A composite deception jamming suppression method based on intra-pulse frequency agility and inter-pulse initial phase agility waveform

Abstract

The present invention discloses a composite deception interference suppression method based on an intra-pulse frequency agility-inter-pulse initial phase agility waveform. First, based on the inherent characteristics of the intra-pulse frequency agility-inter-pulse initial phase agility waveform, the method uses the Capon spectrum estimation method to achieve velocity estimation of echo signals in different distance segments. Then, based on the estimated velocity information, the subspace of the echo signals in different distance segments is constructed, and the idea of ​​alternating iterative reconstruction is adopted to achieve reconstruction of the echo signals in different distance segments, thereby achieving suppression of full-pulse forwarding interference. Finally, fine time-frequency feature matching technology is used to suppress intermittent sampling forwarding interference. This method can effectively suppress the composite deception interference composed of full-pulse forwarding interference and intermittent sampling forwarding interference, and achieve estimation of the real target distance and velocity information.

Description

Technical Field

[0001] The present invention belongs to the field of radar interference suppression, and in particular relates to a composite deception interference suppression method based on an intra-pulse frequency agility-inter-pulse initial phase agility waveform. Background Art

[0002] In modern battlefields, radars face an increasingly complex electromagnetic environment, prompting the emergence of various new electronic jamming devices. In particular, with the rapid development of digital radio frequency memory (DRFM) technology, active deception jamming has gradually gained importance in electronic warfare. Composite deception jamming, composed of multiple active deception jammers, achieves near-100% coverage of target echoes in the time or frequency domain, severely restricting the detection performance of modern radars. Based on the integrity of the jammer's intercepted signal, active deception jamming can be primarily categorized as full pulse repeater jamming (FPRJ) and interrupted sampling repeater jamming (ISRJ). It should be noted that due to the relatively long generation time of FPRJ, in order to ensure that the generated decoy targets surround the real target, the FPRJ typically lags behind the target echo by at least one pulse repetition time (PRT). For ease of description, the echo signal is divided into distance segments with varying delays based on the PRT. Existing jamming suppression methods are mostly applicable only to single jamming scenarios and are ineffective against composite deception jamming. In recent years, agile waveforms have garnered widespread attention for their "active anti-jamming" capabilities. In 2023, Professor Li Yachao of Xidian University employed a combined inter-pulse and intra-pulse frequency-coded waveform to counter complex deceptive jamming. When frequency-coded modulation is used intra-pulse, it effectively enhances the time-frequency distinction between ISRJ and target echoes; when frequency agility is used inter-pulse, it effectively counters FPRJ. However, while inter-pulse frequency-agile waveforms improve radar low-acquisition and anti-jamming capabilities, they also present challenges for radar coherent processing. Specifically, due to the inter-pulse carrier frequency agility, the echo inter-pulse phase is discontinuous, making traditional coherent accumulation methods infeasible. Compared to inter-pulse frequency agility, inter-pulse initial phase agility requires only initial phase compensation for coherent processing, making it simpler to operate and easier to implement. Therefore, if an agile waveform uses initial phase-coded modulation between pulses and frequency-coded modulation within pulses, this can effectively avoid the coherent processing difficulties and, combined with appropriate signal processing methods, effectively suppress complex deceptive jamming. Summary of the Invention

[0003] The problem solved by the present invention is to overcome the shortcomings of the existing technology and propose a composite deception interference suppression method based on intra-pulse frequency agility-inter-pulse initial phase agility waveform to effectively suppress the composite deception interference composed of ISRJ and FPRJ.

[0004] The present invention proposes a composite deception interference suppression method based on intra-pulse frequency agility and inter-pulse initial phase agility waveform, which includes the following steps:

[0005] Step 1: Use the Capon spectrum estimation method to estimate the speed of the interference and target in different distance segments. Based on the Capon spectrum results, CFAR detection technology is used to estimate the speed of the interference and target in different distance segments. The calculation process of the Capon spectrum in step 1 is as follows:

[0006] definition As the Doppler steering vector of the slow time dimension of the pulse-Doppler (PD) radar, f is the normalized Doppler frequency and M is the number of pulses transmitted within the coherent integration time. The initial phase sequence is expressed as The slow-time steering vector of a single interference or target in the x-th distance segment can be expressed as

[0007]

[0008] Where X is the maximum number of fuzzy range segments. Assume that the echo signal matrix is ​​represented by E,

[0009] E=[e(0),…,e(k),…,e(K-1)] (2)

[0010] Where e(k) represents the slow time dimension data corresponding to the kth sampling point, and K is the number of sampling points in a PRT.

[0011] The slow-time covariance matrix R of the echo signal can be estimated by the covariance matrix of the sampling data, that is,

[0012]

[0013] Therefore, the Capon spectrum corresponding to the echo signal in the xth distance segment is

[0014]

[0015] Step 2: Based on the estimated velocity information, construct the subspace corresponding to the echo signals of different distance segments, and use the alternating iterative reconstruction technique to reconstruct and decorrelate the echoes of different distance segments, thereby suppressing FPRJ. Step 2 further includes:

[0016] Step 2.1: Based on the estimated velocity information, construct the subspace corresponding to the echo signal of the x-th distance segment as

[0017]

[0018] Among them, P x The number of velocity channels detected for the Capon spectrum of the xth distance segment.

[0019] Step 2.2: Substitute the above steering vector set with the matrix U x Indicates that Then the projection matrix P of the x-th distance segment is x for

[0020]

[0021] Step 2.3: Project the echo signal matrix to the projection matrix corresponding to the echo signal of the x-th distance segment. The echo signal of the x-th distance segment is preliminarily estimated to be

[0022] E x =P x E (7)

[0023] Step 2.4: Use alternating iterative reconstruction technology between different distance segments to gradually eliminate the echo folding energy of other distance segments extracted by the projection matrix, and gradually reconstruct and invert the echo signal from the xth distance segment, ultimately achieving decorrelation between the echo signals of each distance segment. The recursive formula of the alternating iterative reconstruction process is as follows

[0024]

[0025] Wherein, the superscript {κ} represents the iteration index. The convergence condition of the iterative process is Or the number of iterations reaches the set value, ||·|| F Denotes the Frobenius norm. Combining the above process, the echo signal of the x-th distance segment can be expressed as

[0026]

[0027] In summary, the decorrelation between echoes in each distance segment in the echo signal can be completed, that is, the FPRJ can be suppressed.

[0028] Step 3: After completing the suppression of FPRJ, extract the echo signal of the designated velocity channel after the initial phase compensation and Doppler processing of the echo signal in the range segment where the target is located. The designated velocity channel can be determined based on the velocity estimated by Capon spectrum.

[0029] Step 4: For the echo signal of the extracted designated velocity channel, an interference suppression method based on fine time-frequency feature matching is used to suppress the ISRJ in the echo signal. Step 4 further includes:

[0030] Step 4.1: Perform short-time Fourier transform on any transmitted pulse to obtain the time-frequency result of the transmitted pulse, and binarize the time-frequency result to obtain the time-frequency template T.

[0031] Step 4.2: Perform short-time Fourier transform on the echo signal to obtain its time-frequency result. The corresponding time-frequency matrix is ​​represented by Y, and Y is binarized to obtain the matrix

[0032] Step 4.3: By shifting the time-frequency template and combining it with the matrix Point product, the process can be expressed as

[0033]

[0034] Where D represents the total number of shifts of the time-frequency template, Δd is the shift interval unit, shift[T,d·Δd] means shifting T to the right by d shift interval units, and the symbol ⊙ represents the Hadamard product (element-wise product).

[0035] Step 4.4: Calculate the mean and variance of the matching information in the template after each shift, denoted as mean(d) and var(d). Construct the shift index set The set is composed of the shift indices corresponding to the maximum values ​​of the mean; when the set The corresponding mean And the variance When , it is considered that there is a target echo in the area where the time-frequency template is located after the shift, and the corresponding index set is

[0036] Step 4.5: Index the collection The echo time-frequency information matched to the corresponding time-frequency template is transformed by inverse short-time Fourier transform to obtain

[0037]

[0038] Step 4.6: Calculation The variance of the non-zero elements in is denoted as according to Determine whether the matched target signal contains residual interference energy. If The target echo with residual interference signals is determined to be interference-free. The rest are determined to be target echoes with residual interference signals. For target echoes with residual interference signals, the Otsu algorithm (OSTU) is used to calculate the threshold and set the signals greater than the threshold in the extracted echo to 0, thus achieving the extraction of interference-free target echoes.

[0039] Step 4.7: After obtaining the interference-free target echo, construct a sub-pulse reference signal to perform matched filtering on the interference-free target echo and accumulate it. The maximum value of the accumulated result is set to 1, and the remaining values ​​are set to 0 to construct a range-dimensional filter. The constructed range-dimensional filter can be expressed as

[0040] Step 4.8: Match the target echo Pulse compression processing is performed, and the sub-pulse matching method is adopted, that is, the sub-pulse reference signal is constructed to respectively Perform matched filtering processing; then, accumulate the matched filtering results of all sub-pulses in a pulse, and finally obtain The pulse compression results

[0041] Step 4.9: Use the filter obtained in step 4.7 to filter the pulse compression result of step 4.8 to complete interference suppression and target positioning, that is,

[0042]

[0043] Step 4.10: Repeat steps 4.7 to 4.9 until all The interference suppression result of the speed channel is obtained as

[0044]

[0045] Step 5: In summary, the echo signal processing for a single velocity channel has been completed. Repeat step 4 until the echo signal processing for all extracted velocity channels is complete. The data processing results for the extracted velocity channel are added to the range-velocity results for the remaining velocity channels to obtain the range-velocity result diagram after composite deception interference suppression.

[0046] Beneficial effects:

[0047] 1. The Capon spectrum estimation method adopted in the present invention can effectively estimate the speed of targets and interferences in different distance segments. Based on the estimated speed information, the subspaces corresponding to targets and interferences in different distance segments are constructed, and the idea of ​​alternating iterative reconstruction is adopted to reconstruct the target echo and interference signals in different distance segments, which can effectively suppress the FPRJ in the echo.

[0048] 2. After FPRJ suppression is complete, an interference suppression method based on fine time-frequency feature matching is used to suppress ISRJ interference in the echo. This method extracts time-frequency features in the time-frequency domain using template shift matching to distinguish interference from targets, and then constructs a range-dimensional filter to remove the interference. This method effectively suppresses ISRJ in the echo while causing minimal target energy loss. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 , is a schematic diagram of the intra-pulse frequency agility-inter-pulse initial phase agility waveform in this embodiment;

[0050] Figure 2 , are the results of coherent processing of the original echo signal by range segment in this embodiment, (a) 3D view, (b) range-velocity projection diagram;

[0051] Figure 3 , are Capon spectrum estimation result diagrams corresponding to echo signals of different distance segments in this embodiment, (a) 0th distance segment, (b) 1st distance segment, (c) 2nd distance segment;

[0052] Figure 4 , is a diagram showing the result of the range segment coherent processing after the FPRJ in the echo is suppressed in this embodiment,

[0053] (a) 3D view, (b) range-velocity projection diagram;

[0054] Figure 5 , is a flow chart of the ISRJ suppression method based on fine time-frequency feature matching in this embodiment;

[0055] Figure 6 , is the composite deception interference suppression result in this embodiment. DETAILED DESCRIPTION

[0056] For ease of understanding of the present application, the specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thoroughly and comprehensively understood.

[0057] The core idea of ​​this invention is to first estimate the velocity of targets and interference within different distance segments using the Capon spectrum estimation method based on the inherent characteristics of the intra-pulse frequency agility and inter-pulse initial phase agility waveform. Then, based on the estimated velocity information, the subspaces corresponding to the targets and interference within different distance segments are constructed, and the target echo and interference signal within different distance segments are reconstructed using the idea of ​​alternating iterative reconstruction, thereby achieving FPRJ suppression. Finally, refined feature matching feature technology is used in the time-frequency domain to extract the target echo and achieve ISRJ suppression. In summary, it can achieve effective suppression of composite deceptive interference.

[0058] The traditional PD radar transmits a waveform with fixed parameters (constant initial phase between pulses), which results in highly correlated slow-time-dimensional steering vectors of echo signals with different distances but the same Doppler shift, making them difficult to distinguish. The schematic diagram of the intra-pulse frequency agility-inter-pulse initial phase agility waveform is shown in the figure below. Figure 1As shown, since different initial phases are modulated between pulses, the slow-time dimension steering vectors of the echo signals in different distance segments can be used to estimate the speed of interference and targets in different distance segments, which is convenient for distinguishing and extracting interference and targets in different distance segments. At the same time, the intra-pulse frequency agility-inter-pulse initial phase agility waveform adopts frequency coding modulation within the pulse, which can effectively enhance the distinguishability of target echo and ISRJ in the time-frequency domain, and provide support for subsequent signal processing. The composite deception interference suppression method based on the intra-pulse frequency agility-inter-pulse initial phase agility waveform proposed in the present invention specifically includes the following steps:

[0059] Step 1: Based on the inter-pulse modulation characteristics of the intra-pulse frequency agility-inter-pulse initial phase agility waveform, the Capon spectrum estimation method is used to estimate the speed of the interference and target in different distance segments.

[0060] definition As the Doppler steering vector of the slow time dimension of the PD radar, f is the normalized Doppler frequency and M is the number of pulses transmitted within a coherent integration time. The initial phase sequence is expressed as Then the slow-time dimension guidance vector corresponding to a single target or interference in the 0th distance segment can be expressed as

[0061]

[0062] Where X is the maximum number of fuzzy range segments. The slow-time dimension steering vector of the interference or target in the x-th range segment can be expressed as

[0063]

[0064] Assume that the echo signal matrix is ​​represented by E,

[0065] E=[e(0),…,e(k),…,e(K-1)] (3)

[0066] Where e(k) represents the slow time dimension data corresponding to the kth sampling point, and K is the number of sampling points in a PRT.

[0067] The slow-time covariance matrix R of the echo signal can be estimated by the covariance matrix of the sampling data, that is,

[0068]

[0069] Therefore, the Capon spectrum corresponding to the echo signal in the xth distance segment is

[0070]

[0071] Based on the Capon spectrum estimation results, the CFAR detection technology is used to estimate the corresponding velocities of the interference and target in different distance segments.

[0072] Step 1 is further described in detail with reference to the accompanying drawings. In this embodiment, it is assumed that there is a point target in the radar observation scene, located at 2.25 km in the 0th distance segment, with a speed of 300 m / s and a signal-to-noise ratio of -10 dB; the radar unambiguous ranging range is 7.5 km, which corresponds to a range of one distance segment; three ISRJs are in the same distance segment with the target, which are located at 2.4 km, 2.78 km and 2.96 km respectively, with speeds of 300 m / s, 150 m / s and 100m / s, and the signal-to-interference ratio is -30dB. At the same time, there is FPRJ in the scene, which randomly generates 40 false targets within the first distance range of [9.66, 9.84] km, of which 20 false targets have a speed of 200m / s and the remaining 20 false targets have a speed of 150m / s. In the second distance range of [17.16, 17.34] km, 20 false targets are randomly generated with a speed of 300m / s. The signal-to-interference ratio of FPRJ is -40dB. The results of the coherent processing of the original echo in different ranges are shown as follows: Figure 2 As shown. Figure 2 It can be seen that the composite deceptive jamming has a dual jamming effect of suppressing and deceiving the target at the 0th distance segment, making the target undetectable. Figure 3 (a)-(c) are shown, where the solid line is the Capon spectrum estimation result and the dotted line is the threshold set by CA-CFAR. Figure 2 It can be seen that the Capon spectrum estimation method can accurately estimate the speeds corresponding to interference and targets in different distance segments; at the same time, the Capon spectrum is detected using CFAR, which can effectively detect the speed channel where the target or interference is located.

[0073] Step 2: Based on the detected speed information, construct the subspace corresponding to the echo signal of different distance segments. Let the subspace corresponding to the echo signal of the xth distance segment be

[0074]

[0075] Among them, P x is the number of velocity channels detected by the Capon spectrum of the x-th distance segment. x It can be rewritten as

[0076]

[0077] According to formula (7), the projection matrix P of the x-th distance segment is x for

[0078]

[0079] By projecting the echo signal matrix onto the projection matrix corresponding to the echo signal of the x-th distance segment, the echo signal of the x-th distance segment can be preliminarily estimated. The expression is as follows

[0080] E x =P x E (9)

[0081] It is worth noting that E x The x-th range segment contains not only the interference / target energy but also the folded energy of echo signals from some other range segments. Therefore, to minimize the folded energy of echoes from other range segments folded into the x-th range segment, an alternating iterative reconstruction technique is used between different range segments to gradually eliminate the folded energy of echoes from other range segments extracted by the projection matrix. The echo signal from the x-th range segment is then gradually reconstructed and inverted, ultimately achieving decorrelation between the echo signals of each range segment.

[0082] The recursive formula of the alternating iterative reconstruction process is as follows

[0083]

[0084] Among them, the superscript {κ} represents the iteration index, the iteration initial value Can be set to

[0085]

[0086] The convergence condition of the iterative process is Or the number of iterations reaches a set value, where ||·|| F represents the Frobenius norm.

[0087] Combined with the above derivation process, the echo signal of the xth distance segment can be expressed as

[0088]

[0089] In summary, the decorrelation between echoes in each distance segment in the echo signal can be completed, that is, the FPRJ can be suppressed.

[0090] After processing in step 2, the coherent processing results of echo signals in different distance segments are as follows: Figure 4 As shown. Figure 4 It can be seen that after processing in step 2, the echo signals of the three range segments are effectively reconstructed, and the interference from the FPRJ of other range segments folded into the range segment where the target is located is effectively suppressed.

[0091] Step 3: After completing the suppression of FPRJ, extract the echo signal of the designated velocity channel after the initial phase compensation and Doppler processing of the echo signal in the range segment where the target is located. The designated velocity channel can be determined based on the velocity estimated by Capon spectrum.

[0092] Step 4: For the echo signal of the extracted specified velocity channel, the interference suppression method based on fine time-frequency feature matching is used to suppress ISRJ. The flow chart of this method is as follows: Figure 5 The specific steps are as follows:

[0093] Step 4.1: Perform short-time Fourier transform on any transmitted pulse to obtain its time-frequency result, and binarize the time-frequency result to obtain the time-frequency template T.

[0094] Step 4.2: Perform short-time Fourier transform on the echo signal to obtain its time-frequency result. The corresponding time-frequency matrix is ​​represented by Y. Binarize Y to obtain the matrix The binarization threshold can be set according to the noise power.

[0095] Step 4.3: By shifting the time-frequency template and combining it with the matrix Point product, the process can be expressed as

[0096]

[0097] Where D represents the total number of shifts of the time-frequency template, Δd is the shift interval unit, shift[T,d·Δd] means shifting T to the right by d shift interval units, and the symbol ⊙ represents the Hadamard product (element-wise product).

[0098] Step 4.4: Calculate the mean and variance of the matching information within the template after each shift, denoted as mean(d) and var(d). Due to the incompleteness of ISRJ itself, when the time-frequency template is matched to the interference and target respectively, there is a significant difference in the mean and variance of the two. Therefore, the mean and variance that meet specific conditions are selected to achieve the location of the target echo. Construct a shift index set The set is composed of the shift indices corresponding to the maximum values ​​of the mean; when the set The corresponding mean And the variance When , it is considered that there is a target echo in the area where the time-frequency template is located after the shift, and the corresponding index set is

[0099] Step 4.5: Index the collection The echo time-frequency information matched to the corresponding time-frequency template is transformed by inverse short-time Fourier transform to obtain

[0100]

[0101] Step 4.6: Calculation The variance of the non-zero elements in is denoted as It should be noted that in the time-frequency domain, the target echo may be covered by the interference sidelobe energy. When there is residual interference energy in the matched target echo, it will produce a false target after pulse compression, thereby affecting the detection of the real target. Therefore, it is necessary to first determine whether the matched target signal contains residual interference energy. If The target echo with residual interference signals is determined to be interference-free. The rest are determined to be target echoes with residual interference signals. For target echoes with residual interference signals, the Otsu algorithm (OSTU) is used to calculate the threshold. Signals greater than the threshold in the extracted echo are set to 0 to extract the target echo with no interference.

[0102] Step 4.7: After obtaining the interference-free target echo, construct a sub-pulse reference signal to perform matched filtering on the interference-free target echo and accumulate it. The maximum value of the accumulated result is set to 1, and the remaining values ​​are set to 0 to construct a range-dimensional filter. The constructed range-dimensional filter can be expressed as

[0103] Step 4.8: Match the target echo Pulse compression processing is performed, and the sub-pulse matching method is adopted, that is, the sub-pulse reference signal is constructed to respectively Perform matched filtering processing; then, accumulate the matched filtering results of all sub-pulses in a pulse, and finally obtain The pulse compression results

[0104] Step 4.9: Use the filter obtained in step 4.7 to filter the pulse compression result of step 4.8 to complete interference suppression and target positioning, that is,

[0105]

[0106] Step 4.10: Repeat steps 4.7 to 4.9 until all The interference suppression result of the speed channel is obtained as

[0107]

[0108] Step 5: In summary, the echo signal processing for a single velocity channel has been completed. Repeat step 4 until the echo signal processing for all extracted velocity channels is complete. The data processing results for the extracted velocity channel are added to the range-velocity results for the remaining velocity channels to obtain the range-velocity result diagram after composite deception interference suppression.

[0109] In this embodiment, the distance-speed result after composite deception interference suppression is as follows: Figure 6As shown in FIG, the result graph is normalized based on the peak value of the target echo coherent processing result. Figure 6 It can be seen that the three ISRJs in the range segment where the target is located are effectively suppressed, and the target can be effectively displayed; at the same time, the method proposed in this invention has basically no loss to the target energy and even enhances it. This is because the interference in the same range gate as the target enhances the peak energy of the target.

[0110] Of course, the present invention may have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims attached to the present invention.

Claims

1. A composite deception interference suppression method based on intra-pulse frequency agility and inter-pulse initial phase agility waveform, characterized in that: The method comprises the following steps: Step 1: Use the Capon spectrum estimation method to estimate the speed of the interference and target in different distance segments. Based on the Capon spectrum results, use the CFAR detection technology to estimate the corresponding speed of the interference and target in different distance segments. Step 2: Based on the estimated velocity information, the subspaces corresponding to the echo signals in different distance segments are constructed, and the alternating iterative reconstruction technique is used to reconstruct and decorrelate the echoes in different distance segments, thereby suppressing FPRJ. Step 3: After completing the FPRJ suppression, extract the echo signal of the designated velocity channel after the initial phase compensation and Doppler processing of the echo signal in the range segment where the target is located. The designated velocity channel can be determined based on the velocity estimated by Capon spectrum. Step 4: For the echo signal of the extracted specified velocity channel, an interference suppression method based on fine time-frequency feature matching is used to suppress the ISRJ in the echo signal; Step 5: In summary, the echo signal processing for a single velocity channel has been completed. Repeat step 4 until the echo signal processing for all extracted velocity channels is complete. The data processing results for the extracted velocity channel are added to the range-velocity results for the remaining velocity channels to obtain the range-velocity result diagram after composite deception interference suppression.

2. The method for suppressing composite deception interference based on intra-pulse frequency agility and inter-pulse initial phase agility waveform according to claim 1, characterized in that: The calculation process of the Capon spectrum in step 1 is: definition As the Doppler steering vector in the slow time dimension of the pulse-Doppler (PD) radar, is the normalized Doppler frequency, is the number of pulses emitted during the coherent integration time; The initial phase sequence is expressed as , No. The slow-time steering vector of a single interference or target within the range segment can be expressed as ； in is the maximum number of fuzzy distance segments; Assume that the echo signal matrix is express, ； in Indicates the The slow time dimension data corresponding to the sampling points, is the number of sampling points in a PRT; Slow-time covariance matrix of the echo signal It can be estimated by the covariance matrix of the sampled data, that is ； Therefore, the The corresponding Capon spectrum within the distance segment is 。 3. The method for suppressing composite deceptive interference based on intra-pulse frequency agility and inter-pulse initial phase agility waveform according to claim 2, characterized in that: The step 2 further comprises: Step 2.1: Based on the estimated speed information, construct the The subspace corresponding to the range segment echo signal is ； in For the The number of velocity channels detected by the Capon spectrum of the range segment; Step 2.2: Use the matrix Indicates that , then Projection matrix for distance segments for ； Step 2.3: Project the echo signal matrix to the The projection matrix corresponding to the range segment echo signal is preliminarily estimated. The echo signal of the distance segment is ； Step 2.4: Use alternating iterative reconstruction technology between different distance segments to gradually eliminate the echo folding energy of other distance segments extracted by the projection matrix, and only the echo from the first The range segment echo signals are gradually reconstructed and inverted, and finally the decorrelation between the echo signals of each range segment is achieved; the recursive formula of the alternating iterative reconstruction process is as follows ； Among them, the superscript represents the iteration index; the convergence condition of the iterative process is Or the number of iterations reaches the set value, represents the Frobenius norm; combined with the above process, The distance segment echo signal is expressed as 。 4. The method for suppressing composite deception interference based on intra-pulse frequency agility and inter-pulse initial phase agility waveform according to claim 1, characterized in that: The step 4 further comprises: Step 4.1: Perform short-time Fourier transform on any transmitted pulse to obtain the time-frequency result of the transmitted pulse, and binarize the time-frequency result to obtain the time-frequency template ; Step 4.2: Perform short-time Fourier transform on the echo signal to obtain its time-frequency result. The corresponding time-frequency matrix is To express and Perform binarization operation to obtain matrix ; Step 4.3: By shifting the time-frequency template and combining it with the matrix Point product, the process can be expressed as ； in, Indicates the total number of shifts of the time-frequency template, is the shift interval unit, Indicates that Shift right Shift interval unit, symbol represents the Hadamard product, that is, the element-wise product; Step 4.4: Calculate the mean and variance of the matching information within the template after each shift, recorded as and ; Build a shift index set , the set is composed of the shift index corresponding to the maximum value of the mean; when the set The corresponding mean And the variance When , it is considered that there is a target echo in the area where the time-frequency template is located after the shift, and the corresponding index set is ; Step 4.5: Index the collection The echo time-frequency information matched to the corresponding time-frequency template is transformed by inverse short-time Fourier transform to obtain ； Step 4.6: Calculation The variance of the non-zero elements in is denoted as ;according to Determine whether the matched target signal contains residual interference energy. If , it is determined to be a target echo without interference; the rest are determined to be target echoes with residual interference signals. For target echoes with residual interference signals, the Otsu algorithm (OSTU for short) is used to calculate the threshold, and the signals greater than the threshold in the extracted echoes are set to 0 to achieve the extraction of target echoes without interference; Step 4.7: After obtaining the interference-free target echo, construct a sub-pulse reference signal to perform matched filtering on the interference-free target echo and accumulate it. The maximum value of the accumulated result is set to 1, and the remaining values ​​are set to 0 to construct a range-dimensional filter. The constructed range-dimensional filter can be expressed as ; Step 4.8: Match the target echo Pulse compression processing is performed, and the sub-pulse matching method is adopted, that is, the sub-pulse reference signal is constructed to respectively Perform matched filtering processing; then, accumulate the matched filtering results of all sub-pulses in a pulse, and finally obtain The pulse compression results ; Step 4.9: Use the filter obtained in step 4.7 to filter the pulse compression result of step 4.8 to complete interference suppression and target positioning, that is, ； Step 4.10: Repeat steps 4.7 to 4.9 until all The interference suppression result of the speed channel is obtained as 。

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