Narrow pulse interference suppression method based on energy stability judgment and spectrum correlation

Abstract

The invention discloses a narrow pulse interference suppression method based on energy stability judgment and spectrum correlation, and the method comprises the steps: dividing radar intermediate frequency modulo data into a plurality of data intervals according to an amplitude continuous over-threshold criterion, and carrying out the narrow pulse suppression of the data intervals meeting the narrow pulse amplitude and width judgment criterion, a data interval which only meets amplitude and does not meet width judgment is divided into echo signal subintervals and interference signal subintervals, correlation coefficients of signal frequency spectrums of the echo signal subintervals and local signal frequency spectrums are calculated, each interference signal subinterval is traversed, correlation coefficients of the frequency spectrums and the sum of the signal frequency spectrums of the echo signal subintervals and the local signal frequency spectrums are calculated, and the frequency spectrums of the interference signal subintervals are calculated. And performing narrow pulse interference detection and suppression on the interference signal subintervals according to a correlation coefficient judgment criterion, and repeating the process until all data intervals are processed. According to the invention, detection and suppression of narrow pulse interference in a high signal-to-noise ratio echo background are realized, and the target detection performance of the radar in an interference environment is improved.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, and in particular to a narrow pulse interference suppression method based on energy stationarity decision and spectrum correlation. Background Technology

[0002] With the development of technology, the electromagnetic environment faced by radar has become increasingly complex due to industrial and equipment interference, non-cooperative frequency occupation, signal leakage, and the increase of illegal transmission sources. Various types of interference seriously threaten the performance of radar, which not only affects the working efficiency of radar, but may even hinder the normal operation of radar.

[0003] Radar systems are susceptible to various types of interference during operation, with narrow-pulse interference being a common and typical example. Narrow-pulse interference refers to short-duration interference signals within the radar receiver's bandwidth. Its pulse width is often equal to or smaller than the pulse width transmitted by the radar. This interference typically originates from other radar systems operating at the same frequency but asynchronously, or from jammers. When narrow-pulse interference enters the radar receiver, it superimposes with the echo signal. After pulse compression processing, this results in an excessively high detection threshold, leading to missed target detections and severely impacting the radar system's performance.

[0004] For other synchronous and asynchronous radar systems, narrow pulse interference can be detected and suppressed through amplitude judgment, interference width judgment, and asynchronous interference judgment. However, jammers usually use composite interference composed of different interference types. When the radar faces composite interference of narrow pulse and false target, the jammer will superimpose one or more narrow pulse interferences with a large interference-to-signal-to-noise ratio on the high signal-to-noise ratio false target echo. Traditional methods cannot distinguish between false target echo and narrow pulse interference through amplitude judgment, thus failing to meet the interference width judgment criterion, resulting in the failure of anti-jamming methods. After the narrow pulse interference is processed by pulse compression, the target detection threshold is greatly raised, making it impossible to detect and track the target normally, which seriously affects the radar's combat effectiveness.

[0005] Therefore, there is an urgent need to invent a narrow pulse interference suppression method with strong detection and suppression capabilities to solve the problem of suppressing the two combined interferences of narrow pulses and false targets, and improve the radar's anti-narrow pulse interference capability. Summary of the Invention

[0006] The purpose of this invention is to provide a narrow pulse interference suppression method based on energy stability decision and spectrum correlation, which can detect and suppress narrow pulse interference in the background of high signal-to-noise ratio echo, and has strong anti-interference ability.

[0007] The technical solution to achieve the purpose of this invention is: a narrow pulse interference suppression method based on energy stationarity decision and spectrum correlation, comprising the following steps:

[0008] Step 1: Set the absolute amplitude detection threshold T1. Search for two or more consecutive data intervals in the pulse repetition period where the absolute amplitude detection threshold T1 is greater than the distance unit amplitude value.

[0009] Step 2: Set thresholds T2 and T3. If the width W of the i-th data interval... i If T3 < W, then narrow pulse interference is determined to exist. Values ​​are assigned to the intermediate frequency I / Q data of the corresponding distance cell in the data interval, and the process continues to traverse the next data interval. If T3 ≤ W i If W ≤ T2, then it is determined that there is no narrow pulse interference, and the process continues to traverse the next data interval; if W i If T2 is reached, proceed to step 3.

[0010] Step 3: Set the threshold T4, let f ESD (d)=M d / M d-1 d=2, ..., L, M d M d-1 This represents the intermediate frequency modulus data of the d-th and d-1-th distance cells in the middle, when the judgment condition max(f ESD (d))>T4 and judgment condition 1 / min(f ESD If (d))>T4 is not satisfied, it is determined that there is no narrow pulse interference, and the process returns to step 2 to continue traversing the next data interval; otherwise, it indicates that there is an energy mutation phenomenon, and the d values ​​that meet the conditions are written into the energy mutation index set J in ascending order. i In the middle, based on the energy mutation index, the data interval is divided into K+1 sub-intervals S1~S K+1 ;

[0011] Step 4: Set threshold T5 and divide each sub-interval into interference signal sub-intervals and echo signal sub-intervals according to the energy relationship of each sub-interval;

[0012] Step 5: Calculate the envelope summation result (SE) of the spectrum of each echo signal sub-interval. FFTEVL Spectral envelope ST of locally transmitted signal FFTEVL correlation coefficient ;

[0013] Step 6: Calculate the spectral envelope SJ of the j-th interference signal sub-interval. FFTEVL According to SJ FFTEVL SE FFTEVL and ST FFTEVL Calculate the correlation coefficient between the sum of the spectral envelopes of the j-th interference signal sub-interval and the echo signal sub-interval and the spectral envelope of the local transmitted signal. ;

[0014] Step 7, according to and Detection and suppression of narrow pulse interference, if For the intermediate frequency I / Q data of the distance cell corresponding to the j-th interference signal sub-interval, no processing is performed, and the process returns to step 6 to continue traversing the next interference signal sub-interval; if The j-th interference signal sub-interval is determined to be narrow pulse interference. The intermediate frequency I / Q data of the distance cell corresponding to the current interference signal sub-interval are all assigned the value 0.7*T0. Then, return to step 6 to continue traversing the next interference signal sub-interval.

[0015] Step 8: Repeat steps 6 and 7 until narrow pulse interference detection and suppression are completed in all interference signal sub-intervals;

[0016] Step 9: Repeat steps 2 to 8 until narrow pulse interference detection and suppression are completed for all data intervals.

[0017] A computer device includes a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the narrow pulse interference suppression method based on energy stability decision and spectrum correlation.

[0018] A computer program product includes computer instructions for causing a computer to execute the narrow pulse interference suppression method based on energy stability decision and spectrum correlation.

[0019] Compared with the prior art, the present invention has the following significant advantages: (1) By using the energy stability decision criterion, the signal interval and the interference interval are finely divided, and then the narrow pulse interference under the high signal-to-noise ratio echo background is detected and suppressed according to the spectral correlation coefficient decision criterion of the signal interval and the interference interval, thereby improving the target detection performance of the radar under the interference environment; (2) The method is simple and has strong real-time performance, which improves the radar's anti-narrow pulse interference capability and improves the radar's combat effectiveness. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a narrow pulse interference suppression method based on energy stability decision and spectrum correlation according to the present invention.

[0021] Figure 2 This is a graph showing the simulation results of narrow pulse interference under noisy background in an embodiment of the present invention.

[0022] Figure 3 These are simulation results curves of the intermediate frequency modulus calculation data and pulse compression modulus calculation data after narrow pulse suppression in a noisy background, as described in the embodiments of the present invention and the traditional method.

[0023] Figure 4 This is a graph showing the simulation results of narrow pulse interference under echo background in an embodiment of the present invention.

[0024] Figure 5 These are simulation results curves of intermediate frequency modulus calculation data and pulse compression modulus calculation data after narrow pulse suppression in the background using the traditional method in this embodiment of the invention.

[0025] Figure 6 These are simulation result curves of the intermediate frequency modulus data and pulse compression modulus data obtained by the method of the present invention under narrow pulse suppression in the background of the present invention. Detailed Implementation

[0026] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0027] like Figure 1 As shown, the present invention provides a narrow pulse interference suppression method based on energy stationarity decision and spectrum correlation, comprising the following steps:

[0028] Step 1: Set the absolute amplitude detection threshold T1. Search for two or more consecutive data intervals in the pulse repetition period where the absolute amplitude detection threshold T1 is greater than the distance unit amplitude value.

[0029] Step 2: Set thresholds T2 and T3. If the width W of the i-th data interval... i If T3 < W, then narrow pulse interference is determined to exist. Values ​​are assigned to the intermediate frequency I / Q data of the corresponding distance cell in the data interval, and the process continues to traverse the next data interval. If T3 ≤ W i If W ≤ T2, then it is determined that there is no narrow pulse interference, and the process continues to traverse the next data interval; if W i If T2 is reached, proceed to step 3.

[0030] Step 3: Set the threshold T4, let f ESD (d)=M d / M d-1 d=2, ..., L, M d M d-1 This represents the intermediate frequency modulus data of the d-th and d-1-th distance cells in the middle, when the judgment condition max(f ESD (d))>T4 and judgment condition 1 / min(f ESD If (d))>T4 is not satisfied, it is determined that there is no narrow pulse interference, and the process returns to step 2 to continue traversing the next data interval; otherwise, it indicates that there is an energy mutation phenomenon, and the d values ​​that meet the conditions are written into the energy mutation index set J in ascending order. i In the middle, based on the energy mutation index, the data interval is divided into K+1 sub-intervals S1~S K+1 ;

[0031] Step 4: Set threshold T5 and divide each sub-interval into interference signal sub-intervals and echo signal sub-intervals according to the energy relationship of each sub-interval;

[0032] Step 5: Calculate the envelope summation result (SE) of the spectrum of each echo signal sub-interval. FFTEVL Spectral envelope ST of locally transmitted signal FFTEVL correlation coefficient ;

[0033] Step 6: Calculate the spectral envelope SJ of the j-th interference signal sub-interval. FFTEVL According to SJ FFTEVL SE FFTEVL and ST FFTEVL Calculate the correlation coefficient between the sum of the spectral envelopes of the j-th interference signal sub-interval and the echo signal sub-interval and the spectral envelope of the local transmitted signal. ;

[0034] Step 7, according to and Detection and suppression of narrow pulse interference, if For the intermediate frequency I / Q data of the distance cell corresponding to the j-th interference signal sub-interval, no processing is performed, and the process returns to step 6 to continue traversing the next interference signal sub-interval; if The j-th interference signal sub-interval is determined to be narrow pulse interference. The intermediate frequency I / Q data of the distance cell corresponding to the current interference signal sub-interval are all assigned the value 0.7*T0. Then, return to step 6 to continue traversing the next interference signal sub-interval.

[0035] Step 8: Repeat steps 6 and 7 until narrow pulse interference detection and suppression are completed in all interference signal sub-intervals;

[0036] Step 9: Repeat steps 2 to 8 until narrow pulse interference detection and suppression are completed for all data intervals.

[0037] As a specific example, step 1 is as follows:

[0038] Step 1.1: Perform modulus calculation on the intermediate frequency (IF) IQ data to obtain IF modulus data M, M = {M1, M2, ..., M}. L}, where L represents the number of distance cells in the modulus data;

[0039] Step 1.2: Calculate the mean value T0 of the distance cell corresponding to 10% of the pulse repetition period of the modulus data, and take 8 times the mean value T0 as the absolute amplitude detection threshold T1 of the narrow pulse interference;

[0040] Step 1.3: Traverse each distance cell of the modulus data during the pulse repetition cycle, searching for data intervals where two or more consecutive distance cell amplitude values ​​are greater than the threshold T1. There are N data intervals. Record the starting and ending distance cells of each data interval, and store them in sets A and B respectively, where A = {A1, A2, ..., A...}. N}, B = {B1, B2, ..., B} N}

[0041] As a specific example, step 2 is as follows:

[0042] Step 2.1: Set the threshold Threshold τ is the pulse width of the transmitted pulse, f s The system sampling rate, The symbol represents the floor function; The symbol represents the floor function;

[0043] Step 2.2: Calculate the width W of the i-th data interval. i The calculation formula is W i =B i -A i +1, if the width W of the i-th data interval i If <T3, where i=1,2,...,N, then it is determined that narrow pulse interference exists. The intermediate frequency I / Q data of the corresponding distance cell in the data interval are all assigned the value 0.7*T0, and the next data interval is traversed.

[0044] Step 2.3, if T3≤W i If the value is less than or equal to T2, it is determined that there is no narrow pulse interference. The intermediate frequency I / Q data of the corresponding distance cell in the data interval is not processed, and the next data interval is traversed.

[0045] Step 2.4, if W i If T2 is reached, proceed to step 3 to continue detecting the energy stability of the data interval by using the ratio between adjacent distance cells.

[0046] As a specific example, step 3 is as follows:

[0047] Step 3.1: Perform energy stationarity testing on the i-th data interval, setting a threshold T4=10. When the judgment condition max(f ESD (d))>T4 and judgment condition 1 / min(f ESD If (d))>T4 is not satisfied, it is determined that there is no narrow pulse interference. The intermediate frequency I / Q data of the corresponding distance unit in the data interval is not processed, and the process returns to step 2 to continue traversing the next data interval.

[0048] Step 3.2, when the condition max(f) is satisfied ESD (d))>T4 or satisfy condition 1 / min(f) ESD When (d))>T4, it indicates that there is an energy mutation phenomenon in the i-th data interval. The d values ​​that meet the condition are written into the energy mutation index set J in ascending order. i In the middle, J i ={J i1 J i2 , ..., J iK}, where K represents the number of energy mutations within the data interval;

[0049] Step 3.3: Based on the energy mutation index, divide the data interval into K+1 sub-intervals S1~S2. K+1 The formula for dividing the data into sub-intervals is as follows:

[0050]

[0051] The max(A) function calculates the maximum value of all elements in vector A, and the min(A) function calculates the minimum value of all elements in vector A.

[0052] As a specific example, step 4 is as follows:

[0053] Step 4.1: Set the threshold , where k=1,……,K+1; the min(A) function represents finding the minimum value of all elements in vector A; the mean(A) function represents finding the average value of all elements in vector A;

[0054] Step 4.2: Calculate the mean of the sub-intervals. Sub-intervals whose mean is greater than or equal to the threshold T5 are identified as interference signal sub-intervals SJ, where SJ = {SJ1, SJ2, ..., SJ...} P}, where P is the number of interference signal sub-intervals;

[0055] Step 4.3: Determine the sub-intervals whose mean is less than the threshold T5 as echo signal sub-intervals SE, where SE = {SE1, SE2, ..., SE...} Q}, where Q is the number of echo signal sub-intervals.

[0056] As a specific example, step 5 is as follows:

[0057] Step 5.1: Calculate the envelope summation result SE of the spectrum of each echo signal sub-interval. FFTEVL Spectral envelope ST of locally transmitted signal FFTEVL correlation coefficient The envelope summation result of the spectrum of each signal sub-interval (SE) FFTEVL The calculation formula is:

[0058]

[0059] Spectral envelope ST of locally transmitted signal FFTEVL The calculation formula is:

[0060]

[0061] Where st is the locally transmitted signal, f EVL (A) is the envelope calculation function for the complex variable A, and the calculation formula is:

[0062]

[0063] Where real(·) and img(·) represent the functions for taking the real part and imaginary part, respectively, and fft(A,B) represents the Fast Fourier Transform of variable A with a number of points B. FFTLen The number of points in the Fast Fourier Transform is calculated using the following formula:

[0064]

[0065] in, f is the floor function. s Represents the sampling rate;

[0066] Step 5.2, according to SE FFTEVL and ST FFTEVL Calculate the correlation coefficient between the cumulative sum of the spectral envelopes of the echo signal sub-intervals and the spectral envelope of the locally transmitted signal. The calculation formula is:

[0067]

[0068] Where Cov(·) represents the covariance function and σ(·) represents the standard deviation function.

[0069] As a specific example, step 6 is as follows:

[0070] Step 6.1: Calculate the spectral envelope SJ of the j-th interference signal sub-interval. FFTEVL The calculation formula is:

[0071]

[0072] Where j = 1, ..., P;

[0073] Step 6.2, according to SJ FFTEVL SE FFTEVL and ST FFTEVLCalculate the correlation coefficient between the sum of the spectral envelopes of the j-th interference signal sub-interval and the echo signal sub-interval and the spectral envelope of the local transmitted signal. The calculation formula is:

[0074] .

[0075] As a specific example, step 7 is as follows:

[0076] Step 7.1, according to and Detection and suppression of narrow pulse interference, if The intermediate frequency I / Q data of the distance cell corresponding to the j-th interference signal sub-interval is not processed, and the process returns to step 6 to continue traversing the next interference signal sub-interval.

[0077] Step 7.2, if The j-th interference signal sub-interval is determined to be narrow pulse interference. The intermediate frequency I / Q data of the corresponding distance cell of the current interference signal sub-interval are all assigned the value 0.7*T0. Then, return to step 6 to continue traversing the next interference signal sub-interval.

[0078] The present invention also provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the narrow pulse interference suppression method based on energy stability decision and spectrum correlation.

[0079] The present invention also provides a computer program product, including computer instructions for causing a computer to execute the described narrow pulse interference suppression method based on energy stability decision and spectrum correlation.

[0080] Example

[0081] To verify the effectiveness of the narrow pulse interference suppression method based on energy stability decision and spectrum correlation provided by this invention, simulation experiments and measured data analysis were conducted in this embodiment. The simulation experiment examples and measured data analysis are further explained below.

[0082] Simulation Experiment Example 1: Simulation of Narrow Pulse Interference under Noise Background Figure 2 and Figure 3 As shown, the simulation parameters are as follows: the mean radar floor noise is 42dB, the narrow pulse width is 2μs, and the range cell positions at the start and end of the narrow pulse are 126 and 135, respectively. Figure 2 (a) in the figure represents the intermediate frequency modulus data after superimposed narrow pulse interference. Figure 2 (b) in the figure represents the pulse compression modulus data without narrow pulse suppression, derived from... Figure 2 As shown in (b), due to the influence of narrow pulse interference, after pulse compression processing, the system detection threshold is raised by about 50dB near the location of narrow pulse interference. Figure 3 (a) and Figure 3 (b) in the figure represents the intermediate frequency modulus data and pulse compression modulus data after narrow pulse suppression using the traditional method. Figure 3 (c) and Figure 3 In the figure, (d) represents the intermediate frequency modulus data and pulse compression modulus data after narrow pulse suppression by the method of the present invention. Figure 3 (a)~ Figure 3 As shown in (d), both the traditional algorithm and the method of this invention can effectively detect and suppress narrow pulse interference in a noisy background. After the narrow pulse interference located at the distance cell position of 126~135 is suppressed, the detection threshold of the system is not raised, and the average radar base noise remains at about 42dB.

[0083] Simulation Experiment Example 2: Narrow Pulse Interference Simulation under Target Background Figure 4 , Figure 5 and Figure 6 As shown. The simulation parameters are as follows: the mean radar floor noise is 42dB, the target echo uses a zero-IF linear frequency modulated signal with a signal duration of 20μs and a signal bandwidth of 4MHz, the system sampling rate is 5MHz, the starting and ending range cell positions of the target echo are 100 and 199 respectively, the target signal-to-noise ratio is 73.67-42=31.67dB, the narrow pulse interference width is 2μs, the starting and ending range cell positions of the narrow pulse interference are 126 and 135 respectively, and the interference signal-to-interference ratio of the narrow pulse interference is 93.71-73.67=20.04dB. Figure 4 (a) in the figure represents the intermediate frequency modulus data after superimposed narrow pulse interference. Figure 4 (b) in the figure represents pulse compression data without narrow pulse suppression. Figure 5 (a) in the figure represents the intermediate frequency modulus data after processing narrow pulse interference using traditional methods. Figure 5 (b) in the figure represents the pulse compression and modulus calculation data after processing narrow pulse interference using traditional methods. Figure 5 It is known that the traditional narrow pulse rejection method cannot detect narrow pulses in the background of echo. The reason is that the traditional algorithm first judges the absolute amplitude of the signal. When the signal-to-noise ratio of the echo signal is high and the interference-to-signal ratio of the narrow pulse is greater than zero, the traditional algorithm does not consider the stability of the background of narrow pulse detection. It cannot accurately obtain the start and end positions of the narrow pulse based on the position of the energy change. The narrow pulse width detection condition cannot be met, resulting in the failure of narrow pulse detection. The narrow pulse interference raises the constant false alarm rate (CFAR) detection threshold, ultimately leading to the inability to extract the target. Figure 6(a) in the figure represents the intermediate frequency modulus data after processing narrow pulse interference using the method of this invention. Figure 6 (b) in the figure represents the pulse compression and modulus calculation data after narrow pulse interference processing using the method of this invention. Figure 6 As can be seen, the method of the present invention first searches for a data interval in which two or more consecutive distance unit amplitude values ​​are greater than the threshold T1. The starting and ending distance units of this data interval are recorded in sets A and B, respectively, i.e., A={A1}={100} and B={B1}={199}. The threshold... The data width is 100, satisfying the condition W1≥T2. Further, based on the stationarity criterion of the narrow pulse detection background, the set of energy abrupt change locations is determined: J1={J... 11 J 12}={126,136}, based on the location of the energy mutation J 11 and J 12 Divide the data interval [A1, B1] into three sub-intervals: S1, S2, and S3, i.e., S1 = [A1, B1]. 11 -1]、S2=[J 11 J 12 -1] and S3=[J 12 [B1] Based on the threshold T5, S2 is determined to be an interference signal sub-interval, and S1 and S3 are determined to be echo signal sub-intervals. The envelope accumulation result SE of the spectrum of the S1 and S3 signal sub-intervals is further calculated. FFTEVL Calculate the spectral envelope ST of the locally transmitted signal. FFTEVL According to SE FFTEVL and ST FFTEVL Calculate the correlation coefficient r between the cumulative sum of the spectral envelopes of the echo signal sub-intervals and the spectral envelope of the locally transmitted signal. E =0.78, further calculate the envelope accumulation result SJ of the spectrum of the interference signal sub-interval. FFTEVL According to SJ FFTEVL SE FFTEVL and ST FFTEVL Calculate the correlation coefficient r between the sum of the spectral envelopes of the interference signal sub-interval S2, the echo signal sub-intervals S1 and S3, and the spectral envelope of the local transmitted signal. EJ =0.31, further analysis of the spectral correlation coefficient shows that it meets the requirements. The judgment condition is used to determine the interference signal sub-interval S2 as narrow pulse interference. The intermediate frequency I / Q data of the corresponding distance cell of the current interference signal sub-interval are all assigned a value of 0.7*T0. This enables the detection and suppression of narrow pulse interference in the background of echo, and finally successfully extracts the target in the background of narrow pulse interference.

[0084] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A narrow pulse interference suppression method based on energy stationarity decision and spectral correlation, characterized in that, Includes the following steps: Step 1: Set the absolute amplitude detection threshold T1. Search for two or more consecutive data intervals in the pulse repetition period where the absolute amplitude detection threshold T1 is greater than the distance unit amplitude value. Step 2: Set thresholds T2 and T3. If the width W of the i-th data interval... i If <T3, then narrow pulse interference is determined to exist. Values ​​are assigned to the intermediate frequency I / Q data of the corresponding distance cell in the data interval, and the process continues to traverse the next data interval. If T3≤W i If W ≤ T2, then it is determined that there is no narrow pulse interference, and the process continues to traverse the next data interval; if W i If T2 is reached, proceed to step 3. Step 3: Set the threshold T4, let f ESD (d)=M d / M d-1 d=2, ..., L, M d M d-1 This represents the intermediate frequency modulus data of the d-th and d-1-th distance cells in the middle, when the judgment condition max(f ESD (d))>T4 and judgment condition 1 / min(f ESD If (d))>T4 is not satisfied, it is determined that there is no narrow pulse interference, and the process returns to step 2 to continue traversing the next data interval; otherwise, it indicates that there is an energy mutation phenomenon, and the d values ​​that meet the conditions are written into the energy mutation index set J in ascending order. i In the middle, based on the energy mutation index, the data interval is divided into K+1 sub-intervals S1~S K+1 ; Step 4: Set threshold T5 and divide each sub-interval into interference signal sub-intervals and echo signal sub-intervals according to the energy relationship of each sub-interval; Step 5: Calculate the envelope summation result (SE) of the spectrum of each echo signal sub-interval. FFTEVL Spectral envelope ST of locally transmitted signal FFTEVL correlation coefficient ; Step 6: Calculate the spectral envelope SJ of the j-th interference signal sub-interval. FFTEVL According to SJ FFTEVL SE FFTEVL and ST FFTEVL Calculate the correlation coefficient between the sum of the spectral envelopes of the j-th interference signal sub-interval and the echo signal sub-interval and the spectral envelope of the local transmitted signal. ; Step 7, according to and Detection and suppression of narrow pulse interference, if For the intermediate frequency I / Q data of the distance cell corresponding to the j-th interference signal sub-interval, no processing is performed, and the process returns to step 6 to continue traversing the next interference signal sub-interval; if The j-th interference signal sub-interval is determined to be narrow pulse interference. The intermediate frequency I / Q data of the distance cell corresponding to the current interference signal sub-interval are all assigned the value 0.7*T0. Then, return to step 6 to continue traversing the next interference signal sub-interval. Step 8: Repeat steps 6 and 7 until narrow pulse interference detection and suppression are completed in all interference signal sub-intervals; Step 9: Repeat steps 2 to 8 until narrow pulse interference detection and suppression are completed for all data intervals.

2. The narrow pulse interference suppression method based on energy stability decision and spectrum correlation according to claim 1, characterized in that, Step 1 is as follows: Step 1.1: Perform modulus calculation on the intermediate frequency (IF) IQ data to obtain IF modulus data M, M = {M1, M2, ..., M}. L }, where L represents the number of distance cells in the modulus data; Step 1.2: Calculate the mean value T0 of the distance cell corresponding to 10% of the pulse repetition period of the modulus data, and take 8 times the mean value T0 as the absolute amplitude detection threshold T1 of the narrow pulse interference; Step 1.3: Traverse each distance cell of the modulus data during the pulse repetition cycle, searching for data intervals where two or more consecutive distance cell amplitude values ​​are greater than the threshold T1. There are N data intervals. Record the starting and ending distance cells of each data interval, and store them in sets A and B respectively, where A = {A1, A2, ..., A...}. N }, B = {B1, B2, ..., B} N } 3. The narrow pulse interference suppression method based on energy stability decision and spectrum correlation according to claim 2, characterized in that, Step 2 is as follows: Step 2.1: Set the threshold Threshold τ is the pulse width of the transmitted pulse, f s The system sampling rate, The symbol represents the floor function; The symbol represents the floor function; Step 2.2: Calculate the width W of the i-th data interval. i The calculation formula is W i =B i -A i +1, if the width W of the i-th data interval i If <T3, where i=1,2,...,N, then it is determined that narrow pulse interference exists. The intermediate frequency I / Q data of the corresponding distance cell in the data interval are all assigned the value 0.7*T0, and the next data interval is traversed. Step 2.3, if T3≤W i If the value is less than or equal to T2, it is determined that there is no narrow pulse interference. The intermediate frequency I / Q data of the corresponding distance cell in the data interval is not processed, and the next data interval is traversed. Step 2.4, if W i If T2 is reached, proceed to step 3 to continue detecting the energy stability of the data interval by using the ratio between adjacent distance cells.

4. The narrow pulse interference suppression method based on energy stability decision and spectrum correlation according to claim 3, characterized in that, Step 3 is as follows: Step 3.1: Perform energy stationarity testing on the i-th data interval, setting a threshold T4=10. When the judgment condition max(f ESD (d))>T4 and judgment condition 1 / min(f ESD If (d))>T4 is not satisfied, it is determined that there is no narrow pulse interference. The intermediate frequency I / Q data of the corresponding distance unit in the data interval is not processed, and the process returns to step 2 to continue traversing the next data interval. Step 3.2, when the condition max(f) is satisfied ESD (d))>T4 or satisfy condition 1 / min(f) ESD When (d))>T4, it indicates that there is an energy mutation phenomenon in the i-th data interval. The d values ​​that meet the condition are written into the energy mutation index set J in ascending order. i In the middle, J i ={J i1 J i2 , ..., J iK }, where K represents the number of energy mutations within the data interval; Step 3.3: Based on the energy mutation index, divide the data interval into K+1 sub-intervals S1~S2. K+1 The formula for dividing the data into sub-intervals is as follows: ； The max(A) function calculates the maximum value of all elements in vector A, and the min(A) function calculates the minimum value of all elements in vector A.

5. The narrow pulse interference suppression method based on energy stability decision and spectrum correlation according to claim 4, characterized in that, Step 4 is as follows: Step 4.1: Set the threshold , where k=1,……,K+1; the min(A) function represents finding the minimum value of all elements in vector A; the mean(A) function represents finding the average value of all elements in vector A; Step 4.2: Calculate the mean of the sub-intervals. Sub-intervals whose mean is greater than or equal to the threshold T5 are identified as interference signal sub-intervals SJ, where SJ = {SJ1, SJ2, ..., SJ...} P }, where P is the number of interference signal sub-intervals; Step 4.3: Determine the sub-intervals whose mean is less than the threshold T5 as echo signal sub-intervals SE, where SE = {SE1, SE2, ..., SE...} Q }, where Q is the number of echo signal sub-intervals.

6. The narrow pulse interference suppression method based on energy stability decision and spectrum correlation according to claim 5, characterized in that, Step 5 is as follows: Step 5.1: Calculate the envelope summation result SE of the spectrum of each echo signal sub-interval. FFTEVL Spectral envelope ST of locally transmitted signal FFTEVL correlation coefficient The envelope summation result of the spectrum of each signal sub-interval (SE) FFTEVL The calculation formula is: ； Spectral envelope ST of locally transmitted signal FFTEVL The calculation formula is: ； Where st is the locally transmitted signal, f EVL (A) is the envelope calculation function for the complex variable A, and the calculation formula is: ； Where real(·) and img(·) represent the functions for taking the real part and imaginary part, respectively, and fft(A,B) represents the Fast Fourier Transform of variable A with a number of points B. FFTLen The number of points in the Fast Fourier Transform is calculated using the following formula: ； in, f is the floor function. s Represents the sampling rate; Step 5.2, according to SE FFTEVL and ST FFTEVL Calculate the correlation coefficient between the cumulative sum of the spectral envelopes of the echo signal sub-intervals and the spectral envelope of the locally transmitted signal. The calculation formula is: ； Where Cov(·) represents the covariance function and σ(·) represents the standard deviation function.

7. The narrow pulse interference suppression method based on energy stability decision and spectrum correlation according to claim 6, characterized in that, Step 6 is as follows: Step 6.1: Calculate the spectral envelope SJ of the j-th interference signal sub-interval. FFTEVL The calculation formula is: ； Where j = 1, ..., P; Step 6.2, according to SJ FFTEVL SE FFTEVL and ST FFTEVL Calculate the correlation coefficient between the sum of the spectral envelopes of the j-th interference signal sub-interval and the echo signal sub-interval and the spectral envelope of the local transmitted signal. The calculation formula is: 。 8. The narrow pulse interference suppression method based on energy stationarity decision and spectrum correlation according to claim 7, characterized in that, Step 7 is as follows: Step 7.1, according to and Detection and suppression of narrow pulse interference, if The intermediate frequency I / Q data of the distance cell corresponding to the j-th interference signal sub-interval is not processed, and the process returns to step 6 to continue traversing the next interference signal sub-interval. Step 7.2, if The j-th interference signal sub-interval is determined to be narrow pulse interference. The intermediate frequency I / Q data of the corresponding distance cell of the current interference signal sub-interval are all assigned the value 0.7*T0. Then, return to step 6 to continue traversing the next interference signal sub-interval.

9. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the narrow pulse interference suppression method based on energy stability decision and spectrum correlation as described in any one of claims 1 to 8.

10. A computer program product, characterized in that, Includes computer instructions for causing a computer to execute the narrow pulse interference suppression method based on energy stability decision and spectrum correlation as described in any one of claims 1 to 8.

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