Radar waveform optimization method and system capable of resisting full pulse forwarding type interference

Abstract

The invention discloses a radar waveform optimization method and system for resisting full pulse forwarding interference, and relates to the technical field of radar waveform design, and the method comprises the steps: building a mathematical expression for representing a phase-dependent non-convex quadratic optimization problem of a radar waveform based on an optimization criterion of a maximized signal to interference plus noise ratio, the radar waveform refers to a radar waveform for full-pulse forwarding type interference, and the mathematical expression is associated with a key parameter for suppressing the full-pulse forwarding type interference; solving the mathematical expression to obtain an optimal key parameter; and optimizing the radar waveform by using the optimal key parameter. According to the method, the signal to interference plus noise ratio can be further improved, the convergence performance during solving is ensured, and the false echo energy is distributed outside a true target echo energy region on the premise of not changing the true target echo characteristics, so that the suppression of the full pulse forwarding interference is realized.

Description

Background Art

[0002] As an important means of comprehensive situational awareness, radar sensors have important applications in target detection, tracking, identification, and parameter estimation. However, with the continuous development of electronic information technology, radar jamming technologies for various application scenarios have emerged in an endless stream, resulting in serious deterioration of various performances of traditional radars. With the increasing development and application of digital radio frequency memory (DFRM) technology, rapid sampling, complete retention, and on-demand forwarding of received radar signals have been achieved in engineering, making deceptive jamming based on pulse forwarding possible. In actual combat, targets such as aircraft and missiles usually carry self-defense jammers. After detecting that they are illuminated by local radars, the jammers generate multiple false target echo signals through DFRM technology and radiate them. If the enemy radar does not have the corresponding anti-jamming function, it is easy to lose the real target, which may lead to the failure of the detection mission in serious cases.

[0003] According to the specific sampling and forwarding methods, deceptive forwarding interference can be divided into intermittent sampling and forwarding interference and full pulse forwarding interference. Specifically:

[0004] 1) Intermittent sampling and forwarding jamming samples and forwards some fragments of the received enemy radar signal based on the undersampling principle, thereby achieving dense false target jamming. This process can be equivalent to the weighted synthesis of target echoes with different Doppler frequency shifts after matched filtering.

[0005] 2) Full pulse forwarding jamming first intercepts the entire pulse of the enemy radar signal, and then forwards it after a certain delay. Relative to the target echo, the full pulse forwarding jamming signal usually delays multiple (at least one) pulse repetition intervals (PRI) to enter the radar receiver, and then generates a false target near the range-Doppler unit of the real target, and finally forms deceptive jamming to the radar. The present invention mainly considers the suppression problem of full pulse forwarding jamming.

[0006] Summarizing the existing literature, the existing means of anti-forwarding interference can be divided into receiving end signal processing methods and transmitting end signal processing methods, specifically:

[0007] 1) Based on the signal processing method at the receiving end, a set of bandpass filters is constructed by utilizing the distribution difference of true and false target energy in the time-frequency dimension, and the anti-interference purpose is achieved through the segmented filtering method, such as the least squares estimation method for estimating the forwarding interference parameters.

[0008] 2) The signal processing method based on the transmitter mainly utilizes the idea of ​​radar transmission waveform design to maximize the distribution difference between the target echo energy and the interference echo energy by establishing and solving the corresponding objective function.

[0009] In recent years, with the introduction of the concept of cognitive radar, the research on radar waveform optimization design has made rapid progress. In the process of radar waveform optimization design, the optimization objective function or objective criterion is first selected according to the combat scenario of the radar system and the combat mission requirements, and the constraint conditions are determined by considering the resource limitations of the radar hardware system and the response requirements of the combat mission, so as to establish a high-dimensional constrained optimization problem. After the waveform-related optimization model is established, the mathematical theory should be selected according to the mathematical characteristics of the optimization problem for solution. From the perspective of the achieved waveform performance, the research results in radar waveform design include time domain low sidelobe waveform design, sparse spectrum waveform design, local fuzzy function shaping waveform design, transmission pattern matching waveform design, and waveform design that resists intermittent sampling forwarding interference. In order to further improve the design freedom of the optimization problem and achieve better waveform performance, some scholars have studied the joint optimization problem of radar waveform and receiving filter.

[0010] The waveform design method based on Element Pulse Coding MIMO (EPC-MIMO) is a space-time coding technology. It realizes adaptive adjustment of false target energy distribution by encoding the initial phase of pulses transmitted by different antennas within the accumulation period, and has wide application in resisting full pulse forwarding interference. Under the EPC-MIMO system, a random EPC-MIMO waveform design method is proposed in some literature. This method makes the false target energy noisy in the transmission angular frequency dimension, but the energy will be dispersed in the entire transmission angular frequency dimension; another literature proposes an EPC-MIMO waveform optimization method based on Fourier transform. This method realizes the separation of true and false targets in the transmission angular frequency by moving the false target away from the main lobe area of ​​the true target, but part of the false target energy will still leak into the detection area of ​​the true target through the side lobe.

[0011] In response to the above problems, a literature has proposed an adaptive EPC-MIMO waveform optimization method, which achieves interference suppression by moving the energy distribution of false targets to form a notch in the real target detection area. However, when using the adaptive gradient algorithm to solve the optimal coding vector, this method cannot achieve a strict decrease in the loss function value, and its convergence performance and output signal to interference plus noise ratio (SINR) gain need to be further improved. Summary of the invention

[0012] The technical problem to be solved by the present invention is to address the deficiencies of the prior art and specifically provide a radar waveform optimization method and system for resisting full pulse forwarding interference, as follows:

[0013] 1) In the first aspect, the present invention provides a radar waveform optimization method for resisting full pulse forwarding interference, and the specific technical scheme is as follows:

[0014] Based on the optimization criterion of maximizing the signal-to-interference-noise ratio, a mathematical expression of a phase-dependent non-convex quadratic optimization problem for characterizing radar waveforms is established, wherein the radar waveform refers to a radar waveform used for full pulse repeater jamming, and the mathematical expression is associated with key parameters used to suppress full pulse repeater jamming;

[0015] Solve the mathematical expression to obtain the optimal key parameters;

[0016] Optimize the radar waveform using the optimal key parameters.

[0017] On the basis of the above scheme, the radar waveform optimization method for resisting full pulse forwarding interference of the present invention can also be improved as follows.

[0018] Further, mathematical expressions are solved, including:

[0019] The mathematical expressions are solved using the conjugate gradient algorithm based on line search.

[0020] Furthermore, the process of obtaining the key parameters for suppressing full pulse forwarding interference includes:

[0021] The EPC-MIMO model is analyzed to determine the key parameters for suppressing full pulse forwarding interference.

[0022] Furthermore, the key parameter is the array element pulse code element group.

[0023] 2) In the second aspect, the present invention also provides a radar waveform optimization system for resisting full pulse forwarding interference, and the specific technical solution is as follows:

[0024] Includes: building module, solving module and optimizing module;

[0025] The module is used to establish a mathematical expression for a phase-dependent non-convex quadratic optimization problem for characterizing a radar waveform based on an optimization criterion of maximizing a signal-to-interference-to-noise ratio, wherein the radar waveform refers to a radar waveform for full pulse forwarding jamming, and the mathematical expression is associated with a key parameter for suppressing full pulse forwarding jamming;

[0026] The solution module is used to solve mathematical expressions to obtain the optimal key parameters;

[0027] The optimization module is used to optimize the radar waveform using the optimal key parameters.

[0028] On the basis of the above scheme, the radar waveform optimization system for resisting full pulse forwarding interference of the present invention can also be improved as follows.

[0029] Furthermore, the solution module is specifically used to solve the mathematical expression using a conjugate gradient algorithm based on line search.

[0030] Furthermore, it also includes a key parameter acquisition module, which is used to: analyze the EPC-MIMO model and determine the key parameters for suppressing full pulse forwarding interference.

[0031] Furthermore, the key parameter is the array element pulse code element group.

[0032] 3) In a third aspect, the present invention further provides an electronic device, comprising a processor, the processor being coupled to a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor, so that the electronic device implements any one of the above-mentioned radar waveform optimization methods for resisting full-pulse forwarding interference.

[0033] 4) In a fourth aspect, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is loaded and executed by a processor so that the computer implements any of the above-mentioned radar waveform optimization methods for resisting full-pulse forwarding interference.

[0034] The beneficial effects of the present invention are as follows:

[0035] Firstly, based on the optimization criterion of maximizing the signal-to-interference-noise ratio, a mathematical expression of a phase-related non-convex quadratic optimization problem for characterizing radar waveforms is established and solved. Then, the radar waveform is optimized according to the optimal key parameters obtained by the solution. This can further improve the signal-to-interference-noise ratio and ensure the convergence performance of the solution. Without changing the echo characteristics of the true target, the energy of the false echo is distributed outside the energy area of ​​the true target echo, thereby achieving the suppression of full-pulse forwarding interference. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0037] Figure 1 A schematic flow chart of a radar waveform optimization method for resisting full-pulse forwarding interference according to an embodiment of the present invention;

[0038] Figure 2 is the change curve of objective function value and gradient norm value;

[0039] Figure 3 is the optimized phase value;

[0040] Figure 4 Transmit and receive two-dimensional angular frequency spectrum for real target;

[0041] Figure 5 One of the angular frequency spectra of the false target;

[0042] Figure 6 This is the second angular frequency spectrum of the false target;

[0043] Figure 7 This is the third angular frequency spectrum of the false target;

[0044] Figure 8 The output SINR changes with the number of false targets;

[0045] Fig. 9 The output SINR value changes with the number of pulse delays;

[0046] Fig.10 A schematic diagram of the structure of a radar waveform optimization system for resisting full-pulse forwarding interference according to an embodiment of the present invention;

[0047] Fig.11 The figure is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0049] like Figure 1 As shown, a radar waveform optimization method for resisting full pulse forwarding interference according to an embodiment of the present invention comprises the following steps:

[0050] S1. Based on the optimization criterion of maximizing the signal-to-interference-noise ratio, a mathematical expression of a phase-dependent non-convex quadratic optimization problem for characterizing a radar waveform is established, wherein the radar waveform refers to a radar waveform for full pulse repeater jamming, and the mathematical expression is associated with key parameters for suppressing full pulse repeater jamming;

[0051] S2. Solve the mathematical expression to obtain the optimal key parameters;

[0052] S3. Optimize the radar waveform using the optimal key parameters.

[0053] Optionally, in S2, solving the mathematical expression includes: solving the mathematical expression using a conjugate gradient algorithm based on line search.

[0054] Optionally, in the above technical solution, the process of acquiring key parameters for suppressing full pulse forwarding interference includes: analyzing the EPC-MIMO model to determine the key parameters for suppressing full pulse forwarding interference.

[0055] Optionally, in the above technical solution, the key parameter is an array element pulse codeword group, and the optimal key parameter is an optimal array element pulse codeword group.

[0056] The present invention is described by the following examples, including:

[0057] S11. Analyze the EPC-MIMO model and determine the key parameters for suppressing full pulse forwarding interference. The specific implementation process is as follows:

[0058] Consider the number of receiving antennas is N r , the number of transmitting antennas is N t For a co-located MIMO radar with an array element spacing of d, under the assumption that the target is in the far field, the nth t The mth pulse signal of the transmitting antenna It can be expressed as:

[0059]

[0060] In formula (1), j represents the imaginary unit, n t ∈{1,…,N t},n t represents the transmit antenna index, m∈{1,…,M}, m represents the waveform index, T r Indicates the pulse repetition period PRI, T p Indicates the transmit pulse width, f 0 represents the carrier frequency, rect(·) represents the gate signal, Indicates the nth t The baseband signals of the transmitting antennas are assumed to meet the orthogonality condition, and t represents the time. In addition:

[0061]

[0062] Indicates the nth t The additional phase of the m-1th pulse radiated by the transmitting antenna, φ m Indicates the phase value of the pulse.

[0063] Assume that there is a far-field target at a distance r from the MIMO radar, and its azimuth and velocity relative to the antenna array are θ and v respectively. t The mth pulse s is transmitted by the transmitting antenna m (t) is:

[0064]

[0065] In formula (3), (·) T represents the transpose operation, then the nth r The echo signal received by the receiving antenna can be expressed as:

[0066]

[0067] In formula (4), σ 0 It represents the echo complex coefficient, which is determined by the electromagnetic wave transmission characteristics and the target scattering characteristics. f(θ) = dcos(θ) / λ, which represents the functional relationship between the transmitting and receiving angular frequencies. λ represents the electromagnetic wave wavelength, λ = c / f 0 , c represents the electromagnetic wave propagation speed, τ represents the echo delay, τ = 2(r-vt) / c, a(θ) represents the emission flow vector corresponding to the azimuth θ, which is generally calculated by formula (5):

[0068]

[0069] Through carrier frequency removal and channel matching processing, and taking advantage of the orthogonality between the waveforms transmitted by each channel, the nth r The echo signal received by the nth receiving antenna passes through t The output result after channel matching It can be expressed as:

[0070]

[0071] In formula (6), p represents the number of PRTs that the target echo delays entering the radar receiver, γ(τ-pT r ) represents the autocorrelation function between the signals radiated by different antennas.

[0072] Furthermore, for N r The echo signals of the receiving antennas are processed by multi-channel matching respectively, and we can get N t N r The processing result y of the receiving channel m (τ), which can be specifically expressed as:

[0073]

[0074] In formula (7), represents the Kronecker product, ⊙ represents the Hadamard product, φ represents the array element pulse phase symbol group, and b(θ) is the receiving flow vector corresponding to the azimuth angle θ, which can be expressed as:

[0075]

[0076] Combining the above content, it can be seen that the transmit and receive flow vector c(θ, p) corresponding to the echo signal can be expressed as formula (9):

[0077]

[0078] According to formula (9), the transmit and receive flow vector c(θ, p) is determined by the azimuth angle θ, the array element pulse code element group φ, and the number of PRTs p of the target echo delay entering the radar receiver. For real targets, they are often located within the maximum unambiguous distance range, at which time 0<τ<T r When p is 0, the corresponding transmit and receive flow vector c s (θ s ) is expressed as:

[0079]

[0080] In formula (10), θ s represents the target direction. I The false target at the azimuth angle and delayed by p PRIs has a receiving and sending flow vector c I (θ I ,p) is expressed as:

[0081]

[0082] From the above analysis, we can see that since the real target transmitting angular frequency and receiving angular frequency are both f(θ s ), its echo energy is concentrated on the diagonal of the transmit-receive two-dimensional angular frequency spectrum; since the false target transmit angular frequency is not equal to the receive angular frequency and is related to φ, the false target echo energy is diffusely distributed in the receive angular frequency dimension. Therefore, the true and false targets can be separated by designing φ, thereby realizing the anti-interference function.

[0083] S12. Based on the optimization criterion of maximizing the signal-to-interference-noise ratio, a mathematical expression for a non-convex quadratic optimization problem for characterizing the phase correlation of radar waveforms is established. Specifically:

[0084] Assume that there is an angle θ s , the echo power is The far-field target generates K false targets when escaping radar detection, with azimuth angles of θ I,1 ,…,θ I,K , the power is The number of delayed pulses is p 1 ,…,p K Assume that the system noise n is irrelevant and has a mean of 0 and a variance of R n The cyclically symmetric complex Gaussian distribution of is:

[0085]

[0086] In formula (12), represents the noise power, and I represents the unit array. Then the output SINR of the radar echo after waveform shaping at the target direction can be expressed as:

[0087]

[0088] In formula (13), (·) H represents the conjugate transpose operation, R s represents the target covariance matrix, R I Represents the interference covariance matrix, which can be specifically expressed as:

[0089]

[0090] When the beam processing weight w takes the value c s (θ s ), formula (13) can be re-expressed as:

[0091]

[0092] Under the maximization SINR criterion (optimization criterion for maximizing signal to interference noise ratio), the waveform optimization problem considered in the present invention can be expressed as formula (17):

[0093]

[0094] Since the signal component and the noise component in formula (17) are constants independent of φ, the above optimization problem can be equivalently expressed as formula (18):

[0095]

[0096] Furthermore, g(φ) can be expanded as:

[0097]

[0098] In formula (19), |·| 2 represents the square of the modulus,

[0099] Further, And let Λ=diag(V 1 ,…,V K ), then formula (19) can be written in the following quadratic form:

[0100] g(φ)=(e -jPφ ) H Λe -jPφ (20)

[0101] Therefore, formula (18) can be expressed as:

[0102]

[0103] Formula (21) is the mathematical expression of the non-convex quadratic optimization problem used to characterize the phase correlation of radar waveform.

[0104] S13, using a conjugate gradient algorithm based on line search to solve the mathematical expression, specifically:

[0105] For formula (21), a literature has proposed an adaptive gradient solution method, which minimizes the objective function by continuously reducing the descent step size during the iteration process, but cannot guarantee that the objective function value decreases monotonically at each iteration. In this regard, the present invention uses a conjugate gradient algorithm based on line search to solve this problem. For the smooth function f(x), the standard gradient descent algorithm starts from the initial random point Start the following iterative process:

[0106] x k+1 =x k +μ k d k (twenty two)

[0107] In formula (22), k ≥ 0 and k is an integer, d k Indicates the descending direction, μ k Represents the search step size. Different descent direction selection strategies will produce different gradient-based optimization algorithms, specifically:

[0108] When k =-Gradf(x)+β k-1 d k-1 When , the resulting gradient descent method is the conjugate gradient method. Among them, Gradf(x) represents the gradient of f(x), β k-1 represents the gradient weighted parameter. Accordingly, its iterative process can be further expressed as:

[0109] x k+1 =x k +μ k (-Gradf(x)+β k-1 d k-1 ) (twenty three)

[0110] For the objective function g(φ), when the conjugate gradient method is used to iteratively find its minimum value, the descent direction at each iteration is expressed as:

[0111] d k = -Gradg(φ k )+βk-1 d k-1 (twenty four)

[0112] In formula (24), the parameter β k-1 Select according to the Polark-Ribière parameter rule, Gradg(φ k ) represents the gradient of the objective function at the kth iteration.

[0113] Combining the above, the iterative process of solving the minimum value of the objective function g(φ) can be expressed as:

[0114] φk +1 =φ k -μ k (Gradg(φ k )-β k-1 d k-1 ) (25)

[0115] In formula (25), the function gradient Gradg(φ) can be specifically calculated as:

[0116]

[0117] The function gradient Gradg(φ) is used to calculate the gradient of the objective function at any iteration.

[0118] In addition, in order to ensure that the objective function g(φ) is monotonically non-increasing at each iteration, the search step size μ is determined by line search. k The implementation process of the specific search method can be expressed as the pseudo code in Table 1, where <·> represents the inner product operation. In Table 1, when the decrease value of the objective function g(φ) is less than the preset threshold, the step size μ is reduced. k , until the loop end condition is met. Among them, the decrease value of the objective function g(φ) is obtained by Calculated, the preset threshold is obtained by The calculation shows that the loop end condition is:

[0119] Table 1:

[0120]

[0121] In combination with the above content, the specific implementation process of the conjugate gradient algorithm based on line search of the present invention is the pseudo code in Table 2.

[0122] Table 2:

[0123]

[0124]

[0125] Next, the proposed method is verified through simulation experiments. Specifically:

[0126] In the experiment, the MIMO antenna array element spacing d is set to 0.15m, the number of transmitting and receiving antenna elements M and N are both set to 16, and the carrier frequency f 0 Set to 1GHz, target azimuth angle θ s =90°. The number of false interference targets K = 3, and the azimuth angle of the interference source θ I,1 ,θ I,2 With θ I,3 They are 80°, 90° and 100° respectively, and the pulse delay numbers are 3, 4 and 5. The experiments were carried out under the Manopt framework.

[0127] First, the convergence performance of the proposed algorithm is verified. In the experiment, the maximum number of iterations is set to 100, and the parameter δ in the iteration stop criterion is set to 10. -3 In addition, the signal to noise ratio (SNR) and the signal to interference ratio (SIR) corresponding to the three false targets are both 0dB.

[0128] Figure 2 The graph shows the change curve of the objective function value and the gradient norm value with the number of iterations. As can be seen from the figure, as the number of iterations increases, the gradient norm value shows an overall downward trend, and the iteration stops when the convergence condition is reached. At the same time, observing the objective function value change curve, it can be seen that as the iteration continues, the objective function value shows a monotonically decreasing characteristic, which further verifies the effectiveness of the algorithm proposed in the present invention.

[0129] Figure 3 and Figure 4 The optimized coding phase value and its corresponding target transmission-reception two-dimensional angular frequency spectrum are shown respectively. Figure 3 It can be seen that the optimized phase code values ​​are all between 0 and 2π, which meets the previous assumptions about φ. Since the receiving flow vector of the real target does not have a modulation term related to pulse delay, its transmitting and receiving angular frequencies are both f(θ s ), so its energy should be concentrated in the diagonal part of the two-dimensional angular spectrum. Figure 4 It can be seen that the target two-dimensional angular frequency spectrum is concentrated in the center of the image and is above the diagonal line. The experimental results are consistent with expectations.

[0130] Figure 5 is one of the angular frequency spectra of the false target, Figure 6 This is the second angular frequency spectrum of the false target. Figure 7 This is the third angular frequency spectrum of the false target. Figure 5 , Figure 6 and Figure 7Specifically, the transmit-receive two-dimensional angular frequency spectrum of the false target with three parameters is shown. Figure 5 , Figure 6 and Figure 7 The area defined by the rectangular box in is the main range of the energy distribution of the real target. Since the emission flow vectors of the three false targets are a(θ I,k )⊙exp(-jp k φ) and the receiving flow vector b(θ I,k ) are not equal, so its energy distribution peak will deviate from the diagonal of the two-dimensional angular spectrum and show a certain translation characteristic on the receiving angular frequency axis. Observing the three spectra, it can be seen that the experimental results are consistent with the theoretical analysis. Figure 4 , Figure 5 , Figure 6 and Figure 7 It can be seen from the rectangular box area in the figure that the optimized phase code group makes the energy distribution peak of the false target avoid the target peak area, which makes it possible to achieve cognitive anti-interference through digital beamforming technology in the future.

[0131] In order to further verify the robustness of the proposed method, the present invention further explores the output SINR performance under different numbers of false targets and different numbers of pulse delays.

[0132] First, the influence of the number of false targets on the output SINR value is explored. In the experimental process, it is assumed that the target azimuth is 90°, the number of false targets is K, and they are randomly distributed in the angle range of 80° to 100°. The pulse delay number of all false targets is set to 3, the input SIR is set to -20dB, and the maximum number of iterations is set to 50.

[0133] Figure 8 The output SINR value changes with the number of false targets. As can be seen from the figure, as the number of false targets gradually increases, the output SINR based on the conjugate gradient algorithm and the output SINR based on the adaptive gradient algorithm both show a downward trend. It is worth noting that compared with the adaptive gradient algorithm, the method proposed in the present invention can not only achieve a higher output SINR gain, but also has better robustness.

[0134] The present invention further explores the influence of different pulse delay numbers on the output SINR value. During the experiment, the real target azimuth is set to 90°, and K multiple false targets are randomly distributed in the angle range of 80° to 100°, and their respective pulse delay numbers are 1, 2, ..., K', K'=K. Fig. 9 The output SINR value changes with the pulse delay number. As can be seen from the figure, with the gradual increase of the pulse delay number, the output SINR values ​​of the two algorithms show a downward trend. In addition, compared with the adaptive gradient algorithm, the method proposed in the present invention has certain advantages in output SINR gain value and robustness.

[0135] The present invention aims at the problem of suppressing the main lobe full pulse forwarding interference. Under the EPC-MIMO waveform system, the present invention proposes a phase code group optimization method based on the line search conjugate gradient method. The method first establishes a quadratic optimization problem related to the waveform phase based on the optimization criterion of maximizing the signal to interference plus noise ratio (SINR). Then, by solving the optimal array element pulse code element group, the phase of the radar waveform is optimized according to the optimal array element pulse code element group. The proposed method makes the false echo energy distributed outside the true target echo energy area without changing the true target echo characteristics, thereby realizing the suppression of forwarding deception interference, and effectively solves the problem that the objective function in the adaptive gradient descent algorithm cannot converge monotonically. The simulation experimental results show that the method proposed by the present invention can not only effectively suppress the interference of multiple false targets generated by the full pulse forwarding jammer, but also has better SINR gain performance and better robustness than the classical method.

[0136] In the above embodiments, although the steps are numbered S1, S2, etc., these are only specific embodiments given by the present invention. Those skilled in the art may adjust the execution order of S1, S2, etc. according to actual conditions, which is also within the protection scope of the present invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0137] like Fig.10 As shown, a radar waveform optimization system 200 for resisting full pulse forwarding interference according to an embodiment of the present invention includes: an establishment module 201, a solution module 202 and an optimization module 203;

[0138] The establishment module 201 is used to: establish a mathematical expression of a phase-related non-convex quadratic optimization problem for characterizing a radar waveform based on an optimization criterion of maximizing a signal-to-interference-noise ratio, wherein the radar waveform refers to a radar waveform for full pulse forwarding interference, and the mathematical expression is associated with a key parameter for suppressing full pulse forwarding interference;

[0139] The solution module 202 is used to: solve the mathematical expression to obtain the optimal key parameters;

[0140] The optimization module 203 is used to optimize the radar waveform using the optimal key parameters.

[0141] Optionally, in the above technical solution, the solution module 202 is specifically used to solve the mathematical expression using a conjugate gradient algorithm based on line search.

[0142] Optionally, the above technical solution further includes a key parameter acquisition module, which is used to: analyze the EPC-MIMO model to determine key parameters for suppressing full pulse forwarding interference.

[0143] Optionally, in the above technical solution, the key parameter is an array element pulse code element group.

[0144] It should be noted that the beneficial effects of the radar waveform optimization system 200 for resisting full pulse forwarding interference provided by the above embodiment are the same as the beneficial effects of the radar waveform optimization method for resisting full pulse forwarding interference, which will not be described in detail here. In addition, when the system provided by the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the system can be divided into different functional modules according to actual conditions to complete all or part of the functions described above. In addition, the system and method embodiments provided by the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be described in detail here.

[0145] like Fig.11 As shown, an electronic device 300 according to an embodiment of the present invention includes a processor 320, the processor 320 is coupled to a memory 310, and the memory 310 stores at least one computer program 330, and the at least one computer program 330 is loaded and executed by the processor 320, so that the electronic device 300 implements any of the above-mentioned radar waveform optimization methods for resisting full pulse forwarding interference, specifically:

[0146] The electronic device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors 320 (Central Processing Units, CPU) and one or more memories 310, wherein at least one computer program 330 is stored in the one or more memories 310, and the at least one computer program 330 is loaded and executed by the one or more processors 320, so that the electronic device 300 implements any radar waveform optimization method for resisting full pulse forwarding interference provided in the above embodiments. Of course, the electronic device 300 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output. The electronic device 300 may also include other components for realizing the functions of the device, which will not be repeated here. The electronic device may specifically be a computer, etc.

[0147] A computer-readable storage medium according to an embodiment of the present invention stores at least one computer program, and the at least one computer program is loaded and executed by a processor so that a computer implements any of the above-mentioned radar waveform optimization methods for resisting full-pulse forwarding interference.

[0148] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0149] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device performs any of the above-mentioned radar waveform optimization methods for resisting full pulse forwarding interference.

[0150] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present invention can be specifically implemented in the following forms, namely: it can be complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software. The present invention is generally referred to as a "circuit", "module" or "system". In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0151] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0152] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A radar waveform optimization method for resisting full pulse forwarding interference, characterized in that: include: Based on the optimization criterion of maximizing the signal-to-interference-noise ratio, a mathematical expression of a phase-dependent non-convex quadratic optimization problem for characterizing a radar waveform is established, wherein the radar waveform refers to a radar waveform for full pulse repeater jamming, and the mathematical expression is associated with a key parameter for suppressing full pulse repeater jamming; Solving the mathematical expression to obtain the optimal key parameters; The radar waveform is optimized using the optimal key parameters.

2. The radar waveform optimization method for resisting full pulse forwarding interference according to claim 1 is characterized in that: Solving the mathematical expression includes: The mathematical expression is solved using a conjugate gradient algorithm based on line search.

3. The radar waveform optimization method for resisting full pulse forwarding interference according to claim 1 is characterized in that: The process of obtaining the key parameters for suppressing full pulse forwarding interference includes: The EPC-MIMO model is analyzed to determine the key parameters for suppressing full pulse forwarding interference.

4. The radar waveform optimization method for resisting full pulse forwarding interference according to claim 3 is characterized in that: The key parameter is the array element pulse code element group.

5. A radar waveform optimization system for resisting full pulse forwarding interference, characterized in that: include: Building modules, solving modules and optimizing modules; The establishment module is used to: establish a mathematical expression for a phase-related non-convex quadratic optimization problem for characterizing a radar waveform based on an optimization criterion of maximizing a signal-to-interference-noise ratio, wherein the radar waveform refers to a radar waveform for full pulse forwarding interference, and the mathematical expression is associated with a key parameter for suppressing full pulse forwarding interference; The solution module is used to: solve the mathematical expression to obtain the optimal key parameters; The optimization module is used to optimize the radar waveform using the optimal key parameters.

6. A radar waveform optimization system for resisting full pulse forwarding interference according to claim 5, characterized in that: The solution module is specifically used to solve the mathematical expression using a conjugate gradient algorithm based on line search.

7. The radar waveform optimization system for resisting full pulse forwarding interference according to claim 5 is characterized in that: It also includes a key parameter acquisition module, which is used to analyze the EPC-MIMO model and determine the key parameters for suppressing full pulse forwarding interference.

8. The radar waveform optimization system for resisting full pulse forwarding interference according to claim 7 is characterized in that: The key parameter is the array element pulse code element group.

9. An electronic device, characterized in that: The electronic device includes a processor, the processor is coupled to a memory, at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor so that the electronic device implements a radar waveform optimization method for resisting full-pulse repeater interference as described in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: At least one computer program is stored in the computer-readable storage medium, and the at least one computer program is loaded and executed by the processor so that the computer implements the radar waveform optimization method for resisting full-pulse forwarding interference as described in any one of claims 1 to 4.

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