Code agile radar clutter suppression method and apparatus

Abstract

The application discloses a code agile radar clutter suppression method and device, and relates to the technical field of radar signal processing, and comprises the following steps: performing frequency down-conversion, pulse compression and frequency domain transformation operations on echo data in one coherent processing interval to obtain an echo snapshot vector; determining a clutter speed interval corresponding to the echo data, constructing a corresponding modulation guide vector, integrating the clutter speed interval, constructing a modulation clutter correlation matrix at each frequency sampling point, performing eigenvalue decomposition on the modulation clutter correlation matrix, combining a power constraint, and generating a corresponding clutter orthogonal projection matrix; performing frequency point projection suppression on the echo snapshot vector by using the clutter orthogonal projection matrix to obtain a clutter suppression frequency domain output, performing inverse frequency domain transformation, coherent accumulation and detection processing on the clutter suppression frequency domain output, and generating a target detection result corresponding to a target code agile radar. Thus, the problem that a traditional slow time clutter suppression method is mismatched due to code agility in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of radar signal processing technology, and in particular to a method and apparatus for suppressing clutter in pattern-agile radar. Background Technology

[0002] Traditional pulse Doppler radars typically utilize the relatively stable phase relationship between pulses within a coherent processing interval to cancel clutter through moving target indication, moving target detection, or conventional subspace suppression methods. However, the aforementioned traditional processing chain usually implies a key premise: that the transmitted waveforms of each pulse within the coherent processing interval are basically consistent, or that the main and sidelobe structures of each pulse in the range dimension are approximately consistent after matched filtering. Only when this premise is met can the statistical structure of clutter in the slow time dimension be stably characterized as a low-Doppler subspace, thereby achieving suppression through high-pass filtering or subspace projection.

[0003] To enhance their low-intercept, anti-reconnaissance, anti-spoofing, and anti-active suppression capabilities, pattern-agile radars typically actively switch the intra-pulse coding of different pulses within the coherent processing interval. While this design improves waveform countermeasures, it introduces differences in the baseband waveforms of different pulses, leading to inconsistencies in the range sidelobe structure after matched filtering, resulting in range sidelobe modulation. This range sidelobe modulation introduces amplitude and phase fluctuations caused by waveform modulation in the slow time dimension, violating the inter-pulse consistency assumption upon which traditional slow-time processing relies.

[0004] In low-altitude target detection scenarios, the above problems become even more prominent. Ground clutter has strong energy and continuous distribution, and low-speed, weak targets are often located in close range cells and close Doppler regions with the clutter. Once the code agility causes a mismatch between the traditional suppression operator and the statistical structure of the real clutter, the clutter residue will be further amplified in the subsequent coherent accumulation process, thereby raising the detection threshold and masking low-speed, weak targets.

[0005] Currently, existing technologies can solve the clutter suppression problem under code agility conditions through mismatch filtering, code design compensation, and joint waveform reception optimization. These methods can reduce the range sidelobe modulation effect to a certain extent, but often at the cost of sacrificing some main lobe gain or target energy. Furthermore, the processing performance depends on the specific code set, filter design criteria, and parameter matching accuracy.

[0006] Furthermore, existing technologies mostly mitigate code pattern differences from the perspective of receiver filter design, but rarely explicitly characterize the modulation effect of waveform frequency domain priors on clutter statistical structure from the perspective of clutter subspace modeling. When strong clutter and weak targets coexist, if the modeling method with completely consistent inter-pulse responses is still used, problems such as large clutter subspace estimation bias, unreasonable allocation of projection degrees of freedom, and excessive loss of target components are likely to occur.

[0007] In summary, the code agility in existing technologies leads to a mismatch with traditional slow-time clutter suppression methods, which urgently needs to be addressed. Summary of the Invention

[0008] This application provides a method and apparatus for suppressing clutter in radar with agile code patterns, in order to solve the problem of mismatch in traditional slow-time clutter suppression methods caused by code agility in the prior art.

[0009] The first aspect of this application provides a clutter suppression method for pattern-agile radar, comprising the following steps: performing down-conversion, pulse compression, and frequency domain transformation operations on echo data of a target pattern-agile radar within a coherent processing interval to obtain a corresponding echo snapshot vector; determining the clutter velocity range corresponding to the echo data, constructing a corresponding modulation guidance vector based on the clutter velocity range, integrating the clutter velocity range based on the modulation guidance vector to construct a modulation clutter correlation matrix at each frequency sampling point, performing eigenvalue decomposition on the modulation clutter correlation matrix, and generating a corresponding clutter orthogonal projection matrix by combining a preset power constraint; performing a preset frequency point projection suppression operation on the echo snapshot vector using the clutter orthogonal projection matrix to obtain a clutter suppression frequency domain output, and performing a preset inverse frequency domain transformation, coherent accumulation, and detection processing on the clutter suppression frequency domain output to generate a target detection result corresponding to the target pattern-agile radar.

[0010] Optionally, in one embodiment of this application, the step of performing down-conversion, pulse compression, and frequency domain transformation operations on the echo data of the target pattern agile radar within a coherent processing interval to obtain the corresponding echo snapshot vector includes: transmitting multiple pulse signals to the target under test through the target pattern agile radar within the coherent processing interval, receiving the echo data corresponding to the multiple pulse signals, and performing preset down-conversion and pulse compression processing on the echo data to obtain the corresponding compressed signal; performing Fourier transform on the compressed signal along the first target time dimension to obtain the echo snapshot vector at each frequency sampling point.

[0011] Optionally, in one embodiment of this application, determining the clutter velocity range corresponding to the echo data, constructing a corresponding modulation guidance vector based on the clutter velocity range, integrating the clutter velocity range based on the modulation guidance vector to construct a modulation clutter correlation matrix at each frequency sampling point, performing eigenvalue decomposition on the modulation clutter correlation matrix, and generating a corresponding clutter orthogonal projection matrix in conjunction with a preset power constraint, includes: acquiring the baseband transmit waveform and transmit carrier frequency corresponding to the multiple pulse signals, and constructing a corresponding waveform spectrum vector based on the baseband transmit waveform; acquiring the radial velocity and pulse repetition interval of the target under test, determining a corresponding velocity guidance vector based on the transmit carrier frequency, the radial velocity, and the pulse repetition interval, and calculating... The Hadamard product between the velocity guidance vector and the waveform spectrum vector is used to determine the modulation guidance vector. The modulation guidance vector is used to integrate the velocity range where clutter is located in the echo data to construct the modulation clutter correlation matrix at each frequency sampling point. Eigenvalue decomposition is performed on the modulation clutter correlation matrix to obtain the corresponding eigenvalue decomposition result. Based on the power constraint, the effective rank of the modulation clutter correlation matrix is ​​determined, and multiple principal eigenvectors of the modulation clutter correlation matrix are obtained according to the eigenvalue decomposition result. The effective rank and the multiple principal eigenvectors are used to construct the corresponding clutter orthogonal projection matrix, wherein the power constraint is that the residual clutter power of the modulation clutter correlation matrix is ​​lower than the noise power.

[0012] Optionally, in one embodiment of this application, the mathematical expression for the clutter suppression frequency domain output is:

[0013] in, This represents the clutter suppression frequency domain output; Represents frequency The clutter orthogonal projection matrix at the location; Represents frequency The echo snapshot vector at that location.

[0014] Optionally, in one embodiment of this application, the mathematical expression for the modulation clutter correlation matrix is:

[0015] in, Represents frequency The modulation clutter correlation matrix at the location; This represents the lower limit of the velocity range in which the clutter exists; This represents the upper limit of the velocity range in which the clutter is located; Represents frequency Modulation guidance vector at the location; Represents frequency The conjugate transpose of the modulation guidance vector at that location; Indicates the conjugate transpose of the orientation quantity; Indicates radial velocity.

[0016] A second aspect of this application provides a clutter suppression device for pattern-agile radar, comprising: a preprocessing module, used to perform down-conversion, pulse compression, and frequency domain transformation operations on echo data of a target pattern-agile radar within a coherent processing interval to obtain a corresponding echo snapshot vector; an eigenvalue decomposition module, used to determine the clutter velocity range corresponding to the echo data, construct a corresponding modulation guidance vector based on the clutter velocity range, integrate the clutter velocity range based on the modulation guidance vector to construct a modulation clutter correlation matrix at each frequency sampling point, perform eigenvalue decomposition on the modulation clutter correlation matrix, and generate a corresponding clutter orthogonal projection matrix in combination with a preset power constraint; and a clutter suppression module, used to perform preset frequency point projection suppression operations on the echo snapshot vector using the clutter orthogonal projection matrix to obtain a clutter suppression frequency domain output, and perform preset inverse frequency domain transformation, coherent accumulation, and detection processing on the clutter suppression frequency domain output to generate a target detection result corresponding to the target pattern-agile radar.

[0017] Optionally, in one embodiment of this application, the preprocessing module includes: a receiving unit, configured to transmit multiple pulse signals to the target under test via the target pattern agile radar within a coherent processing interval, and receive echo data corresponding to the multiple pulse signals, and perform preset down-conversion and pulse compression processing on the echo data to obtain a corresponding compressed signal; and a transform unit, configured to perform Fourier transform on the compressed signal along a first target time dimension to obtain the echo snapshot vector at each frequency sampling point.

[0018] Optionally, in one embodiment of this application, the eigenvalue decomposition module includes: a first construction unit, configured to acquire the baseband transmission waveform and transmission carrier frequency corresponding to the plurality of pulse signals, and construct a corresponding waveform spectrum vector based on the baseband transmission waveform; a calculation unit, configured to acquire the radial velocity and pulse repetition interval of the target under test, to determine the corresponding velocity guidance vector based on the transmission carrier frequency, the radial velocity, and the pulse repetition interval, and to calculate the Hadamard product between the velocity guidance vector and the waveform spectrum vector, and to determine the modulation guidance vector through the Hadamard product; and an integration unit, configured to utilize the modulation guidance vector The velocity range containing clutter in the echo data is integrated to construct a modulation clutter correlation matrix at each frequency sampling point, and eigenvalue decomposition is performed on the modulation clutter correlation matrix to obtain the corresponding eigenvalue decomposition result; the second construction unit is used to determine the effective rank of the modulation clutter correlation matrix based on the power constraint, and obtain multiple principal eigenvectors of the modulation clutter correlation matrix according to the eigenvalue decomposition result, so as to construct the corresponding clutter orthogonal projection matrix using the effective rank and the multiple principal eigenvectors, wherein the power constraint is that the residual clutter power of the modulation clutter correlation matrix is ​​lower than the noise power.

[0019] Optionally, in one embodiment of this application, the mathematical expression for the clutter suppression frequency domain output is:

[0020] in, This represents the clutter suppression frequency domain output; Represents frequency The clutter orthogonal projection matrix at the location; Represents frequency The echo snapshot vector at that location.

[0021] Optionally, in one embodiment of this application, the mathematical expression for the modulation clutter correlation matrix is:

[0022] in, Represents frequency The modulation clutter correlation matrix at the location; This represents the lower limit of the velocity range in which the clutter exists; This represents the upper limit of the velocity range in which the clutter is located; Represents frequency Modulation guidance vector at the location; Represents frequency The conjugate transpose of the modulation guidance vector at that location; Indicates the conjugate transpose of the orientation quantity; Indicates radial velocity.

[0023] A third aspect of this application 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 pattern-agile radar clutter suppression method as described in the above embodiments.

[0024] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described pattern-agile radar clutter suppression method.

[0025] A fifth aspect of this application provides a computer program product, including a computer program that is executed to implement the above-described pattern-agile radar clutter suppression method.

[0026] Therefore, the embodiments of this application have the following beneficial effects: The embodiments of this application obtain the corresponding echo snapshot vector by performing down-conversion, pulse compression, and frequency domain transformation operations on the echo data of the target pattern agile radar within a coherent processing interval; determine the clutter velocity range corresponding to the echo data, construct the corresponding modulation guidance vector according to the clutter velocity range, and integrate the clutter velocity range based on the modulation guidance vector to construct the modulation clutter correlation matrix at each frequency sampling point; perform eigenvalue decomposition on the modulation clutter correlation matrix, and generate the corresponding clutter orthogonal projection matrix by combining it with a preset power constraint; use the clutter orthogonal projection matrix to perform preset frequency point projection suppression operation on the echo snapshot vector to obtain the clutter suppressed frequency domain output; and perform preset inverse frequency domain transformation, coherent accumulation, and detection processing on the clutter suppressed frequency domain output to generate the target detection result corresponding to the target pattern agile radar. This application can effectively suppress clutter components by explicitly writing the inter-pulse waveform difference into the frequency domain guidance vector, constructing a modulation clutter correlation matrix that matches the actual pattern, and adaptively generating an orthogonal projection matrix based on the eigenvalue distribution. This solves the problem of mismatch in traditional slow-time clutter suppression methods caused by code agility in existing technologies.

[0027] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0028] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a pattern-agile radar clutter suppression method provided according to an embodiment of this application; Figure 2 A schematic diagram of a dataset usage path is provided for one embodiment of this application; Figure 3 This is an example diagram of a pattern-agile radar clutter suppression device according to an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0029] Among them, 10-code-type agile radar clutter suppression device, 100-preprocessing module, 200-eigenvalue decomposition module, 300-clutter suppression module, 401-memory, 402-processor, and 403-communication interface. Detailed Implementation

[0030] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0031] The following describes a clutter suppression method and apparatus for pattern-agile radar according to embodiments of this application with reference to the accompanying drawings. Addressing the problems mentioned in the background art, this application provides a clutter suppression method for pattern-agile radar. In this method, the echo data of the target pattern-agile radar within a coherent processing interval is down-converted, pulse-compressed, and frequency-domain transformed to obtain the corresponding echo snapshot vector; the clutter velocity range corresponding to the echo data is determined, and a corresponding modulation guidance vector is constructed based on the clutter velocity range. The modulation guidance vector is then integrated over the clutter velocity range to construct the modulation clutter correlation matrix at each frequency sampling point. The modulation clutter correlation matrix is ​​then subjected to eigenvalue decomposition, and combined with a preset power constraint, a corresponding clutter orthogonal projection matrix is ​​generated. The clutter orthogonal projection matrix is ​​used to perform a preset frequency point projection suppression operation on the echo snapshot vector to obtain a clutter-suppressed frequency domain output. A preset inverse frequency domain transformation, coherent accumulation, and detection processing are then performed on the clutter-suppressed frequency domain output to generate the target detection result corresponding to the target pattern-agile radar. This application can directly utilize prior information in the frequency domain of the pattern-agile waveform to construct a modulation clutter subspace without relying on inter-pulse waveform consistency, and perform projection suppression, thus balancing clutter suppression capability, target preservation capability, and engineering implementation complexity. This solves the problem of mismatch in traditional slow-time clutter suppression methods caused by pattern agility in existing technologies.

[0032] Specifically, Figure 1 This is a flowchart illustrating a pattern-agile radar clutter suppression method provided in an embodiment of this application.

[0033] like Figure 1As shown, the clutter suppression method for this code-agile radar includes the following steps: In step S101, the echo data of the target code agile radar within one coherent processing interval is subjected to down-conversion, pulse compression, and frequency domain transformation operations to obtain the corresponding echo snapshot vector.

[0034] The embodiments of this application first perform down-conversion, pulse compression, and frequency domain transformation on the echo data within a coherent processing interval to obtain the echo snapshot vector expanded along the pulse dimension at each frequency sampling point, thereby providing reliable data support for clutter suppression in the realization of agile radar. Optionally, in one embodiment of this application, down-conversion, pulse compression, and frequency domain transformation operations are performed on the echo data of the target pattern agile radar within a coherent processing interval to obtain the corresponding echo snapshot vector. This includes: transmitting multiple pulse signals to the target under test through the target pattern agile radar within a coherent processing interval, receiving the echo data corresponding to the multiple pulse signals, and performing preset down-conversion and pulse compression processing on the echo data to obtain the corresponding compressed signal; performing Fourier transform on the compressed signal along the first target time dimension to obtain the echo snapshot vector at each frequency sampling point.

[0035] In actual implementation, the embodiments of this application may set a coherent processing interval for transmission. The pulse, the first The transmission carrier frequency of each pulse is The baseband transmit waveform is Then the first The transmitted signal of a pulse can be represented as:

[0036] in, The pulse number; For fast-time sampling variables; Indicates the first The baseband encoded waveform used for each pulse; j It represents the imaginary unit.

[0037] When the initial distance of the target to be measured is Radial velocity is The pulse repetition interval is At that time, under the approximate condition of stopping the jump, the first The down-conversion target echo corresponding to each pulse can be expressed as:

[0038] in, Indicates the target scattering coefficient; It represents the speed of light.

[0039] It is understandable that the above expression shows that under the condition of code agility, the difference between pulses is not only reflected in the phase change caused by velocity, but also explicitly reflected in the waveforms of each pulse. The difference in frequency domain response.

[0040] Secondly, embodiments of this application can perform Fourier transform on the down-converted target echo, and the target echo at the frequency... The expression at the location is:

[0041] in, Indicates the first The spectrum of the baseband pulse transmission waveform, and the equivalent complex scattering coefficients satisfy... .

[0042] Furthermore, the complete echo in the frequency domain can be expressed as the sum of the target component, clutter component, and noise component, as shown in the following equation:

[0043] If the clutter scattering sources are distributed within the distance range and speed range The clutter frequency domain expression is as follows:

[0044] Subsequently, by integrating the distance variable in this embodiment, a simplified clutter frequency domain expression can be obtained:

[0045] Furthermore, embodiments of this application can be implemented at a frequency Define the echo snapshot vector stacked along the pulse dimension. Then we have:

[0046] Wherein, the target component vector is in the th At each pulse position, the following condition is satisfied:

[0047] Therefore, this embodiment of the application can acquire pulse echo data of pattern-agile radar within a coherent processing interval, perform down-conversion and pulse compression processing on the echo data, and perform Fourier transform along the fast time dimension (i.e., the first target time dimension) to obtain the echo snapshot vector at each frequency sampling point, thereby organizing the original echo into the frequency domain vector form required for subsequent subspace modeling. Furthermore, this embodiment of the application can explicitly introduce the pattern-agile waveform spectrum into the frequency domain guidance vector, thereby ensuring that the clutter subspace modeling is consistent with the actual transmitted waveform, fundamentally alleviating the model mismatch problem of traditional slow-time suppression methods under pattern-agile conditions.

[0048] In step S102, the clutter velocity range corresponding to the echo data is determined, and the corresponding modulation guidance vector is constructed based on the clutter velocity range. The clutter velocity range is integrated based on the modulation guidance vector to construct the modulation clutter correlation matrix at each frequency sampling point. The modulation clutter correlation matrix is ​​decomposed into eigenvalues ​​and combined with the preset power constraints to generate the corresponding clutter orthogonal projection matrix.

[0049] Furthermore, embodiments of this application may be based on the first... Known baseband transmit waveform of one pulse Calculate the corresponding spectrum A waveform spectrum vector is formed at each frequency sampling point. Simultaneously, a velocity guidance vector is constructed based on the low-speed range where clutter is located. This leads to the formation of a modulation guidance vector. .

[0050] Secondly, in this embodiment, the modulation guidance vector can be integrated within the clutter velocity range to calculate the modulation clutter correlation matrix. This matrix unifies the code pattern information and low-speed clutter distribution information into the same covariance model, which is the basis for subsequently obtaining the main clutter subspace.

[0051] Subsequently, in embodiments of this application, eigenvalue decomposition can be performed on the modulation clutter correlation matrix. Based on the magnitude of the eigenvalues ​​and a preset clutter-to-noise ratio parameter, the effective rank at the corresponding frequency sampling point can be determined, and a clutter orthogonal projection matrix can be generated. In embodiments of this application, the effective rank can be selected as the minimum rank that satisfies the condition that the residual clutter power is lower than the projected noise power.

[0052] Therefore, the embodiments of this application do not rely on the traditional assumption that the waveforms between pulses are completely consistent. Instead, they directly use the prior knowledge of the known waveforms to construct the modulation clutter correlation matrix. Thus, they can still maintain high clutter suppression stability when different pulses use different coding sequences.

[0053] Optionally, in one embodiment of this application, the clutter velocity range corresponding to the echo data is determined, and a corresponding modulation guidance vector is constructed based on the clutter velocity range. The clutter velocity range is then integrated based on the modulation guidance vector to construct a modulation clutter correlation matrix at each frequency sampling point. Furthermore, eigenvalue decomposition is performed on the modulation clutter correlation matrix, and a corresponding clutter orthogonal projection matrix is ​​generated by combining it with a preset power constraint. This includes: acquiring the baseband transmitted waveform and transmitted carrier frequency corresponding to multiple pulse signals, and constructing a corresponding waveform spectrum vector based on the baseband transmitted waveform; acquiring the radial velocity and pulse repetition interval of the target under test, and determining the corresponding velocity guidance vector based on the transmitted carrier frequency, radial velocity, and pulse repetition interval. The Hadamard product between the velocity guidance vector and the waveform spectrum vector is calculated, and the modulation guidance vector is determined by the Hadamard product. The modulation guidance vector is used to integrate the velocity range where clutter is located in the echo data to construct the modulation clutter correlation matrix at each frequency sampling point. Eigenvalue decomposition is then performed on the modulation clutter correlation matrix to obtain the corresponding eigenvalue decomposition results. Based on the power constraint, the effective rank of the modulation clutter correlation matrix is ​​determined, and multiple principal eigenvectors of the modulation clutter correlation matrix are obtained according to the eigenvalue decomposition results. The corresponding clutter orthogonal projection matrix is ​​constructed using the effective rank and multiple principal eigenvectors. The power constraint is that the residual clutter power of the modulation clutter correlation matrix is ​​lower than the noise power.

[0054] Specifically, embodiments of this application may be implemented at frequency Constructing the modulation guidance vector It is composed of waveform spectrum vector and velocity guidance vector Obtained by the Hadamard product, i.e.:

[0055] It should be noted that, for the velocity range where clutter is located, the embodiments of this application can construct a modulation clutter correlation matrix at each frequency sampling point. :

[0056] in, Represents frequency The modulation clutter correlation matrix at the location; This represents the lower limit of the velocity range in which the clutter exists; This represents the upper limit of the velocity range in which the clutter exists; Represents frequency Modulation guidance vector at the location; Represents frequency The conjugate transpose of the modulation guidance vector at that location; Indicates the conjugate transpose of the orientation quantity; Indicates radial velocity.

[0057] its first i Line 1 k Column elements can be represented as:

[0058] Among them, matrix superscript The symbol represents the Hermitian transpose, and the asterisk represents the conjugate. Since low-velocity clutter satisfies time-limited band-limited characteristics within the coherent processing interval, its subspace can be characterized using a low-rank method. In this embodiment, the row correlation matrix consisting solely of velocity guidance vectors can be defined as:

[0059] Since the waveform spectrum vector is independent of the velocity variable, the modulation clutter correlation matrix can be further compacted as follows:

[0060] Therefore, the effect of code agility on the clutter subspace can be understood as applying a linear modulation transformation related to the waveform spectrum to the original low-Doppler subspace, while preserving the low-rank property of the clutter subspace. Let the effective rank of the modulation clutter correlation matrix be... Then the following conditions are met:

[0061] Furthermore, embodiments of this application can perform eigenvalue decomposition on the modulation clutter correlation matrix to obtain the following equation:

[0062] According to the previous One principal feature vector can be used to construct a frequency. Clutter orthogonal projection matrix at the location:

[0063] To minimize target energy loss while ensuring clutter suppression, the effective rank is selected based on the criterion that the residual clutter power is lower than the noise power, i.e.:

[0064] in, The modulated clutter correlation matrix is ​​arranged in descending order. 1 eigenvalue, This represents the accumulated clutter-to-noise ratio without clutter suppression. This criterion can suppress residual clutter while avoiding excessive projection degrees of freedom being used to suppress dimensions that do not need to be suppressed.

[0065] Under normal circumstances, if the waveform spectrum vector at each frequency sampling point does not degenerate, then the matrix can be processed first. By performing eigenvalue decomposition and uniformly determining the effective rank, the online computational complexity can be reduced. At this point, we can obtain:

[0066] Therefore, embodiments of this application can construct a waveform spectrum vector based on the known baseband transmit waveform of each pulse, and construct a velocity guidance vector and a modulation guidance vector based on a preset low-speed clutter range. Furthermore, by integrating the modulation guidance vector over the clutter velocity range, a modulation-clutter correlation matrix is ​​constructed at each frequency sampling point. Subsequently, embodiments of this application perform eigenvalue decomposition on the modulation-clutter correlation matrix and determine the effective rank based on the constraint that the residual clutter power is lower than the noise power, thereby generating the corresponding clutter orthogonal projection matrix.

[0067] Furthermore, the embodiments of this application utilize eigenvalue decomposition and adaptive rank selection to simultaneously consider clutter suppression capability and target component fidelity, thus making it suitable for strong clutter backgrounds and easy to adjust parameters according to different clutter-to-noise ratio conditions.

[0068] In step S103, the echo snapshot vector is subjected to a preset frequency point projection suppression operation using the clutter orthogonal projection matrix to obtain the clutter suppressed frequency domain output. The preset inverse frequency domain transformation, coherent accumulation and detection processing are then performed on the clutter suppressed frequency domain output to generate the target detection result corresponding to the target code agile radar.

[0069] Furthermore, embodiments of this application can utilize echo snapshot vectors. Projected onto the orthogonal cosine subspace corresponding to the orthogonal projection matrix of the clutter (i.e., using the projection matrix to represent the frequency). The echo snapshot vector at the location is projected and suppressed to obtain the projection-suppressed output (i.e., the clutter-suppressed frequency domain output). :

[0070] in, This indicates the clutter suppression frequency domain output; Represents frequency The clutter orthogonal projection matrix at the location; Represents frequency The echo snapshot vector at that location.

[0071] Therefore, the embodiments of this application can retain non-master clutter subspace components, thereby preserving the target component as much as possible and suppressing interference energy consistent with the master clutter subspace.

[0072] Subsequently, in the embodiments of this application, the projected outputs at all frequency sampling points can be combined to obtain the complete frequency domain echo after clutter suppression (i.e., the projected suppressed outputs at all frequency sampling points). The inverse frequency domain transformation is then performed on the complete frequency domain echo after clutter suppression to recover the range dimension response. Slow-time coherent accumulation, velocity spectrum calculation, and threshold detection (i.e., target detection based on the range profile, velocity spectrum, or range-velocity map) are then performed to obtain the target detection result. If necessary, the embodiments of this application can perform target tracking or display operations based on the target detection result.

[0073] It should be noted that the embodiments of this application can establish waveform spectrum libraries offline for different code pattern sets, and establish relevant matrix template libraries offline for different clutter velocity spectral widths. During online processing, only the corresponding waveform templates need to be retrieved and a small number of matrix updates need to be completed, thereby reducing real-time processing overhead.

[0074] Furthermore, when the radar operating mode is switched, the embodiments of this application can automatically regenerate the velocity guidance vector and rank threshold parameters based on the coherent processing interval length, pulse number, and waveform set, thereby adapting to different operating modes.

[0075] As one possible approach, the waveform spectrum vector, velocity guidance vector template, and rank selection threshold parameter in the embodiments of this application can be pre-calculated and cached offline, thereby simplifying the online processing mainly to frequency point matrix construction, eigenvalue decomposition, and projection multiplication, which is beneficial for deployment in real-time radar signal processing platforms. When there is prior uncertainty in the clutter velocity spectrum width, the velocity range can be appropriately expanded so that the constructed modulation clutter correlation matrix covers a range slightly wider than the true clutter spectrum width, thereby reducing the risk of clutter residual leakage. Correspondingly, the effective rank selection criterion can automatically adjust the projection degrees of freedom, mitigating the additional loss of target components due to the expanded velocity range.

[0076] In the parameter selection and engineering implementation process, the embodiments of this application specify the rank selection parameter. The setting can be based on the accumulated clutter-to-noise ratio in the actual scenario without clutter suppression; for the speed range The velocity range can be determined based on scene experience, prior map information, or historical echo statistics. If the scene clutter spectral width changes over time, the velocity range can be adaptively updated.

[0077] In practical engineering implementation, the construction of correlation matrices and projection suppression processes at each frequency sampling point can be executed in parallel; for eigenvalue decomposition at the same frequency sampling point, hardware acceleration or parallel numerical libraries can also be used for acceleration. Since the embodiments of this application use frequency point decomposition processing, they have good parallel deployment characteristics.

[0078] The execution logic of the pattern-agile radar clutter suppression method of this application will be described below with reference to the accompanying drawings.

[0079] Figure 2 This is a schematic diagram illustrating the execution logic of the code-agile radar clutter suppression method of this application. Figure 2 As shown, the execution process of the code-agile radar clutter suppression method of this application is as follows: S201: Input echo data, echo information and clutter velocity range; S202: Perform down-conversion, pulse compression, and frequency domain transformation on the echo to obtain the echo snapshot vector at each frequency sampling point; S203: Construct waveform spectrum vectors based on the baseband transmission waveforms of each pulse, and construct velocity guidance vectors and modulation guidance vectors based on the low-speed clutter region; S204: Construct the modulation clutter correlation matrix at each frequency sampling point based on the integral of the modulation guidance vector over the clutter velocity interval; S205: Perform eigenvalue decomposition on the modulation clutter correlation matrix and generate the clutter orthogonal projection matrix according to the rank selection criterion; S206: Use the projection matrix to perform frequency point projection suppression on the echo snapshot vector at each frequency sampling point to obtain the frequency domain output after clutter suppression; S207: Perform inverse frequency domain transformation, coherent accumulation and detection on the frequency domain output after clutter suppression, and output target range information, velocity information or joint range and velocity results.

[0080] Furthermore, this application can also construct a corresponding pattern-agile radar clutter suppression system based on the execution logic of the pattern-agile radar clutter suppression method. This pattern-agile radar clutter suppression system includes an echo preprocessing module, a frequency domain prior construction module, a modulation covariance calculation module, a rank estimation and projection generation module, a frequency domain projection suppression module, and a detection output module.

[0081] The echo preprocessing module is used to perform down-conversion, pulse compression, and frequency domain transformation on the echo data to generate echo snapshot vectors at the frequency sampling points.

[0082] The frequency domain prior construction module is used to generate waveform spectrum vectors and modulation guidance vectors based on known code pattern information.

[0083] The modulation covariance calculation module is used to construct the modulation clutter correlation matrix; the rank estimation and projection generation module is used to complete eigenvalue decomposition, rank selection and projection matrix generation.

[0084] The frequency domain projection suppression module is used to perform orthogonal projection of the echo snapshot vector at each frequency sampling point according to the projection matrix, thereby suppressing the main clutter subspace component.

[0085] The detection output module is used to perform inverse frequency domain transformation, coherent accumulation, and target detection on the projection suppression results, and output target distance information, velocity information, or joint distance and velocity information.

[0086] It should be noted that the embodiments of this application can be seamlessly integrated with existing pulse compression modules, frequency domain accumulation modules, and detection modules without fundamentally modifying the back-end detection framework. For existing radar signal processing links, only a modulation subspace projection processing unit needs to be added between the frequency domain pulse compression output and the slow-time accumulation.

[0087] In the embodiments of this application, the pattern-agile radar clutter suppression system can also be implemented in a modular manner, wherein each functional module can be deployed on the same processing platform or distributed according to actual engineering needs. As long as echo preprocessing, modulation subspace construction, projection suppression, and detection output can be completed, it should be considered to fall within the protection scope of this application.

[0088] According to the clutter suppression method for pattern-agile radar proposed in this application, the echo data of the target pattern-agile radar within a coherent processing interval is down-converted, pulse-compressed, and frequency-domain transformed to obtain the corresponding echo snapshot vector. The clutter velocity range corresponding to the echo data is determined, and a corresponding modulation guidance vector is constructed based on the clutter velocity range. The modulation guidance vector is then integrated over the clutter velocity range to construct the modulation clutter correlation matrix at each frequency sampling point. The modulation clutter correlation matrix is ​​then subjected to eigenvalue decomposition, and combined with a preset power constraint, a corresponding clutter orthogonal projection matrix is ​​generated. The clutter orthogonal projection matrix is ​​used to perform preset frequency point projection suppression operations on the echo snapshot vector to obtain the clutter-suppressed frequency domain output. Preset inverse frequency domain transformation, coherent accumulation, and detection processing are then performed on the clutter-suppressed frequency domain output to generate the target detection result corresponding to the target pattern-agile radar. The frequency point independent construction and projection processing of this application facilitate parallel implementation, are compatible with existing frequency domain signal processing architectures, and are suitable for engineering deployment in radar real-time signal processing equipment, software radio platforms, or general-purpose processor platforms.

[0089] Secondly, the code-agile radar clutter suppression device according to the embodiments of this application is described with reference to the accompanying drawings.

[0090] Figure 3 This is a block diagram of a pattern-agile radar clutter suppression device according to an embodiment of this application.

[0091] like Figure 3 As shown, the code-agile radar clutter suppression device 10 includes: a preprocessing module 100, an eigenvalue decomposition module 200, and a clutter suppression module 300.

[0092] The preprocessing module 100 is used to perform down-conversion, pulse compression, and frequency domain transformation operations on the echo data of the target code agile radar within a coherent processing interval to obtain the corresponding echo snapshot vector.

[0093] The eigenvalue decomposition module 200 is used to determine the clutter velocity range corresponding to the echo data, construct the corresponding modulation guidance vector based on the clutter velocity range, integrate the clutter velocity range based on the modulation guidance vector to construct the modulation clutter correlation matrix at each frequency sampling point, perform eigenvalue decomposition on the modulation clutter correlation matrix, and generate the corresponding clutter orthogonal projection matrix in combination with the preset power constraints.

[0094] The clutter suppression module 300 is used to perform preset frequency point projection suppression operation on the echo snapshot vector using the clutter orthogonal projection matrix to obtain the clutter suppression frequency domain output, and to perform preset inverse frequency domain transformation, coherent accumulation and detection processing on the clutter suppression frequency domain output to generate the target detection result corresponding to the target code agile radar.

[0095] Optionally, in one embodiment of this application, the preprocessing module 100 includes a receiving unit and a transformation unit.

[0096] The receiving unit is used to transmit multiple pulse signals to the target under test through the target code agile radar within a coherent processing interval, and to receive the echo data corresponding to the multiple pulse signals. It also performs preset down-conversion and pulse compression processing on the echo data to obtain the corresponding compressed signal.

[0097] The transformation unit is used to perform a Fourier transform on the compressed signal along the first target time dimension to obtain the echo snapshot vector at each frequency sampling point.

[0098] Optionally, in one embodiment of this application, the eigenvalue decomposition module 200 includes: a first construction unit, a calculation unit, an integration unit, and a second construction unit.

[0099] The first construction unit is used to acquire the baseband transmission waveform and transmission carrier frequency corresponding to multiple pulse signals, and to construct the corresponding waveform spectrum vector based on the baseband transmission waveform.

[0100] The calculation unit is used to obtain the radial velocity and pulse repetition interval of the target under test, so as to determine the corresponding velocity guidance vector according to the transmission carrier frequency, radial velocity and pulse repetition interval, and calculate the Hadamard product between the velocity guidance vector and the waveform spectrum vector, and determine the modulation guidance vector through the Hadamard product.

[0101] The integration unit is used to integrate the velocity range of clutter in the echo data using the modulation guidance vector to construct the modulation clutter correlation matrix at each frequency sampling point, and to perform eigenvalue decomposition on the modulation clutter correlation matrix to obtain the corresponding eigenvalue decomposition results.

[0102] The second construction unit is used to determine the effective rank of the modulation clutter correlation matrix based on power constraints, and to obtain multiple principal eigenvectors of the modulation clutter correlation matrix according to the eigenvalue decomposition results, so as to construct the corresponding clutter orthogonal projection matrix using the effective rank and multiple principal eigenvectors. The power constraint is that the residual clutter power of the modulation clutter correlation matrix is ​​lower than the noise power.

[0103] Optionally, in one embodiment of this application, the mathematical expression for the clutter suppression frequency domain output is:

[0104] in, This indicates the clutter suppression frequency domain output; Represents frequency The clutter orthogonal projection matrix at the location; Represents frequency The echo snapshot vector at that location.

[0105] Optionally, in one embodiment of this application, the mathematical expression for the modulation clutter correlation matrix is:

[0106] in, Represents frequency The modulation clutter correlation matrix at the location; This represents the lower limit of the velocity range in which the clutter exists; This represents the upper limit of the velocity range in which the clutter exists; Represents frequency Modulation guidance vector at the location; Represents frequency The conjugate transpose of the modulation guidance vector at that location; Indicates the conjugate transpose of the orientation quantity; Indicates radial velocity.

[0107] It should be noted that the foregoing explanation of the code-agile radar clutter suppression method embodiment also applies to the code-agile radar clutter suppression device of this embodiment, and will not be repeated here.

[0108] The clutter suppression device for pattern-agile radar proposed in this application includes a preprocessing module 100, which performs down-conversion, pulse compression, and frequency domain transformation operations on the echo data of the target pattern-agile radar within a coherent processing interval to obtain the corresponding echo snapshot vector; an eigenvalue decomposition module 200, which determines the clutter velocity range corresponding to the echo data, constructs the corresponding modulation guidance vector based on the clutter velocity range, integrates the clutter velocity range based on the modulation guidance vector to construct the modulation clutter correlation matrix at each frequency sampling point, performs eigenvalue decomposition on the modulation clutter correlation matrix, and generates the corresponding clutter orthogonal projection matrix in combination with a preset power constraint; and a clutter suppression module 300, which performs preset frequency point projection suppression operation on the echo snapshot vector using the clutter orthogonal projection matrix to obtain the clutter suppression frequency domain output, and performs preset inverse frequency domain transformation, coherent accumulation, and detection processing on the clutter suppression frequency domain output to generate the target detection result corresponding to the target pattern-agile radar. This application can effectively suppress clutter components by explicitly writing the inter-pulse waveform difference into the frequency domain guide vector, constructing a modulation clutter correlation matrix that matches the actual code pattern, and adaptively generating an orthogonal projection matrix based on the eigenvalue distribution.

[0109] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 401, the processor 402, and the computer program stored on the memory 401 and capable of running on the processor 402.

[0110] When the processor 402 executes the program, it implements the pattern-agile radar clutter suppression method provided in the above embodiments.

[0111] Furthermore, electronic devices also include: Communication interface 403 is used for communication between memory 401 and processor 402.

[0112] The memory 401 is used to store computer programs that can run on the processor 402.

[0113] Memory 401 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0114] If the memory 401, processor 402, and communication interface 403 are implemented independently, then the communication interface 403, memory 401, and processor 402 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0115] Optionally, in a specific implementation, if the memory 401, processor 402, and communication interface 403 are integrated on a single chip, then the memory 401, processor 402, and communication interface 403 can communicate with each other through an internal interface.

[0116] Processor 402 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0117] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described pattern-agile radar clutter suppression method.

[0118] This application also provides a computer program product, including a computer program, which, when executed, is used to implement the above-described pattern-agile radar clutter suppression method.

[0119] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0120] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0121] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0122] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0123] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0124] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0125] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0126] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for clutter suppression in a code agile radar, characterized by, Includes the following steps: The echo data of the target code agile radar within one coherent processing interval is subjected to down-conversion, pulse compression and frequency domain transformation to obtain the corresponding echo snapshot vector. The clutter velocity range corresponding to the echo data is determined, and a corresponding modulation guidance vector is constructed based on the clutter velocity range. The clutter velocity range is integrated based on the modulation guidance vector to construct the modulation clutter correlation matrix at each frequency sampling point. The modulation clutter correlation matrix is ​​decomposed into eigenvalues ​​and combined with a preset power constraint to generate the corresponding clutter orthogonal projection matrix. The clutter orthogonal projection matrix is ​​used to perform a preset frequency point projection suppression operation on the echo snapshot vector to obtain the clutter suppressed frequency domain output. The preset inverse frequency domain transformation, coherent accumulation and detection processing are then performed on the clutter suppressed frequency domain output to generate the target detection result corresponding to the target pattern agile radar.

2. The code agility radar clutter suppression method of claim 1, wherein, The process of performing down-conversion, pulse compression, and frequency domain transformation operations on the echo data of the target pattern agile radar within one coherent processing interval to obtain the corresponding echo snapshot vector includes: The target pattern agile radar transmits multiple pulse signals to the target under test within one coherent processing interval, receives the echo data corresponding to the multiple pulse signals, and performs preset down-conversion and pulse compression processing on the echo data to obtain the corresponding compressed signal. The compressed signal is subjected to a Fourier transform along the first target time dimension to obtain the echo snapshot vector at each frequency sampling point.

3. The code agility radar clutter suppression method of claim 2, wherein, The process of determining the clutter velocity range corresponding to the echo data, constructing a corresponding modulation guidance vector based on the clutter velocity range, integrating the clutter velocity range based on the modulation guidance vector to construct the modulation clutter correlation matrix at each frequency sampling point, performing eigenvalue decomposition on the modulation clutter correlation matrix, and generating a corresponding clutter orthogonal projection matrix by combining a preset power constraint, includes: Obtain the baseband transmission waveform and transmission carrier frequency corresponding to the multiple pulse signals, and construct the corresponding waveform spectrum vector based on the baseband transmission waveform; The radial velocity and pulse repetition interval of the target under test are obtained, and the corresponding velocity guidance vector is determined according to the transmission carrier frequency, the radial velocity and the pulse repetition interval. The Hadamard product between the velocity guidance vector and the waveform spectrum vector is calculated, and the modulation guidance vector is determined by the Hadamard product. The modulation guidance vector is used to integrate the velocity range where the clutter in the echo data is located to construct the modulation clutter correlation matrix at each frequency sampling point, and the modulation clutter correlation matrix is ​​subjected to eigenvalue decomposition to obtain the corresponding eigenvalue decomposition result. Based on the power constraint, the effective rank of the modulation clutter correlation matrix is ​​determined, and multiple principal eigenvectors of the modulation clutter correlation matrix are obtained according to the eigenvalue decomposition result, so as to construct the corresponding clutter orthogonal projection matrix using the effective rank and the multiple principal eigenvectors, wherein the power constraint is that the residual clutter power of the modulation clutter correlation matrix is ​​lower than the noise power.

4. The code agility radar clutter suppression method of claim 3, wherein, The mathematical expression for the clutter suppression frequency domain output is: in, This represents the clutter suppression frequency domain output; Represents frequency The clutter orthogonal projection matrix at the location; Represents frequency The echo snapshot vector at that location.

5. The code-agile radar clutter suppression method according to claim 3, characterized in that, The mathematical expression for the modulation clutter correlation matrix is: in, Represents frequency The modulation clutter correlation matrix at the location; This represents the lower limit of the velocity range in which the clutter exists; This represents the upper limit of the velocity range in which the clutter is located; Represents frequency Modulation guidance vector at the location; Represents frequency The conjugate transpose of the modulation guidance vector at that location; Indicates the conjugate transpose of the orientation quantity; Indicates radial velocity.

6. A pattern-agile radar clutter suppression device, characterized in that, include: The preprocessing module is used to perform down-conversion, pulse compression, and frequency domain transformation operations on the echo data of the target code agile radar within one coherent processing interval to obtain the corresponding echo snapshot vector. The eigenvalue decomposition module is used to determine the clutter velocity range corresponding to the echo data, construct the corresponding modulation guidance vector according to the clutter velocity range, integrate the clutter velocity range based on the modulation guidance vector to construct the modulation clutter correlation matrix at each frequency sampling point, perform eigenvalue decomposition on the modulation clutter correlation matrix, and generate the corresponding clutter orthogonal projection matrix in combination with the preset power constraint. The clutter suppression module is used to perform a preset frequency point projection suppression operation on the echo snapshot vector using the clutter orthogonal projection matrix to obtain the clutter suppression frequency domain output, and to perform preset inverse frequency domain transformation, coherent accumulation and detection processing on the clutter suppression frequency domain output to generate the target detection result corresponding to the target code agile radar.

7. The pattern-agile radar clutter suppression device according to claim 6, characterized in that, The preprocessing module includes: The receiving unit is configured to transmit multiple pulse signals to the target under test through the target code agile radar within a coherent processing interval, receive echo data corresponding to the multiple pulse signals, and perform preset down-conversion and pulse compression processing on the echo data to obtain the corresponding compressed signal. The transformation unit is used to perform a Fourier transform on the compressed signal along the first target time dimension to obtain the echo snapshot vector at each frequency sampling point.

8. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the pattern-agile radar clutter suppression method as described in any one of claims 1-5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the pattern-agile radar clutter suppression method as described in any one of claims 1-5.

10. A computer program product, comprising a computer program, characterized in that, The computer program is executed to implement the pattern-agile radar clutter suppression method as described in any one of claims 1-5.

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