A main lobe interference layering suppression method based on wavelet decomposition

Abstract

This invention discloses a layered suppression method for main lobe interference based on wavelet decomposition. For situations with high interference-to-signal ratio and high signal-to-noise ratio, it estimates interference parameters based on time-domain echo signals and uses the correlation between the interference and the transmitted signal to determine the location and frequency of the interference. This avoids significant deviations in the estimated interference parameters caused by strong interference energy, thus improving the accuracy of interference estimation. Furthermore, this invention estimates interference parameters based on time-domain echo signals and further divides the echo into interference, target, and noise components using wavelet decomposition, retaining the target component to reconstruct the echo. While suppressing interference, it maximizes the integrity of target information, reduces target energy loss, and improves target detection probability. This invention retains the target component of the echo and removes interference components entering the radar main lobe based on wavelet decomposition, avoiding interference energy leakage caused by poor filter design or masking methods, which could affect target detection.

Description

Technical Field

[0001] This invention belongs to the field of radar technology, specifically relating to a method for hierarchical suppression of main lobe interference based on wavelet decomposition. Background Technology

[0002] Ensuring survival and completing detection missions in complex electromagnetic environments has always been a key concern in the radar field. Radar jamming techniques have evolved from simple methods such as initial noise blocking and placing artificial jamming sources to complex forms such as deceptive jamming or multiple jamming methods coexisting. Furthermore, if interference enters the main lobe beamwidth of the radar, it will gain the radar's main lobe gain, making it impossible to filter out using methods such as sidelobe cancellation or sidelobe concealment. This will have a significant impact on target detection.

[0003] DRFM (Digital Radio Frequency Memory) jammers are typically used to generate deceptive interference. Jamming types include full-pulse store-and-forward, intermittent sampling store-and-forward, and intermittent sampling store-and-forward with convolutional modulation. Intermittent sampling store-and-forward involves sampling, storing, and forwarding the signal until the received signal ends. This method improves the problem of false target lag to some extent, but the coherence between the jamming signal and the transmitted signal deteriorates, and multiple false target peaks still form after pulse compression. Intermittent sampling store-and-forward jamming with convolutional modulation superimposes convolutional noise on top of intermittent sampling store-and-forward jamming. The resulting jamming signal possesses both the strong deceptiveness of intermittent sampling jamming and the strong suppressive power of noise jamming. After pulse compression, energy high points are formed over a large area, and multiple intermittent sampling jammings over a wide area will overwhelm the target, preventing the radar from effectively filtering out the interference and detecting the target's location.

[0004] In related technologies, one type of target detection method against main lobe interference is based on time-domain, frequency-domain, or time-frequency-domain masking methods for interference identification. This method eliminates high-energy regions under high interference-to-signal ratio (CNR) conditions to achieve interference suppression. However, when the overlap between interference and the target is large, the target may be missed due to significant energy loss. Furthermore, if the sidelobes of the interference cover the target, it will also lead to energy loss. Another type of related technology involves designing filters based on interference parameter estimation to filter out interference. However, this method has two problems: 1. It is easily affected by high CNR; for example, time-frequency-domain estimation methods may experience significant deviations in estimation results due to the high sidelobes of the interference. 2. It relies heavily on the design accuracy of the filter, requiring a high filter order, and is also affected by interference sidelobes.

[0005] It is evident that the aforementioned target detection methods against main lobe interference suffer from low detection accuracy due to errors in interference parameter estimation and energy loss of the target during interference suppression. Summary of the Invention

[0006] To address the aforementioned problems in the existing technology, this invention provides a main lobe interference layering suppression method based on wavelet decomposition. The technical problem to be solved by this invention is achieved through the following technical solution:

[0007] This invention provides a method for hierarchical suppression of main lobe interference based on wavelet decomposition, comprising:

[0008] The minimum interference slice length L based on the magnitude estimation of the echo signal. pre And according to the minimum interference slice length L pre The matching coefficients are divided into K segment matching coefficients;

[0009] The K sub-matching coefficients are pulse-compressed with the echo signal respectively. The decision threshold is calculated based on the variance var(k) of the absolute value of the pulse-compressed k-th sub-matching coefficient in the time domain, where k = 1, 2, ..., K.

[0010] Using the aforementioned decision threshold Interference information is determined by performing interference information judgment on the K-segment sub-matching coefficients after pulse compression to obtain the frequency segment corresponding to the interference slice; wherein, the number of interference slices and the number of interference sub-matching coefficients and the corresponding frequency segment are the same, and the interference sub-matching coefficients are sub-matching coefficients containing interference information;

[0011] For each interference slice, its boundary is slid within a preset range, and the boundary of each interference slice is corrected based on the inflection point of the peak energy change curve during the sliding process. Then, the interference sub-matching coefficient corresponding to each interference slice is corrected according to the corrected boundary.

[0012] The parameters of each interference slice are estimated using the corrected interference sub-matching coefficients and the echo signal;

[0013] Based on the parameters, wavelet decomposition is performed on the echo signal at the location of each interference slice to obtain H sub-modes, and the interference sub-mode is determined according to the matching degree between the H sub-modes and the corrected interference sub-matching coefficients.

[0014] After determining the correlation coefficients of the H sub-modes based on the interference sub-matching coefficients, the sub-modes containing the target component are determined from the sub-modes corresponding to the correlation coefficient values, and the reconstructed echo signal is obtained after de-skewing processing.

[0015] In one embodiment of the present invention, the minimum interference slice length L is estimated based on the magnitude of the echo signal. pre And according to the minimum interference slice length L pre The matching coefficients are divided into K segment matching coefficients, including:

[0016] Calculate the magnitude of the echo signal:

[0017]

[0018] In the formula, n represents the nth interference slice, M represents the number of interference slices, τ represents the width of the interference slice, and T... s Indicates the interference sampling period, A j K represents the amplitude of the interference slice. r Indicates the frequency modulation of the transmitted signal, t j Represents the time delay introduced by the distance between the jammer and the radar, where rect(·) is the rectangular gate function;

[0019] The magnitude of the echo signal is differentially processed:

[0020]

[0021] In the formula, ' represents the first derivative, δ(·) represents the impulse function, and t represents time. When t = t j +(n-1)T s At that time, A J '(t)=A j When t = t j +(n-1)T s When +τ, A J '(t)=-A j ;

[0022] Sort the difference processing results according to time t, and generate vector A = [t]. j ,t j +T s ,…,t j +(M-1)T s ] and vector B = [t j +τ,t j +T s +τ,…,t j +(M-1)T s +τ], and calculate the average length of the interference slice based on vector A and vector B. Where mean represents the calculated average;

[0023] Estimate the number of interference forwarding attempts, N;

[0024] Based on the number of forwardings N and the average length Calculate the minimum interference slice length L pre And utilizing the minimum interference slice length L pre The matching coefficients are divided into K segment matching coefficients.

[0025] In one embodiment of the present invention, the step of estimating the number of forwardings N of the interference slice includes:

[0026] After pulse compression of all interference slices, the number of interference forwardings N is estimated based on the number of peaks.

[0027] Based on the number of forwardings N and the average length The minimum interference slice length L is calculated using the following formula. pre :

[0028]

[0029] In one embodiment of the present invention, the K sub-matching coefficients are pulse-compressed with the echo signal respectively, and the decision threshold is calculated based on the variance var(k) of the absolute value of the pulse-compressed k-th sub-matching coefficient in the time domain. The steps include:

[0030] The K segment matching coefficients are pulse-compressed with the echo signal respectively, and the variance var(k) of the absolute value of the pulse-compressed k-th segment matching coefficient in the time domain is calculated.

[0031] Determine the maximum variance var of the absolute value of the sub-matching coefficient pulse in the time domain after compression. max (k) and minimum value var min After (k), the maximum value var max (k) and minimum value var min The difference between (k) is divided into a preset number of I sub-intervals;

[0032] The variance of the absolute value in the time domain located in the i-th sub-interval is quantized into g. i , where g i Let be the center value of the variance of the absolute value in the time domain located in the i-th interval;

[0033] Determine the number f of variances of the time-domain absolute values ​​located in the i-th subinterval. i And calculate the quantization value g. i Probability of occurrence:

[0034] Select the quantization value g of the η=1th subinterval η Using the quantized value g η The quantized values ​​corresponding to the I sub-intervals are divided into a set A = {g} i |g i ≤g η} and B = {g i |g i >g η} and calculate the first proportionality coefficient respectively. Second proportional coefficient

[0035] Based on the first proportionality coefficient, the second proportionality coefficient, and the quantization value g i Calculate the average amplitude λ0 of set A, the average amplitude λ1 of set B, and the overall average amplitude λ, where,

[0036] Calculate the variance σ between sets A and B based on the average magnitude λ0 of set A, the average magnitude λ1 of set B, and the overall average magnitude λ. 2 (g η )=w0(λ-λ0) 2 +w1(λ-λ1) 2 ;

[0037] Let η = η + 1, and return the quantization value g of the selected ηth sub-interval. η Using the quantized value g η The quantized values ​​corresponding to the I sub-intervals are divided into a set A = {g} i |g i ≤g η} and B = {g i |g i >g η The steps are repeated until η = I;

[0038] Based on all the calculated variances σ 2 (g η ), determine what makes σ 2 (g η (To obtain the maximum value) Reaching the judgment threshold

[0039] In one embodiment of the present invention, the decision threshold is utilized. The steps for determining the frequency band corresponding to the interference information by performing interference information determination on the K-segment matching coefficients after pulse compression include:

[0040] If var(k) is less than the decision threshold If the matching coefficient of the kth segment corresponding to var(k) contains interference information, the frequency band corresponding to the interference information can be determined based on the matching coefficient of the kth segment corresponding to var(k); otherwise, the matching coefficient of the kth segment corresponding to var(k) does not contain interference information.

[0041] In one embodiment of the present invention, the step of sliding the boundary of each interference slice within a preset range, correcting the boundary of each interference slice based on the inflection point of the peak energy change curve during the sliding process, and then correcting the interference sub-matching coefficient corresponding to each interference slice according to the corrected boundary includes:

[0042] For each interference slice, its first boundary is slid within a first preset range and its second boundary is slid within a second preset range, where the first preset range is t. n1 -L pre / 2~t n1 +L pre / 2, the second preset range is t n2 -L pre / 2~t n2 +L pre / 2, [t] n1 ,t n2 [This represents the preset range of sampling points;]

[0043] Calculate the first peak energy change curve corresponding to the first boundary and the second peak energy change curve corresponding to the second boundary during the sliding process. Take the inflection point of the first peak energy change curve as the first boundary T after the interference slice is corrected. n,1 The inflection point of the second peak energy change curve is taken as the second boundary T after the interference slice is corrected. n,2 ;

[0044] Based on the corrected first boundary T n,1 With the modified second boundary T n,2 Correct the matching coefficients of the interference sub-slices corresponding to each interference slice.

[0045] In one embodiment of the present invention, the step of estimating the parameters of each interference slice using the corrected interference sub-matching coefficients and the echo signal includes:

[0046] The modified interfering sub-matching coefficients and the echo signal are pulse-compressed respectively to estimate the location of the interference slice corresponding to the modified interfering sub-matching coefficients: P=[P1,…,P n ,…,P M ];

[0047] Based on the frequency modulation coefficient K of the linear frequency modulated signal r The estimated interference frequency band of the interference slice corresponding to the corrected interference sub-matching coefficient is: [K r T n,1 ,K r T n,2 ].

[0048] In one embodiment of the present invention, the parameters include the location of each interference slice and the corresponding frequency band;

[0049] Based on the parameters, the echo signal at the location of each interference slice is decomposed into H sub-modes, and the interference sub-modes are determined according to the matching degree between the H sub-modes and the corrected interference sub-matching coefficients. This step includes:

[0050] L-level wavelet decomposition is performed on the real and imaginary parts of the echo signals at the locations of the M interference slices to obtain H sub-modes for each interference slice;

[0051] Calculate the matching degree of the H sub-modes and interfering sub-matching coefficients for each of the M interfering slices.

[0052] like If the maximum value in the submode is greater than or equal to the preset threshold ε1, then the submode corresponding to the maximum value is selected as the interference submode. Conversely, let L = L + 1, and return to the step of performing L-level wavelet decomposition on the real and imaginary parts of the echo signals at the locations of the M interference slices respectively.

[0053] In one embodiment of the present invention, before the step of performing wavelet decomposition on the echo signal at the location of each interference slice to obtain H sub-modes, and determining the sub-mode as an interference component based on the matching degree between the H sub-modes and the corrected interference sub-matching coefficients, the method further includes:

[0054] The echo signal at the location of the interfering slice is deskewed.

[0055] In one embodiment of the present invention, the steps of determining the correlation coefficients of the H sub-modes based on the interference sub-matching coefficients, determining the sub-modes containing the target component from the sub-modes corresponding to the correlation coefficient values, and obtaining the reconstructed echo signal after de-skewing processing include:

[0056] With interference slice length L n The correlation coefficients of the H sub-modes are obtained by truncating the interfering sub-matching coefficients using a sliding window. Among them, L n =T n,2 -T n,1 ;

[0057] Get The correlation coefficients and their corresponding submodes that are greater than or equal to a set threshold ε2 like and Consistent, then For interference submodes; conversely, for non-interference submodes, then For the target sub-mode;

[0058] By filtering out interfering sub-modes from the sub-modes, the reconstructed signal is obtained.

[0059] The reconstructed signal Multiply by exp(jπK) r t 2 ), to obtain the reconstructed echo signal

[0060] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0061] 1. This invention addresses situations with high interference-to-signal ratio and high signal-to-noise ratio by estimating interference parameters based on time-domain echo signals. It utilizes the correlation between interference and transmitted signals to determine the location and frequency of interference, thus avoiding significant deviations in the estimated interference parameters caused by strong interference energy and improving the accuracy of interference estimation.

[0062] 2. This invention addresses situations with high interference-to-signal ratio and high signal-to-noise ratio. It estimates interference parameters based on time-domain echo signals and further divides the echo into interference, target, and noise components using wavelet decomposition, retaining the target component to reconstruct the echo. Under the premise of suppressing interference, it ensures the integrity of target information as much as possible, reduces target energy loss, and improves the target detection probability.

[0063] 3. This invention preserves the target component of the echo and removes interference components based on wavelet decomposition, thus avoiding the leakage of interference energy caused by poor filter design or masking method, which would affect the detection of the target.

[0064] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0065] Figure 1 This is a flowchart of a wavelet decomposition-based main lobe interference hierarchical suppression method provided in an embodiment of the present invention;

[0066] Figure 2a This is a schematic diagram of the echo signal magnitude provided in an embodiment of the present invention;

[0067] Figure 2b This is a schematic diagram of the differential processing result of the echo signal magnitude provided in an embodiment of the present invention;

[0068] Figure 3 This is a schematic diagram of the pulse pressure characteristic curve provided in an embodiment of the present invention. Detailed Implementation

[0069] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0070] Figure 1This is a flowchart of a wavelet decomposition-based main lobe interference layered suppression method provided in an embodiment of the present invention. Figure 1 As shown, this embodiment of the invention provides a method for hierarchical suppression of main lobe interference based on wavelet decomposition, including:

[0071] S1, The minimum interference slice length L based on the magnitude estimation of the echo signal. pre And according to the minimum interference slice length L pre The matching coefficients are divided into K segment matching coefficients;

[0072] S2. Perform pulse compression on the K sub-matching coefficients and the echo signal respectively. Calculate the decision threshold based on the variance var(k) of the absolute value of the pulse-compressed k-th sub-matching coefficient in the time domain, where k = 1, 2, ..., K.

[0073] S3, Utilizing Judgment Thresholds Interference information is determined by performing interference information judgment on the K-segment sub-matching coefficients after pulse compression to obtain the frequency band corresponding to the interference slice; wherein, the number of interference slices and the number of interference sub-matching coefficients and the corresponding frequency bands are the same, and the interference sub-matching coefficients are sub-matching coefficients containing interference information;

[0074] S4. For each interference slice, slide its boundary within a preset range, and after correcting the boundary of each interference slice based on the inflection point of the peak energy change curve during the sliding process, correct the interference sub-matching coefficient corresponding to each interference slice according to the corrected boundary.

[0075] S5. Estimate the parameters of each interference slice using the corrected interference sub-matching coefficients and echo signals;

[0076] S6. Based on the parameters, perform wavelet decomposition on the echo signal at the location of each interference slice to obtain H sub-modes, and determine the interference sub-modes according to the matching degree between the H sub-modes and the corrected interference sub-matching coefficients.

[0077] S7. After determining the correlation coefficients of H sub-modes based on the interference sub-matching coefficients, determine the sub-modes containing the target component from the sub-modes corresponding to the correlation coefficient values, and obtain the reconstructed echo signal after de-skewing.

[0078] In this embodiment, the radar system performs interference parameter estimation and interference suppression in stages based on the received echo signal. In the first stage, the radar estimates the interference parameters according to the time-domain characteristics of the echo signal. Specifically, the radar can estimate the minimum interference slice length L based on the magnitude of the echo signal. pre The interference sub-matching coefficients containing interference information are found according to the interference slice matching algorithm, and the interference length is finely corrected by combining the characteristics of pulse compression.

[0079] Furthermore, based on the interference parameters estimated in the first stage, the echo signals at the corresponding interference locations are de-skewing and decomposed into wavelet components, which are then decomposed into target, interference, and noise components. Subsequently, based on the different sub-matching coefficients of the interference and the target, the target and interference are distinguished, thereby retaining the sub-modes classified as targets. Finally, the reconstructed target echo signal is obtained by reconstructing the modes and de-skewing.

[0080] Optionally, in step S1 above, the minimum interference slice length L is estimated based on the magnitude of the echo signal. pre And according to the minimum interference slice length L pre The matching coefficients are divided into K segment matching coefficients, including:

[0081] S101. Calculate the magnitude of the echo signal:

[0082]

[0083] In the formula, n represents the nth interference slice, M represents the number of interference slices, and M < T. p / T s τ represents the width of the interference slice, T s Indicates the interference sampling period, A j T represents the amplitude of the interference slice. p K represents the transmission signal duration. r Indicates the frequency modulation of the transmitted signal, t j Represents the time delay introduced by the distance between the jammer and the radar, where rect(·) is the rectangular gate function:

[0084]

[0085] S102. Differential processing is performed on the magnitude of the echo signal:

[0086]

[0087] In the formula, ' represents the first derivative, δ(·) represents the impulse function, and t represents time. When t = t j +(n-1)T s At that time, A J '(t)=A j When t = t j +(n-1)T s When +τ, A J '(t)=-A j .

[0088] Figure 2a This is a schematic diagram of the echo signal magnitude provided in an embodiment of the present invention. Figure 2b This is a schematic diagram of the differential processing result of the echo signal magnitude provided in an embodiment of the present invention. For example... Figures 2a-2bAs shown, since the echo signal has a high signal-to-interference ratio, the magnitude of the echo signal can reflect the distribution of interference, and the difference result of the echo signal magnitude reflects the start and end positions of the interference slice.

[0089] S103. After sorting the difference processing results according to time t, generate vector A = [t] j ,t j +T s ,…,t j +(M-1)T s ] and vector B = [t j +τ,t j +T s +τ,…,t j +(M-1)T s +τ], and calculate the average length of the interference slice based on vector A and vector B. Where mean represents the calculated average;

[0090] S104. Estimate the number of interference forwarding attempts N;

[0091] S105. Based on the number of interference forwarding times N and the average length Calculate the minimum interference slice length L pre And utilize the minimum interference slice length L pre The matching coefficients are divided into K segment matching coefficients.

[0092] Optionally, the step of estimating the number of forwardings N of the interfering slice includes:

[0093] After pulse compression of all interference slices, the number of interference forwardings N is estimated based on the number of peaks.

[0094] Specifically, in A i ~B i The number of peak values ​​in the pulse compression within the segment is counted, and this number of peak values ​​is the estimated number of interference forwardings N, where A i ~B i This represents the start delay and end delay of the i-th interference slice.

[0095] Based on the number of interference forwardings N and the average length The minimum interference slice length L is calculated using the following formula. pre :

[0096]

[0097] This embodiment calculates the decision threshold based on the maximum inter-class variance criterion. Optionally, in step S2, the K sub-matching coefficients are pulse-compressed with the echo signal respectively, and the decision threshold is calculated based on the variance var(k) of the absolute value of the pulse-compressed k-th sub-matching coefficient in the time domain. The steps include:

[0098] S201. Perform pulse compression on the K segment matching coefficients and the echo signal respectively, and calculate the variance var(k) of the absolute value of the time domain of the pulse compression of the k segment matching coefficients.

[0099] S202. Determine the maximum variance var of the absolute value of the time domain after pulse compression of the sub-matching coefficients. max (k) and minimum value var min After (k), the maximum value var max (k) and minimum value var min The difference between (k) is divided into a preset number of I sub-intervals;

[0100] S203. Quantize the variance of the absolute value in the time domain of the i-th sub-interval into g. i , where g i Let be the center value of the variance of the absolute value in the time domain located in the i-th interval;

[0101] S204. Determine the number f of variances of the absolute values ​​in the time domain located in the i-th subinterval. i And calculate the quantization value g. i Probability of occurrence:

[0102] S205. Select the quantization value g of the η=1th sub-interval. η Using the quantized value g η Divide the quantized values ​​corresponding to the I sub-intervals into a set A = {g} i |g i ≤g η} and B = {g i |g i >g η} and calculate the first proportionality coefficient respectively. Second proportional coefficient

[0103] S206. Based on the first proportionality coefficient, the second proportionality coefficient, and the quantization value g i Calculate the average amplitude λ0 of set A, the average amplitude λ1 of set B, and the overall average amplitude λ, where,

[0104] S207. Calculate the variance σ between set A and set B based on the average amplitude λ0 of set A, the average amplitude λ1 of set B, and the overall average amplitude λ. 2(g η )=w0(λ-λ0) 2 +w1(λ-λ1) 2 ;

[0105] S208. Let η = η + 1, and return the quantization value g of the selected ηth sub-interval. η Using the quantized value g η The quantized values ​​corresponding to the I sub-intervals are divided into a set A = {g} i |g i ≤g η} and B = {g i |g i >g η The steps are repeated until η = I;

[0106] S209. Based on the calculated variances σ 2 (g η ), determine what makes σ 2 (g η (To obtain the maximum value) Reaching the judgment threshold In other words, let g η The values ​​of g are g1, g2, ..., g I until a value is found that makes σ 2 (g η (To obtain the maximum value) That is, satisfying:

[0107] Furthermore, utilizing judgment thresholds The steps for determining the frequency band corresponding to the interference information by performing interference information determination on the K-segment matching coefficients after pulse compression include:

[0108] If var(k) is less than the decision threshold If the matching coefficient of the kth segment corresponding to var(k) contains interference information, the frequency band corresponding to the interference information can be determined based on the matching coefficient of the kth segment corresponding to var(k); otherwise, the matching coefficient of the kth segment corresponding to var(k) does not contain interference information.

[0109] In this embodiment, since the interference is part of the echo signal and the echo signal has a strong interference-to-signal ratio, the K-segment sub-matching coefficients, after pulse compression of the interference segment in the echo signal, will generate strong primary false targets and continuous secondary false targets. This phenomenon leads to a large variance in the sub-matching coefficients containing the interference frequency segment after pulse compression. Therefore, this embodiment estimates the decision threshold based on the post-pulse compression variance of different sub-matching coefficients, and then makes a decision based on the decision threshold to obtain the sub-matching coefficients containing the interference frequency segment.

[0110] In step S4 above, the step of sliding the boundary of each interference slice within a preset range, correcting the boundary of each interference slice based on the inflection point of the peak energy change curve during the sliding process, and then correcting the interference sub-matching coefficient corresponding to each interference slice according to the corrected boundary includes:

[0111] For each interference slice, its first boundary is slid within a first preset range and its second boundary is slid within a second preset range, where the first preset range is t. n1 -L pre / 2~t n1 +L pre / 2, the second preset range is t n2 -L pre / 2~t n2 +L pre / 2, [t] n1 ,t n2 [This represents the preset range of sampling points;]

[0112] Calculate the first peak energy change curve corresponding to the first boundary and the second peak energy change curve corresponding to the second boundary during the sliding process. Take the inflection point of the first peak energy change curve as the first boundary T after the interference slice is corrected. n,1 The inflection point of the second peak energy change curve is taken as the second boundary T after the interference slice is corrected. n,2 ;

[0113] Based on the corrected first boundary T n,1 With the modified second boundary T n,2 Correct the matching coefficients of the interference sub-slices corresponding to each interference slice.

[0114] Figure 3 This is a schematic diagram of the pulse pressure characteristic curve provided in an embodiment of the present invention. Figure 3 As shown, please refer to Figure 3 The peak energy of the pulse compression interference gradually increases with the increase of the matching coefficient length, reaching its maximum when the matching coefficient matches the interference. In this embodiment, the pre-estimated interference slice is further corrected by adjusting the left and right boundaries. The change in the peak energy function of the pulse compression interference during the correction process is referenced... Figure 3 The schematic diagram of the pulse compression characteristic curve shown uses the inflection point of the pulse compression characteristic curve as the left and right boundaries of the estimated interference slice.

[0115] Specifically, for the nth interference slice, the preset range of the number of sampling points is [t]. n1 ,t n2 Taking the correction of its left boundary as an example, the left boundary is at t n1 -L pre / 2~tn1 +L pre Slide within a range of / 2 in units of sampling intervals, while keeping the right boundary stationary. The true sampling point range of the nth interference slice is denoted as [T]. n1 ,T n2 ], normally, t n1 -L pre / 2<T n1 <t n1 +L pre / 2. That is, the left boundary t l In t n1 -L pre / 2~T n1 There is no interference within the range, and during the sliding of the left boundary within this range, the peak value of the interference after pulse compression does not suffer energy loss. The total energy at this time is:

[0116]

[0117] Among them, J n H represents the nth interference slice. n This represents the interfering sub-matching coefficient corresponding to the nth interfering slice.

[0118] Left boundary t l In T n1 to t n1 +L pre When the range is 2 / 2, which is the frequency band where the interference is located, the left boundary slides from left to right within this range. l The peak energy of the post-pulse pressure interference continues to increase. The continuous decrease can be represented as:

[0119]

[0120] At this point, the second derivative of the peak function of the left boundary pulse compression can be expressed as:

[0121]

[0122] Therefore, during the sliding process at the left boundary, the energy of the pulse pressure interference peak is recorded. The inflection point of the peak change curve is T. n '1, that is, the corrected left boundary, then T n '1=T n1 .

[0123] Similarly, when correcting the right boundary, the right boundary t r Energy of pulse pressure interference peak during sliding process The inflection point of the peak change curve is T. n '2, that is, the corrected right boundary, then T n '2=Tn2 Pulse pressure peak Regarding the right boundary position t r The expression is:

[0124]

[0125] At this point, the second derivative of the peak function of the right boundary pulse compression can be expressed as:

[0126]

[0127] The above formula can be used to obtain the minimum value of the second derivative at the sampling point where the inflection point is located, and based on this, the right boundary value after the interference slice is corrected can be obtained.

[0128] Finally, based on the corrected left boundary T n,1 With the corrected right boundary T n,2 Correct the matching coefficients of the interference sub-slices corresponding to each interference slice.

[0129] Furthermore, step S5 above, which involves estimating the parameters of each interference slice using the corrected interference sub-matching coefficients and the echo signal, includes:

[0130] The modified interfering sub-matching coefficients and the echo signal are pulse-compressed respectively to estimate the location of the interference slice corresponding to the modified interfering sub-matching coefficients: P=[P1,…,P n ,…,P M ];

[0131] Based on the frequency modulation coefficient K of the linear frequency modulated signal r The estimated interference frequency band of the interference slice corresponding to the corrected interference sub-matching coefficient is: [K r T n,1 ,K r T n,2 ].

[0132] Specifically, the range of sampling points for the corrected interference sub-matching coefficients is denoted as:

[0133] Here, the M rows of T contain M interference slices, and each interference slice contains a corresponding matching coefficient.

[0134] Next, pulse compression is performed between the corrected interfering sub-matching coefficients and the echo signal to obtain the location of the interference slice represented by each corrected interfering sub-matching coefficient, denoted as: P = [P1, ..., P2]. n ,…,P MFurthermore, regarding the estimated interference frequency band, it should be noted that since the radar's transmitted signal is a linear frequency modulated signal, assuming the transmitted signal frequency starts from 0 and the echo signal has been down-converted to the fundamental frequency, then at time T... n,1 The corresponding frequency is K r T n,1 The interference frequency band is: [K r T n,1 ,K r T n,2 ].

[0135] In this embodiment, the parameters include the location of each interference slice, the corresponding frequency band, and the length;

[0136] In step S6, based on the parameters, wavelet decomposition is performed on the echo signal at the location of each interference slice to obtain H sub-modes. The step of determining the interference sub-modes based on the matching degree between the H sub-modes and the corrected interference sub-matching coefficients includes:

[0137] S601. Perform L-level wavelet decomposition on the real and imaginary parts of the echo signals at the locations of the M interference slices to obtain H sub-modes.

[0138] S602. Calculate the matching degree of the H sub-modes and the interfering sub-matching coefficients for each of the M interference slices.

[0139] S603, if If the maximum value in the submode is greater than or equal to the preset threshold ε1, then the submode corresponding to the maximum value is selected as the interference submode. Conversely, let L = L + 1, and return to the steps described above for performing L-level wavelet decomposition on the real and imaginary parts of the echo signals at the locations of the M interference slices.

[0140] Submodes represent different frequency bands of the echo signal after deskewing. After wavelet decomposition at a preset number of decomposition levels L, the submodes should contain only one of the target or interference components.

[0141] In step S601 above, performing L-level wavelet decomposition on the real and imaginary parts of the echo signals at the locations of the M interference slices yields M sub-modes u of the real and imaginary parts. r n,1 ,u r n,2 ,…,u r n,M and u i n,1 ,u i n,2 ,…,u i n,M Then the i-th submode of the n-th interference slice can be represented as un,i =u r n,i +ju i n,i .

[0142] In step S602 above, wavelet reconstruction is performed on the real and imaginary parts of the H sub-modes to obtain the reconstructed signal r of the real part. R (t) and the reconstructed signal r of the imaginary part I The submode reconstruction signal is represented as r(t) = r(t). R (t)+jr I (t), multiply the submode reconstruction signal by exp(jπK) r t2) Obtain the sub-mode reconstruction echo and calculate the correlation coefficients between the H sub-modes and the interference segment to obtain the desired result. if If the match is greater than or equal to the preset threshold ε1, then the maximum matching degree is selected. The corresponding sub-mode μ M As an interference component, otherwise let L = L + 1 for further decomposition. Based on the final decomposition level L, calculate the matching degree between the H sub-modes obtained from the L-level wavelet decomposition and the interference matching coefficients. if If the degree of matching is greater than or equal to the set threshold ε1, then the sub-mode corresponding to the maximum matching degree is selected. As an interfering component.

[0143] It should be noted that before the step of performing wavelet decomposition on the echo signal at the location of each interference slice to obtain H sub-modes, and determining the sub-modes as interference components based on the matching degree between the H sub-modes and the corrected interference sub-matching coefficients, the following steps are also included:

[0144] The echo signal at the location of the interfering slice is deskewed.

[0145] Specifically, multiply the echo signal by exp(-jπK) r t 2 ), obtain x d (t), and take the real and imaginary parts as the de-skewed echo signal, the de-skewed echo signal x d (t) contains only a single frequency component, the frequency component of which is related to the frequency modulation coefficient of the linear frequency modulated signal and the time delay of the target and the interference.

[0146] Optionally, in step S7 above, after determining the correlation coefficients of H sub-modes based on the interference sub-matching coefficients, determining the sub-modes containing the target component from the sub-modes corresponding to the correlation coefficient values, and obtaining the reconstructed echo signal after de-skewing processing, includes:

[0147] S701, with interference slice length Ln The interference sub-matching coefficients are truncated using a sliding window to obtain the correlation coefficients of H sub-modes. Among them, L n =T n,2 -T n,1 ;

[0148] S702, Obtain The correlation coefficients and their corresponding submodes that are greater than or equal to a set threshold ε2 like and Consistent, then For interference submodes; conversely, for non-interference submodes, then For the target sub-mode;

[0149] S703. Filter out interfering sub-modes in the sub-modes to obtain the reconstructed signal.

[0150] S704, Reconstruct the signal Multiply by exp(jπK) r t 2 ), to obtain the reconstructed echo signal

[0151] In this embodiment, taking the nth interference slice as an example, the matching degree calculation process involves wavelet reconstruction of the submodes of the nth interference slice, and multiplying the reconstructed submode signal by exp(jπK). r t 2 The sub-mode reconstruction echoes are obtained, and the correlation coefficient is calculated with the matching coefficient of each segment to obtain the matching degree. After that, take As a submode u n,1 highest correlation coefficient By analogy, the correlation coefficients of the H sub-modes of the nth interference slice can be obtained.

[0152] In step S702 above, record Submodes corresponding to correlation coefficients greater than or equal to a set threshold ε2 like With interference sub-mode If the labels are the same, it means It is an interfering component; if Then it means For the target component; if Then it means This is a noise component.

[0153] Since both the target and the interference are part of the transmitted signal, the sub-modes belonging to both components will have a high degree of matching with the matching coefficients. The sub-mode belonging to the interference will have a high degree of matching with the corresponding interference matching coefficient; the sub-mode belonging to the target will have a lower degree of matching with the interference matching coefficient, but will have a higher degree of matching with a certain segment of the transmitted signal. Therefore, by performing a sliding window truncation on the matching coefficients, a segment will have a high correlation coefficient with the sub-mode belonging to the target; the sub-mode belonging to the noise is uncorrelated with the transmitted signal, so the calculated correlation coefficient is low.

[0154] In this embodiment, the sub-modes contained in the target component are selected as the modes to be reconstructed, and M reconstructed signal segments are obtained after wavelet reconstruction. The M signal segments obtained at this point no longer contain interference components. Replacing the deskewing signal segments with these M signal segments, while keeping the other segments in the echo signal unchanged, yields the wavelet-reconstructed signal. Multiply by exp(jπK) r t 2 The reconstructed echo signal can be obtained at this time. The echo after interference filtering.

[0155] The main lobe interference hierarchical suppression method based on wavelet decomposition provided in this invention will be further verified through simulation experiments below.

[0156] Simulation conditions:

[0157] The simulation system of this invention is an Intel(R) Core(TM) i5-12500h CPU@2.50GHz, a 64-bit Windows 11 operating system, and the simulation software is MATLAB (R2020b).

[0158] The effectiveness of the proposed method is verified through simulation experiments. The experimental scenario is set as follows: the radar system transmits a linear frequency modulated signal and receives target echoes with SNR = [4,6,8,10,12,...,26] dB and random distance; the jammer randomly transmits JSR = [2 0 ,…,2 12 The interference is randomized. Here, JSR represents the interference-to-signal ratio, and SNR represents the signal-to-noise ratio.

[0159] The detection probability of the target was calculated using the wavelet decomposition-based main lobe interference hierarchical suppression method provided in this invention, and the comparison of detection probabilities under different SNR and JNR conditions was obtained, as shown in Table 1:

[0160] Table 1 Target detection probability under different JSR and SNR

[0161]

[0162]

[0163] As can be seen from Table 1, when JSR = 1-16 and SNR = 4-20dB, the target detection probability is low, basically remaining below 67%; however, when JSR and SNR are high, the target detection probability is basically maintained at a level above 97%, indicating that the present invention has a good target detection probability in environments with high interference-to-signal ratio and high signal-to-noise ratio.

[0164] In summary, this invention achieves anti-interference detection in environments with high interference-to-signal ratio and high signal-to-noise ratio by employing a two-stage approach: time-domain parameter estimation and wavelet decomposition for interference filtering. In the first stage, the correlation between interference and the transmitted signal is utilized to improve the accuracy of interference parameter estimation. In the second stage, the frequency separability of the target and interference after deskewing is leveraged to filter out interference using wavelet decomposition. This two-stage processing enhances the performance of anti-interference target detection.

[0165] As can be seen from the above embodiments, the beneficial effects of the present invention are as follows:

[0166] 1. This invention addresses situations with high interference-to-signal ratio and high signal-to-noise ratio by estimating interference parameters based on time-domain echo signals. It utilizes the correlation between interference and transmitted signals to determine the location and frequency of interference, thus avoiding significant deviations in the estimated interference parameters caused by strong interference energy and improving the accuracy of interference estimation.

[0167] 2. This invention addresses situations with high interference-to-signal ratio and high signal-to-noise ratio. It estimates interference parameters based on time-domain echo signals and further divides the echo into interference, target, and noise components using wavelet decomposition, retaining the target component to reconstruct the echo. Under the premise of suppressing interference, it ensures the integrity of target information as much as possible, reduces target energy loss, and improves the target detection probability.

[0168] 3. This invention preserves the target component of the echo and removes interference components based on wavelet decomposition, thus avoiding the leakage of interference energy caused by poor filter design or masking method, which would affect the detection of the target.

[0169] In the description of this invention, 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 indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0170] The use of terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples" indicates 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 the present invention. 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. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0171] Although this application has been described herein in conjunction with various embodiments, other variations of the disclosed embodiments can be understood and implemented by those skilled in the art in carrying out the claimed application by reviewing the accompanying drawings, the disclosure, and the appended claims.

[0172] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for hierarchical suppression of main lobe interference based on wavelet decomposition, characterized in that, include: Minimum interference slice length based on echo signal magnitude estimation and according to the minimum interference slice length The matching coefficients are divided into Joke matching coefficient; The The segment matching coefficients are pulse compressed with the echo signal, according to the... The variance of the absolute value of the individual matching coefficient pulse in the time domain after pulse compression Calculate the decision threshold, where, ; The pulse compression is performed using the aforementioned decision threshold. Interference information is determined by segment matching coefficients to obtain the frequency band corresponding to the interference slice; wherein, the number of interference slices and the number of interference sub-matching coefficients and the corresponding frequency bands are the same, and the interference sub-matching coefficients are sub-matching coefficients that contain interference information; For each interference slice, its boundary is slid within a preset range, and the boundary of each interference slice is corrected based on the inflection point of the peak energy change curve during the sliding process. Then, the interference sub-matching coefficient corresponding to each interference slice is corrected according to the corrected boundary. The parameters of each interference slice are estimated using the corrected interference sub-matching coefficients and the echo signal; Based on the parameters, wavelet decomposition is performed on the echo signal at the location of each interference slice to obtain... Sub-modalities, and according to the The degree of matching between each sub-mode and the corrected interference sub-matching coefficient is used to determine the interference sub-mode; Determine the interference sub-matching coefficient. After determining the correlation coefficients of each sub-mode, the sub-mode containing the target component is identified from the sub-modes corresponding to the correlation coefficient values, and the reconstructed echo signal is obtained after de-skewing.

2. The wavelet decomposition-based main lobe interference hierarchical suppression method according to claim 1, characterized in that, Minimum interference slice length based on echo signal magnitude estimation and according to the minimum interference slice length The matching coefficients are divided into Joke matching coefficient, including: Calculate the magnitude of the echo signal: ； In the formula, Indicates the first One interfering slice, Indicates the number of interfering slices. Indicates the width of the interference slice. Indicates the interference sampling period. Indicates the amplitude of the interference slice. This indicates the time delay introduced by the distance between the jammer and the radar. It is a rectangular gate function; The magnitude of the echo signal is differentially processed: ； In the formula, Denotes the first derivative. Represents the impulse function. Indicates time, where, when hour, ,when hour, ; According to time Sort the difference processing results to generate a vector. sum vector And according to the vector sum vector Calculate the average length of the interference slice : ;in, This indicates the calculation of the average value; Estimate the number of interference forwardings ; Based on the number of forwards and the average length Calculate the minimum interference slice length And utilize the minimum interference slice length The matching coefficients are divided into Joke matching coefficient.

3. The wavelet decomposition-based main lobe interference hierarchical suppression method according to claim 2, characterized in that, Estimate the number of forwardings of the interference slice The steps include: After pulse compression of all interference slices, the number of interference relays is estimated based on the number of peaks. ; Based on the number of forwards and the average length The minimum interference slice length is calculated using the following formula. : 。 4. The wavelet decomposition-based main lobe interference hierarchical suppression method according to claim 1, characterized in that, The The segment matching coefficients are pulse compressed with the echo signal, according to the... The variance of the absolute value of the individual matching coefficient pulse in the time domain after pulse compression The steps for calculating the decision threshold include: The The segment matching coefficients are pulse-compressed with the echo signal and the first segment is calculated. Variance of the absolute value of the time domain of the matching coefficient pulse after compression ; Determine the maximum variance of the absolute value of the sub-matching coefficient pulse in the time domain after compression. and minimum value Then, the maximum value and minimum value The difference between them is divided into preset quantities. Sub-intervals; Will be located in the The variance quantization of the absolute value in the time domain of each sub-interval is as follows: ,in, For the position located at the The central value of the variance of the absolute value in the time domain of each interval; Determine the location at the The number of variances of the absolute values ​​in the time domain of each subinterval And calculate the quantized value. Probability of occurrence: ; Select the first Quantization values ​​of each sub-interval Using quantified values The The quantized values ​​corresponding to each sub-interval are divided into sets. and And calculate the first proportionality coefficient respectively. Second proportional coefficient ; Based on the first proportional coefficient, the second proportional coefficient, and the quantized value Calculate the set average amplitude ,gather average amplitude and overall average amplitude ,in, , , ; According to the set average amplitude ,gather average amplitude and overall average amplitude Calculate the set With sets variance between ; make and return to the selected first Quantization values ​​of each sub-interval Using quantified values The The quantized values ​​corresponding to each sub-interval are divided into sets. and The steps, until ; Based on all the calculated variances , determine To obtain the maximum value The judgment threshold was reached. .

5. The wavelet decomposition-based main lobe interference hierarchical suppression method according to claim 4, characterized in that, The pulse compression is performed using the aforementioned decision threshold. The steps for determining interference information using segment matching coefficients to obtain the frequency band corresponding to the interference information include: like Less than the judgment threshold ,but The corresponding number The joke matching coefficient contains interference information, according to The corresponding number The frequency band corresponding to the interference information is determined by the segment matching coefficient; conversely, the frequency band corresponding to the interference information is determined by the matching coefficient. The corresponding number The joke matching coefficient does not contain interference information.

6. The main lobe interference hierarchical suppression method based on wavelet decomposition according to claim 1, characterized in that, For each interference slice, the steps include sliding its boundary within a preset range, correcting the boundary of each interference slice based on the inflection point of the peak energy change curve during the sliding process, and then correcting the interference sub-matching coefficient corresponding to each interference slice according to the corrected boundary, including: For each interference slice, its first boundary is slid within a first preset range and its second boundary is slid within a second preset range, wherein the first preset range is... The second preset range is , The preset range of sampling points; Calculate the first peak energy change curve corresponding to the first boundary and the second peak energy change curve corresponding to the second boundary during the sliding process. Take the inflection point of the first peak energy change curve as the first boundary after the interference slice correction. The inflection point of the second peak energy change curve is taken as the second boundary after the interference slice is corrected. ; Based on the corrected first boundary With the modified second boundary Correct the matching coefficients of the interference sub-slices corresponding to each interference slice.

7. The wavelet decomposition-based main lobe interference hierarchical suppression method according to claim 6, characterized in that, The step of estimating the parameters of each interference slice using the corrected interference sub-matching coefficients and the echo signal includes: The modified interfering sub-matching coefficients and the echo signal are pulse compressed respectively to estimate the location of the interference slice corresponding to the modified interfering sub-matching coefficients: , Indicates the number of interfering slices; Based on the frequency modulation coefficient of the linear frequency modulated signal The estimated interference frequency band of the interference slice corresponding to the corrected interference sub-matching coefficient is: .

8. The main lobe interference hierarchical suppression method based on wavelet decomposition according to claim 6, characterized in that, The parameters include the location of each interference slice and its corresponding frequency band; Based on the parameters, wavelet decomposition is performed on the echo signal at the location of each interference slice to obtain... Sub-modalities, and according to the The step of determining the interfering sub-mode by matching the sub-mode with the corrected interfering sub-matching coefficient includes: To each The real and imaginary parts of the echo signal at the location of each interference slice are analyzed. Layer wavelet decomposition, yielding Submodalities; Calculate separately Interference slices The matching degree between sub-mode and interfering sub-matching coefficients ; like The maximum value in the range is greater than or equal to the preset threshold. Then the sub-mode corresponding to the maximum value is selected as the interference sub-mode. Conversely, then let and return the respective pairs The real and imaginary parts of the echo signal at the location of each interference slice are analyzed. The steps of layer wavelet decomposition.

9. The main lobe interference hierarchical suppression method based on wavelet decomposition according to claim 8, characterized in that, Wavelet decomposition was performed on the echo signal at the location of each interference slice to obtain Sub-modalities, and according to the Before determining the sub-mode as an interference component by matching the sub-mode with the corrected interference sub-matching coefficient, the method further includes: The echo signal at the location of the interfering slice is deskewed.

10. The wavelet decomposition-based main lobe interference hierarchical suppression method according to claim 8, characterized in that, Determine the interference sub-matching coefficient. The steps of determining the sub-modes containing the target component from the sub-modes corresponding to the correlation coefficient values ​​after obtaining the correlation coefficients, and obtaining the reconstructed echo signal after de-skewing, include: With interference slice length The interference sub-matching coefficients are truncated using a sliding window to obtain the unit. correlation coefficient of submodal ,in, ; Get The value is greater than or equal to the set threshold. Correlation coefficients and their corresponding submodes ;like and Consistent, then For interference submodes; conversely, for non-interference submodes, then For the target sub-mode; By filtering out interfering sub-modes from the sub-modes, the reconstructed signal is obtained. ; The reconstructed signal Multiply Obtain the reconstructed echo signal , The frequency modulation coefficient represents the frequency modulation coefficient of a linear frequency modulated signal. Indicates the time.

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