal, r is the residual, f l is the Doppler frequency of the lth echo path, e is the natural index, j is the complex number sign, n l is the delay point, T sis the time domain sampling interval, N is the number of time domain sampling points of the echo signal, T is the transposed symbol, s T [·] is the sampling point of the transmitted signal.

[0089] Based on the content of the above device embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation device based on echo reconstruction provided in the embodiment of the present invention further includes: a third submodule, used to implement the target echo signal, and also includes:

[0090]

[0091] Among them, s echo2 is the second target echo signal, A is the observation matrix, To represent a vector.

[0092] Based on the content of the above device embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation device based on echo reconstruction provided in the embodiment of the present invention further includes: a fourth submodule, which is used to implement the and use the second-order polynomial interpolation algorithm to obtain the delay, including:

[0093]

[0094] in, is the rough estimate of the target delay, is the Doppler frequency deviation grid estimate, are the sampling values ​​corresponding to the previous delay unit, the current delay unit, and the next delay unit on the target Doppler profile, respectively. |z[·]| is the modulus value of z[·]. For delay.

[0095] Based on the content of the above device embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation device based on echo reconstruction provided in the embodiment of the present invention further includes: a fifth submodule, which is used to implement the and use the second-order polynomial interpolation algorithm to obtain the Doppler frequency, including:

[0096]

[0097]

[0098] in, is the rough estimate of the target Doppler frequency, is the Doppler frequency deviation grid estimate, are the sampling value corresponding to the previous Doppler unit, the sampling value corresponding to the current Doppler unit, and the sampling value corresponding to the next Doppler unit on the target delay profile, respectively. is the Doppler frequency.

[0099] Based on the content of the above device embodiment, as an optional embodiment, the On-grid sparse recovery radar target parameter estimation device based on echo reconstruction provided in the embodiment of the present invention further includes: a sixth submodule, which is used to implement the and use the second-order polynomial interpolation algorithm to obtain the amplitude parameter, including:

[0100]

[0101]

[0102]

[0103] in, is the peak value of the delay dimension, is the Doppler peak value, is the target amplitude estimate.

[0104] The method of the embodiment of the present invention is implemented by relying on electronic devices, so it is necessary to introduce the relevant electronic devices. Based on this purpose, the embodiment of the present invention provides an electronic device, such as Figure 3 As shown, the electronic device includes: at least one processor, a communication interface, at least one memory, and a communication bus, wherein at least one processor, the communication interface, and at least one memory communicate with each other through the communication bus. At least one processor can call the logic instructions in at least one memory to execute all or part of the steps of the method provided by the aforementioned various method embodiments.

[0105] In addition, the logic instructions in the at least one memory mentioned above can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each method embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0106] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0107] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0108] The flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. Based on this understanding, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and sometimes in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of the boxes in the block diagram and / or the flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0109] In this patent, the terms "include", "comprises" or any other variation thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "includes..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An On-grid sparse recovery radar target parameter estimation method based on echo reconstruction, characterized in that: include: The target echo signal is reconstructed using the observation matrix, sparse approximate solution and residual; Wherein, the target echo signal includes: in, is the first target echo signal, L is the number of diffusion peaks, is the relative amplitude of the lth echo path, is the intermediate variable, For the The delay is The zero Doppler multipath signal, r is the residual, is the Doppler frequency of the lth echo path, e is the natural index, j is the complex number sign, is the delay point, is the time domain sampling interval, N is the number of time domain sampling points of the echo signal, T is the transposed symbol, is the sampling point of the transmitted signal; Oversampling the transmitted signal and the reconstructed echo signal, and calculating the two-dimensional matched filter response; The target spectrum peak position is searched again, and the time delay, Doppler frequency and amplitude parameters are obtained using a second-order polynomial interpolation algorithm.

2. The on-grid sparse recovery radar target parameter estimation method based on echo reconstruction according to claim 1 is characterized in that: The method of reconstructing a target echo signal using an observation matrix, a sparse approximate solution and a residual includes: constructing an atomic vector in the observation matrix by modulating a transmitted signal through time delay and Doppler frequency, multiplying the atomic vector with a non-zero term corresponding to the target in a sparse solution vector, and adding the result to the residual vector to obtain the target echo signal.

3. The on-grid sparse recovery radar target parameter estimation method based on echo reconstruction according to claim 1 is characterized in that: The target echo signal further includes: in, is the second target echo signal, A is the observation matrix, To represent a vector.

4. The on-grid sparse recovery radar target parameter estimation method based on echo reconstruction according to claim 3 is characterized in that: The time delay is obtained by using a second-order polynomial interpolation algorithm, including: in, is the rough estimate of the target delay, is the Doppler frequency deviation grid estimate, , , are the sampling value corresponding to the previous time delay unit, the sampling value corresponding to the current time delay unit, and the sampling value corresponding to the next time delay unit on the target Doppler profile, respectively. For Modulo value, For delay.

5. The on-grid sparse recovery radar target parameter estimation method based on echo reconstruction according to claim 4 is characterized in that: The Doppler frequency is obtained by using a second-order polynomial interpolation algorithm, including: in, is the rough estimate of the target Doppler frequency, is the Doppler frequency deviation grid estimate, , , are the sampling value corresponding to the previous Doppler unit, the sampling value corresponding to the current Doppler unit, and the sampling value corresponding to the next Doppler unit on the target delay profile, respectively. is the Doppler frequency.

6. The on-grid sparse recovery radar target parameter estimation method based on echo reconstruction according to claim 5 is characterized in that: The amplitude parameters are obtained by using a second-order polynomial interpolation algorithm, including: in, is the peak value of the delay dimension, is the Doppler peak value, is the target amplitude estimate.

7. An On-grid sparse recovery radar target parameter estimation device based on echo reconstruction, characterized in that: include: The first main module is used to reconstruct the target echo signal by using the observation matrix, the sparse approximate solution and the residual; wherein the target echo signal includes: in, is the first target echo signal, L is the number of diffusion peaks, is the relative amplitude of the lth echo path, is the intermediate variable, For the The delay is The zero Doppler multipath signal, r is the residual, is the Doppler frequency of the lth echo path, e is the natural index, j is the complex number sign, is the delay point, is the time domain sampling interval, N is the number of time domain sampling points of the echo signal, T is the transposed symbol, is the sampling point of the transmitted signal; The second main module is used to perform oversampling processing on the transmission signal and the reconstructed echo signal, and calculate the two-dimensional matched filter response; The third main module is used to re-search the target spectrum peak position and use the second-order polynomial interpolation algorithm to obtain the time delay, Doppler frequency and amplitude parameters.

8. An electronic device, characterized in that: include: At least one processor, at least one memory and a communication interface; wherein, The processor, memory and communication interface communicate with each other; The memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, which cause the computer to execute the method of any one of claims 1 to 6.

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