A sub-band peak energy detection sidelobe false target elimination method

Abstract

The application discloses a sub-band peak energy detection sidelobe false target elimination method, relates to the field of underwater acoustic array signal processing, and fully utilizes the'spatial consistency' difference between a target and a sidelobe in sub-band processing. On the basis of sub-band peak detection, sub-band peak bifurcation caused by target direction disturbance is eliminated through image inflation and corrosion, a main sidelobe amplitude ratio threshold is given from a distribution function, and sidelobe false target elimination is realized in combination with multi-threshold decision. The application overcomes high false alarm of traditional post-sub-band processing, is used in combination with adaptive processing, and has an engineering application value.

Description

Technical fields:

[0001] This invention belongs to the field of underwater acoustic array signal processing, specifically relating to a method for eliminating sidelobe false targets in subband peak energy detection. Background technology:

[0002] Conventional passive broadband detection typically obtains omnidirectional broadband detection results through multi-channel energy accumulation. This method, which detects based on global energy, introduces excessive noise energy, reducing the algorithm's detection and high-resolution capabilities. Subband peak energy detection, on the other hand, extracts the local peak value from the azimuth spectrum of each subband and then accumulates the peak values ​​across different subbands of the same beam, significantly reducing the impact of noise energy. Theoretically, combining subband peak energy detection with adaptive methods can further improve detection and high-resolution performance.

[0003] However, while subband peak detection improves target azimuth resolution, it also increases false alarms in broadband detection. In particular, when the input signal-to-noise ratio of array elements is low or the beam sidelobes are high, a large number of false alarm targets are generated, which seriously affects the detection performance and restricts the engineering application of subband peak detection. Summary of the Invention:

[0004] The technical problem to be solved by this invention is to provide a method for eliminating sidelobe false targets based on subband peak energy detection. By introducing a sidelobe false target elimination method based on subband peak energy detection, false targets are suppressed, overcoming the high false alarm rate of traditional post-subband processing. When used in combination with adaptive processing, the high-resolution performance is improved by no less than 30% without reducing the detection performance, which has engineering application value.

[0005] The technical solution of this invention is to provide a method for eliminating sidelobe false targets in subband peak energy detection. This method is mainly applied to broadband beamforming. First, multiple sets of array data with clear target trajectories are selected from the experimental data accumulated by the sonar platform. Subband warning beam integration processing, subband peak energy (SPED), and subband peak number (SPED CS) processing are performed on the multi-array data. Second, the subband peak number spectrum is subjected to "expansion erosion" processing, which includes two processing actions: expansion and erosion. The results of "expansion erosion" are used for correction processing of subband peak energy (SPED) and subband peak number (SPED CS). Third, main and sidelobe beam screening is performed on the corrected subband peak energy (SPED). After the azimuth of the main and sidelobe beams are screened out, the main and sidelobe amplitude ratio of the corrected subband peak energy spectrum (SPED) and subband peak number spectrum (SPED CS) is calculated. The amplitude ratio of the main lobe and the sidelobe is quantified and statistically processed to obtain the probability distribution function of the amplitude ratio of the main lobe and the sidelobe. Then, the probability distribution function of the amplitude ratio of the main lobe and the sidelobe is analyzed to give the amplitude ratio of the main lobe and the sidelobe, the amplitude ratio threshold of the number of sub-band peaks, and the amplitude interval threshold of the main lobe and the sidelobe. Finally, the amplitude ratio thresholds of the main lobe and the sidelobe, the amplitude ratio threshold of the number of sub-band peaks, and the amplitude interval threshold of the main lobe are confirmed, and the sidelobe false targets are eliminated by using multi-threshold decision.

[0006] This invention includes processing of subband peak energy SPED and subband peak number SPED CS, SPED CS "expansion corrosion" and SPED and SPED CS correction, main and sidelobe beam filtering and calculation of the probability distribution function of main and sidelobe amplitude ratio, calculation of sidelobe false target threshold, and removal of suspected sidelobe false targets.

[0007] 1. Subband peak energy SPED and number of subband peaks SPED CS processing:

[0008] 101: Sub-band warning beam integration processing; From the experimental data accumulated by the sonar platform, multiple sets of array data with clear target trajectories are selected, and sub-band warning beam integration processing is performed on the multi-array data to obtain the warning beam data P at each frequency point of the current beat. n '(f k ,θ i (n is the time sequence, f) k θ is the k-th frequency point within the operating frequency band. i For the azimuth of the i-th beam, n = 0, ..., N-1, k = 0, ..., K-1, i = 0, ..., I-1. It is generally recommended that N be no less than 20000, K no less than 50, and θ... i (Not greater than 0.2 times the -3dB beamwidth);

[0009] 102: Subband Peak Energy SPED Processing; Subband peak energy is detected at each frequency point, retaining only the maximum value (peak point), and setting all other values ​​to 0. The subband energy spectrum P is obtained after peak detection. n (f k ,θ i ),Right now:

[0010]

[0011] For P on the same beam n (f k ,θ i The subband peak energy spectrum Po was obtained by cumulative synthesis. n (θ i ):

[0012]

[0013] 103: Subband Peak Count SPED CS Processing; Perform subband peak detection at each frequency point, setting the maximum value to 1 and the rest to 0. The subband peak detection result PT can be obtained after peak detection. n (f k ,θ i ),Right now:

[0014]

[0015] For PT on the same beam n (f k ,θ i The subband peak count spectrum Pco was obtained by cumulative synthesis. n (θ i ):

[0016]

[0017] 2. SPED CS "Expansion Corrosion" and SPED and SPED CS Correction:

[0018] 201: SPED CS “expansion” treatment; Pco of subband peak count spectrum n (θ i Perform "dilation processing" on the window length |θ M-1 -θ0| It is recommended to take the center frequency -3dB and the beamwidth θ -3dB 0.5 times, yielding the "expansion" result PZco n (θ i ):

[0019]

[0020] 202: "Erosion" treatment; for expansion result data PZcon (θ i The etching process was performed, resulting in the "etched" result C. n (θ i ):

[0021]

[0022] This eliminates the "peak bifurcation" of the sub-band peak count curve caused by target azimuth disturbance, resulting in a smooth and continuous sub-band peak count curve.

[0023] 203: SPED and SPED CS corrections; C on SPED CS "expansion corrosion" results n (θ i Perform a boolean decision to obtain the SPEDCS gate W. n (θ i ):

[0024]

[0025] And in W n (θ i Under constraints, the modified subband peak energy spectrum Po n (θ i ): In W n (θ i Find Po within the range of 1. n (θ i The maximum point of the peak energy spectrum Po' is determined by the following method: when multiple maxima occur, the energy of the five beams to the left and right of the azimuth corresponding to the maximum maximum is retained, and the energy of the remaining beams is set to 0. n (θ i This eliminates the "peak bifurcation" phenomenon in the subband peak energy. Similarly, using the SPED CS gate W... n (θ i The corrected number of peak values ​​Pco' is obtained. n (θ i ).

[0026] 3. Main and side lobe beam filtering and calculation of the probability distribution function of the main and side lobe amplitude ratio:

[0027] 301: Main lobe and suspected side lobe beam filtering; analysis of the corrected peak energy spectrum Po' n (θ i Perform a maximum search, sort in descending order to select the top 5 maxima with energy values ​​greater than 20, and simultaneously select the target beam with the highest energy among neighboring beams as the target main lobe, whose 5θ... -3dB Within the angular range, the two beams closest to the main lobe on the left and right are considered as suspected side lobes, and the peak energy of the main lobe subband is Po'. n (θ j,0The peak energy of the suspected sidelobe subband is Po'. n (θ j,q )(j=0,1,…,4; |q|≤2), θ j,0 Main lobe orientation, θ j,q (q<0) indicates the suspected left side lobe orientation, θ j,q (q>0) represents the suspected right side lobe orientation. Let Po' be the position of n=0,…,N-1. n (θ i The amplitude ratio of the suspected side lobe to the main lobe (PR) n (θ j,q ):

[0028] PR n (θ j,q )=Po' n (θ j,q ) / Po' n (θ j,0 (j=0,1,…,4;q≠0;PR) n (θ j,q )≤1)

[0029] Pco' n (θ i The amplitude ratio of the suspected side lobes to the main lobe in PCR n (θ j,q ):

[0030] PCR n (θ j,q )=Pco' n (θ j,q ) / Pco' n (θ j,0 (j=0,1,…,4;q≠0;PCR) n (θ j,q )≤1)

[0031] 302: Calculation of the probability distribution function of the main lobe and side lobe amplitude ratio; for each of the selected groups with a main lobe and side lobe amplitude ratio PR not exceeding 20N... n (θ j,q ) and PCR n (θ j,q The set of components is uniformly quantized, with a minimum quantization unit of 0.01. The estimated probability distribution functions of the main lobe amplitude ratio after quantization are as follows:

[0032]

[0033] The probability distribution function curve of the main lobe amplitude ratio rises sharply as a→100, then flattens out, and finally approaches 1.

[0034] 4. Calculation of sidelobe false target threshold:

[0035] 401: Calculation of subband peak energy, main-sidelobe amplitude ratio, and number of subband peaks, and the main-sidelobe amplitude ratio threshold; from... curves and Selecting an appropriate threshold γ in the flat region of the curve PR and γ PCR It is recommended to select the threshold from the interval where the curve rises steeply and just transitions to the flat area. If the threshold is too large, it will weaken the detection performance of the sub-band peak energy detection, and if it is too small, it will weaken the false alarm reduction effect of the sub-band peak energy detection.

[0036] 402: Calculation of the main and side lobe angular spacing threshold; The threshold range [θ] of the main and side lobe angular spacing is given by combining the array configuration and operating frequency. L ,θ R ], generally recommended θ L ≥θ -3dB ,θ R ≤4θ -3dB .

[0037] 5. Removal of suspected spurious targets from side lobes:

[0038] 501: Decision threshold shift; confirming the subband peak energy main-sidelobe amplitude ratio threshold γ PR Number of subband peaks, main lobe amplitude ratio, threshold γ PCR and the main lobe angle interval threshold [θ] L ,θ R After that, set the threshold value γ PR γ PCR 、[θ L ,θ R [Subband peak detection threshold decision used for other test data of the same array]

[0039] 502: Perform suspected sidelobe false target removal on other experimental data of the same array; perform sub-band warning beam integration, sub-band peak energy SPED processing, sub-band peak number SPED CS processing, SPED CS "expansion erosion" correction, and SPED and SPED CS correction on the experimental data respectively, using the same methods as steps 1 and 2, and perform correction on the corrected peak energy spectrum Po' n (θ i Perform a maximum search, when the wave crest and its adjacent crest satisfy the angular interval threshold [θ] L ,θ R Furthermore, the peak energy of the subband and the amplitude of the main and side lobes are greater than those of the PR band. n (θ j,q )≤γ PR The number of subband peaks and the amplitude of the main and side lobes compared to PCR n (θ j,q )≤γ PCR At that time, the suspected side lobe orientation θ was set.j,q The corresponding peak is 0, thus achieving the removal of false targets from the side lobes.

[0040] Compared with the prior art, the present invention has the following advantages:

[0041] This invention proposes a method to improve the detection performance of post-beamforming subband processing. It fully utilizes the spatial consistency difference between the target and sidelobes in subband processing. Based on subband peak detection, it eliminates the "bifurcation" of subband peaks caused by target azimuth disturbances through image "dilation and erosion". It also provides a threshold for the main-sidelobe amplitude ratio based on the distribution function and achieves sidelobe false target removal by combining multi-threshold decision. This overcomes the high false alarm rate of traditional post-subband processing. When used in conjunction with adaptive processing, it improves high-resolution performance by no less than 30% without reducing detection performance, and has engineering application value. Attached image description:

[0042] Figure 1 This is the algorithm principle of the present invention;

[0043] Figure 2 is the probability distribution function of subband peak energy, number of subband peaks, and main lobe amplitude ratio;

[0044] Figure 3 For single-beat band peak energy spectrum Po n (θ i Processing results;

[0045] Figure 4 Pco is the number of peaks in a single beat band. n (θ i Processing results;

[0046] Figure 5 Performance comparison before and after sidelobe false target removal for subband processing. Detailed implementation method:

[0047] The present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0048] A method for eliminating sidelobe false targets using subband peak energy detection, such as... Figure 1 , 2 As shown, the method includes the following steps:

[0049] Step 1: Select multiple sets of array data with clear target trajectories from the experimental data accumulated by the sonar platform, and perform sub-band warning beam integration processing, sub-band peak energy SPED and sub-band peak number SPED CS processing on the multi-array data;

[0050] Step 2: Perform "expansion erosion" processing on the subband peak count spectrum. The results of "expansion erosion" are used for subband peak energy SPED and subband peak count SPED CS correction processing.

[0051] Step 3: Perform main and side lobe beam filtering on the corrected sub-band peak energy SPED. After filtering out the main and side lobe beam orientations, calculate the main and side lobe amplitude ratio of the corrected sub-band peak energy spectrum SPED and the sub-band peak number spectrum SPED CS. Quantize and statistically process the main and side lobe amplitude ratio to obtain the probability distribution function of the main and side lobe amplitude ratio.

[0052] Step 4: Analyze the probability distribution function of the main lobe and side lobe amplitude ratio in the statistical results, and give the main lobe and side lobe amplitude ratio of the peak energy of the side lobe false target subband, the threshold of the main lobe and side lobe amplitude ratio of the number of subband peaks, and the threshold of the main lobe and side lobe angle interval.

[0053] Step 5: Confirm the subband peak energy main-sidelobe amplitude ratio threshold, the subband peak number main-sidelobe amplitude ratio threshold, and the main-sidelobe angle interval threshold. Use multi-threshold decision to eliminate sidelobe false targets.

[0054] In step 1 of the implementation method, taking a circular array as an example, it is assumed that the warning beam processing frequency band is 2.4kHz to 6.4kHz, the sampling rate is 40kHz, the beamforming single-beat has 1024 points (1024-point FFT), K = 103, 720 omnidirectional beams uniformly cover 0 to 360°, the beam spacing is 0.5°, I = 720, and the array data with clear target trajectories is extracted for 15 minutes, N = 35156. The specific operations after obtaining the array data are as follows:

[0055] Step 101: Sub-band warning beam integration processing

[0056] The captured 15-minute array data is processed by sub-band warning beam integration to obtain the warning beam data P at each frequency point of the current beat. n '(f k ,θ i (n is the time sequence, f) k θ is the k-th frequency point within the operating frequency band. i For the azimuth of the i-th beam, Δθ i =0.5°, n=0,…,35155, k=0,…,102, i=0,…,719);

[0057] Step 102: Subband Peak Energy SPED Processing

[0058] Subband peak energy detection is performed at each frequency point, retaining only the peak point with the maximum value, and setting all values ​​outside the peak point to 0. After peak detection, the subband energy spectrum P can be obtained. n (f k ,θ i ),Right now:

[0059]

[0060] For P on the same beam n (f k ,θ i The subband peak energy spectrum Po was obtained by cumulative synthesis. n (θ i ):

[0061]

[0062] Single-cycle peak energy spectrum Po n (θ i The processing result is as follows: Figure 3 As shown.

[0063] Step 103: Subband Peak Count SPED CS Processing

[0064] Subband peak detection is performed at each frequency point, with the maximum value set to 1 and the rest set to 0. The subband peak detection result PT can be obtained after peak detection. n (f k ,θ i ),Right now:

[0065]

[0066] For PT on the same beam n (f k ,θ i The subband peak count spectrum Pco was obtained by cumulative synthesis. n (θ i ):

[0067]

[0068] Single-beat band peak count spectrum Pco n (θ i The processing result is as follows: Figure 4 As shown.

[0069] The specific steps for step 2 are as follows:

[0070] Step 201: SPED CS "Inflation" Processing

[0071] Pair band peak count spectrum Pco n (θ i Perform "dilation processing" on the window length |θ M-1 -θ0| It is recommended to take the center frequency -3dB and the beamwidth θ -3dB 0.5 times, yielding the "expansion" result PZco n (θ i):

[0072]

[0073] Step 202: "Etching" treatment

[0074] For the expansion result data PZco n (θ i The etching process was performed, resulting in the "etched" result C. n (θ i ):

[0075]

[0076] This eliminates the "peak bifurcation" of the sub-band peak count curve caused by target azimuth disturbance, resulting in a smooth and continuous sub-band peak count curve.

[0077] Step 203: SPED and SPED CS Correction

[0078] Results of SPED CS "expansion corrosion" C n (θ i Perform a boolean decision to obtain SPED CS gateW n (θ i ):

[0079]

[0080] And in W n (θ i Under constraints, the modified subband peak energy spectrum Po n (θ i ): In W n (θ i Find Po within the range of 1. n (θ i The maximum point of the peak energy spectrum Po' is determined by the following method: when multiple maxima occur, the energy of the five beams to the left and right of the azimuth corresponding to the maximum maximum is retained, and the energy of the remaining beams is set to 0. n (θ i This eliminates the "peak bifurcation" phenomenon in the subband peak energy. Similarly, using the SPED CS gate W... n (θ i Obtain the corrected peak count spectrum Pco' n (θ i ).

[0081] The specific operation of step 3 in the implementation method is as follows:

[0082] Step 301: Beam filtering of main lobe and suspected side lobe

[0083] The corrected peak energy spectrum Po'n (θ i Perform a maximum search, sort in descending order to select the top 5 maxima with energy values ​​greater than 20, and simultaneously select the target beam with the highest energy among neighboring beams as the target main lobe, whose 5θ... -3dB Within the angular range, the two beams closest to the main lobe on the left and right are considered as suspected side lobes, and the peak energy of the main lobe subband is Po'. n (θ j,0 The peak energy of the suspected sidelobe subband is Po'. n (θ j,q )(j=0,1,…,4; |q|≤2), θ j,0 Main lobe orientation, θ j,q (q<0) indicates a possible left side lobe orientation, θ j,q (q>0) represents the suspected right side lobe orientation. Let Po' be the position of n=0,…,N-1. n (θ i The amplitude ratio of the suspected side lobe to the main lobe (PR) n (θ j,q ):

[0084] PR n (θ j,q )=Po' n (θ j,q ) / Po' n (θ j,0 (j=0,1,…,4;q≠0;PR) n (θ j,q )≤1)

[0085] Pco' n (θ i The amplitude ratio of the suspected side lobes to the main lobe in PCR n (θ j,q ):

[0086] PCR n (θ j,q )=Pco' n (θ j,q ) / Pco' n (θ j,0 (j=0,1,…,4;q≠0;PCR) n (θ j,q )≤1)

[0087] Step 302: Calculation of the probability distribution function of the main lobe-side lobe amplitude ratio

[0088] The main lobe and side lobe amplitude ratios (PR) of the selected groups not exceeding 20N were respectively... n (θ j,q ) and PCR n (θ j,qThe set of components is uniformly quantized, with a minimum quantization unit of 0.01. The estimated probability distribution functions of the main lobe amplitude ratio after quantization are as follows:

[0089]

[0090] The estimation results of the probability distribution function of the main lobe amplitude ratio obtained from the actual sea trial data processing are as follows: Figure 5 As shown, when 0.01*a≤0.8 The curve rises sharply when 0.8 < 0.01*a ≤ 1. The surface is relatively flat; when 0.01*a≤0.9 The curve rises sharply when 0.9 < 0.01*a ≤ 1. Relatively flat.

[0091] The specific operation of step 4 in the implementation method is as follows:

[0092] Step 401: Calculation of subband peak energy, main-sidelobe amplitude ratio, number of subband peaks, and main-sidelobe amplitude ratio threshold for sidelobe spurious targets.

[0093] from curves and Threshold values ​​are selected in the flat region of the curve, here. Threshold γ PR =0.8, Threshold γ PCR =0.9;

[0094] Step 402: Calculation of the main lobe and side lobe angle interval threshold

[0095] The threshold [θ] for the main lobe angular spacing range is given by combining the array configuration and operating frequency. L ,θ R ](θ L =3.5°, θ R =14°).

[0096] The specific steps of implementation step 5 are as follows:

[0097] Step 501: Decision Threshold Shift

[0098] Confirm subband peak energy main lobe amplitude ratio threshold γ PR Number of subband peaks, main lobe amplitude ratio, threshold γ PCR and the main lobe angle interval threshold [θ] L ,θ R After that, set the threshold value γ PR γ PCR 、[θ L ,θ R [Subband peak detection threshold decision used for other test data of the same array]

[0099] Step 502: Perform suspected sidelobe false target removal on other experimental data of the same array.

[0100] Select a segment of experimental data, such as Figure 5 As shown, the sub-band warning beam integration, sub-band peak energy SPED processing, sub-band peak number SPED CS processing, SPED CS "expansion erosion" and SPED and SPED CS corrections are completed, using the same methods as steps 1 and 2, and the corrected peak energy spectrum Po' is then processed. n (θ i Perform a maximum search, when the wave crest and its adjacent crest satisfy the angular interval threshold [θ] L ,θ R Furthermore, the peak energy of the subband and the amplitude of the main and side lobes are greater than those of the PR band. n (θ j,q )≤γ PR The number of subband peaks and the amplitude of the main and side lobes compared to PCR n (θ j,q )≤γ PCR At that time, the suspected side lobe orientation θ was set. j,q The corresponding peak value is 0, achieving sidelobe false target removal. A comparison of detection performance before and after sidelobe false target removal is shown below. Figure 5 As shown.

[0101] This invention discloses a method for improving the detection performance of post-beamforming subband processing, relating to the field of underwater acoustic array signal processing. It fully utilizes the spatial consistency differences between the target and sidelobes in subband processing. Based on subband peak detection, it eliminates the "bifurcation" of subband peaks caused by target azimuth disturbances through image "dilation and erosion." Furthermore, it provides a threshold for the main-sidelobe amplitude ratio based on the distribution function, and combines multi-threshold decision-making to achieve sidelobe false target removal. This overcomes the high false alarm rate of traditional post-subband processing. When used in conjunction with adaptive processing, it improves high-resolution performance by at least 30% without reducing detection performance, demonstrating high engineering application value.

[0102] The above description only illustrates preferred embodiments of the present invention and should not be construed as limiting the scope of the claims. Any equivalent procedural modifications made using this specification are included within the patent protection scope of this invention.

Claims

1. A method for eliminating sidelobe false targets using subband peak energy detection, characterized in that: The method includes, Step 1: Select multiple sets of array data with clear target trajectories from the experimental data accumulated by the sonar platform, and perform sub-band warning beam integration processing, sub-band peak energy SPED and sub-band peak number SPED CS processing on the multi-array data; Step 2: Perform dilatation and etching on the subband peak count spectrum. The dilatation and etching results are used for subband peak energy SPED and subband peak count SPED CS correction processing. Step 3: Perform main and side lobe beam filtering on the modified subband peak energy SPED. After filtering out the main and side lobe beam orientations, calculate the main and side lobe amplitude ratio of the modified subband peak energy spectrum SPED and the subband peak number spectrum SPED CS. Then, quantize and statistically process the main and side lobe amplitude ratio to obtain the probability distribution function of the main and side lobe amplitude ratio. Step 4: Analyze the statistical results and the probability distribution function of the main lobe-side lobe amplitude ratio, and give the main lobe-side lobe amplitude ratio of the peak energy of the side lobe false target subband, the threshold of the main lobe-side lobe amplitude ratio of the number of subband peaks, and the threshold of the main lobe-side lobe angle interval. Step 5: Confirm the subband peak energy main-sidelobe amplitude ratio threshold, the subband peak number main-sidelobe amplitude ratio threshold, and the main-sidelobe angle interval threshold. Use multi-threshold decision to eliminate sidelobe false targets.

2. The method for eliminating sidelobe false targets in subband peak energy detection according to claim 1, characterized in that: Step 1 is performed as follows: Sub-band warning beam integration processing: From the accumulated experimental data of the sonar platform, multiple sets of array data with clear target trajectories are selected, and sub-band warning beam integration processing is performed on the multi-array data to obtain the warning beam data P at each frequency point of the current beat. n '(f k ,θ i ), where n is the time series, f k θ is the k-th frequency point within the operating frequency band. i For the azimuth of the i-th beam, n = 0, ..., N-1, k = 0, ..., K-1, i = 0, ..., I-1, N is not less than 20000, K is not less than 50, θ i Not greater than 0.2 times the -3dB beamwidth; Subband peak energy SPED processing: Subband peak energy detection is performed at each frequency point, retaining only the peak point with the maximum value, and setting all values ​​outside the peak point to 0. The subband energy spectrum P is obtained after peak detection. n (f k ,θ i ),Right now: For P on the same beam n (f k ,θ i The subband peak energy spectrum Po was obtained by cumulative synthesis. n (θ i ): Subband peak count SPED CS processing; subband peak detection is performed at each frequency point, with the maximum value set to 1 and the rest set to 0. The subband peak detection result PT is obtained after peak detection. n (f k ,θ i ),Right now: For PT on the same beam n (f k ,θ i The subband peak count spectrum Pco was obtained by cumulative synthesis. n (θ i ):

3. The method for eliminating sidelobe false targets in subband peak energy detection according to claim 2, characterized in that: Step 2 is performed as follows: SPED CS expansion processing; Pco of subband peak count spectrum n (θ i Perform dilation processing, processing window length |θ M-1 -θ0|Center frequency -3dB beamwidth θ -3dB The expansion result PZco is obtained by multiplying it by 0.5 times. n (θ i ): Corrosion treatment; For the expansion result data PZco n (θ i The corrosion treatment was performed, and the corrosion result C was obtained. n (θ i ): This eliminates the peak bifurcation of the sub-band peak count curve caused by target azimuth disturbance, resulting in a smooth and continuous sub-band peak count curve. SPED and SPED CS corrections; SPED CS expansion corrosion results C n (θ i Perform a boolean decision to obtain SPED CS gateW n (θ i ): And in W n (θ i Under constraints, the modified subband peak energy spectrum Po n (θ i ): In W n (θ i Find Po within the range of 1. n (θ i The maximum point of the peak energy spectrum Po' is determined by the following method: when multiple maxima occur, the energy of the five beams to the left and right of the azimuth corresponding to the maximum maximum is retained, and the energy of the remaining beams is set to 0. n (θ i This eliminates peak bifurcation in the subband peak energy and utilizes SPED CS gate W n (θ i The corrected number of peak values ​​Pco' is obtained. n (θ i ).

4. The method for eliminating sidelobe false targets in subband peak energy detection according to claim 3, characterized in that: Step 3 is performed as follows: Beam filtering of main lobe and suspected side lobe; analysis of the corrected peak energy spectrum Po' n (θ i Perform a maximum search, sort in descending order to select the top 5 maxima with energy values ​​greater than 20, and simultaneously select the target beam with the highest energy among neighboring beams as the target main lobe, whose 5θ... -3dB Within the angular range, the two beams closest to the main lobe on the left and right are considered as suspected side lobes, and the peak energy of the main lobe subband is Po'. n (θ j,0 The peak energy of the suspected sidelobe subband is Po'. n (θ j,q )(j=0,1,…,4; |q|≤2), θ j,0 Main lobe orientation, θ j,q (q<0) indicates a possible left side lobe orientation, θ j,q (q>0) represents the suspected right side lobe orientation; let Po' be the position when n=0,…,N-1. n (θ i The amplitude ratio of the suspected side lobe to the main lobe (PR) n (θ j,q ): PR n (θ j,q )=Po' n (θ j,q ) / Po' n (θ j,0 )(j=0,1,…,4;q≠0;PR n (θ j,q )≤1) Pco' n (θ i The amplitude ratio of the suspected side lobes to the main lobe in PCR n (θ j,q ): PCR n (θ j,q )=Pco' n (θ j,q ) / Pco' n (θ j,0 )(j=0,1,…,4;q≠0;PCR n (θ j,q )≤1) Calculate the probability distribution function of the main lobe-side lobe amplitude ratio; for each of the selected groups with a main lobe-side lobe amplitude ratio PR not exceeding 20N... n (θ j,q ) and PCR n (θ j,q The set of components is uniformly quantized, with a minimum quantization unit of 0.

01. The estimated probability distribution functions of the main lobe amplitude ratio after quantization are as follows: Among them, the probability distribution function curve of the main lobe amplitude ratio rises sharply as a→100, then flattens out, and finally approaches 1.

5. The method for eliminating sidelobe false targets in subband peak energy detection according to claim 4, characterized in that: The specific steps for step 4 are as follows: Calculation of subband peak energy, main-sidelobe amplitude ratio, and number of subband peaks, and main-sidelobe amplitude ratio threshold; from... curves and Selecting an appropriate threshold γ in the flat region of the curve PR and γ PCR ; Calculation of main and side lobe angular spacing threshold; The threshold range [θ] of the main and side lobe angular spacing is given by combining the array configuration and operating frequency. L ,θ R ], θ L ≥θ -3dB ,θ R ≤4θ -3dB .

6. The method for eliminating sidelobe false targets in subband peak energy detection according to claim 5, characterized in that: The specific steps for step 5 are as follows: Decision threshold shift; confirmation of subband peak energy main-sidelobe amplitude ratio threshold γ PR Number of subband peaks, main lobe amplitude ratio, threshold γ PCR and the main lobe angle interval threshold [θ] L ,θ R After that, set the threshold value γ PR γ PCR 、[θ L ,θ R Subband peak detection threshold decision used for other test data of the same array; Suspected sidelobe false targets were removed from other experimental data of the same array; the experimental data were subjected to sub-band warning beam integration, sub-band peak energy SPED processing, sub-band peak number SPED CS processing, SPED CS expansion and erosion, and SPED and SPEDCS correction, and the corrected peak energy spectrum Po' was also processed. n (θ i Perform a maximum search, when the wave crest and its adjacent crest satisfy the angular interval threshold [θ] L ,θ R Furthermore, the peak energy of the subband and the amplitude of the main and side lobes are greater than those of the PR band. n (θ j,q )≤γ PR The number of subband peaks and the amplitude of the main and side lobes compared to PCR n (θ j,q )≤γ PCR At that time, the suspected side lobe orientation θ was set. j,q The corresponding peak is 0, thus achieving the removal of false targets from the side lobes.

7. The method for eliminating sidelobe false targets in subband peak energy detection according to claim 5, characterized in that: When calculating the peak energy of the sidelobe pseudo-target subband and the main-sidelobe amplitude ratio and the threshold of the number of subband peaks in step 4, the threshold is selected from the interval where the curve rises steeply and just transitions to the flat region.

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