阅读说明：本技术 一种用于弱目标检测的宽波束干扰抑制方法 (Wide beam interference suppression method for weak target detection ) 是由 李学敏 黄海宁 李宇 叶青华 于 2019-03-11 设计创作，主要内容包括：本发明提出一种用于弱目标检测的宽波束干扰抑制方法,包括：步骤1)空间线阵接收远距离目标的宽带信号,对线阵各阵元接收的信号在时域作快速傅里叶变换,生成线阵各阵元信号的时域频谱；将空间线阵划分为若干个重叠子阵；对重叠子阵的信号时域频谱作相位补偿,形成波束域输出,得到子阵方位谱图；步骤2)利用子阵方位谱图,确定干扰方位,对波束域输出进行干扰抑制加权,利用期望的零陷宽度对干扰抑制加权进行修正得到零陷加权,控制波束域输出的干扰抑制宽度,得到干扰抑制后的方位谱图,实现强干扰背景下强干扰的抑制和弱目标的检测。本发明有效抑制较宽波束的强干扰信号,提高弱目标的检测性能,提升输出信干比；海试数据证明有效。(The invention provides a wide beam interference suppression method for weak target detection, which comprises the following steps: step 1) receiving a broadband signal of a remote target by a spatial linear array, and performing fast Fourier transform on the signal received by each array element of the linear array in a time domain to generate a time domain frequency spectrum of each array element signal of the linear array; dividing the space linear array into a plurality of overlapped sub-arrays; performing phase compensation on the signal time domain frequency spectrum of the overlapped subarrays to form beam domain output to obtain a subarray azimuth spectrogram; and 2) determining an interference azimuth by using the sub-array azimuth spectrogram, performing interference suppression weighting on the beam domain output, correcting the interference suppression weighting by using the expected null width to obtain the null weighting, controlling the interference suppression width of the beam domain output to obtain the azimuth spectrogram after the interference suppression, and realizing the suppression of strong interference and the detection of a weak target under a strong interference background. The invention effectively inhibits the strong interference signal of a wider wave beam, improves the detection performance of a weak target and improves the output signal-to-interference ratio; the sea test data proved to be valid.)

1. A method of wide beam interference suppression for weak target detection, comprising:

step 1) receiving a broadband signal of a remote target by a spatial linear array, and performing fast Fourier transform on the signal received by each array element of the linear array in a time domain to generate a time domain frequency spectrum of each array element signal of the linear array; dividing the space linear array into a plurality of overlapped sub-arrays; performing phase compensation on the signal time domain frequency spectrum of the overlapped subarrays, and forming a beam domain for output to obtain a subarray azimuth spectrogram;

and 2) determining an interference azimuth by using a sub-array azimuth spectrogram, performing interference suppression weighting on the output of the beam domain, correcting the interference suppression weighting by using an expected null width to obtain a null weighting, controlling the interference suppression width output by the beam domain through the null weighting vector to obtain the azimuth spectrogram after interference suppression, and realizing suppression of strong interference and detection of a weak target under a strong interference background.

2. The method for suppressing wide-beam interference for weak target detection according to claim 1, wherein the step 1) specifically comprises:

step 1-1) receiving a broadband signal of a remote target by a spatial linear array to obtain M array element signals x [ d ]_m,t]M is array element number, M is 1,2_mMd is the position of the mth array element, and d is the array element interval; dividing the signal into N snapshots in time domain, and recording as snapshots 1,2, …, N, …, N, each snapshot x_n[d_m,t]And (3) performing fast Fourier transform on the nth snapshot signal in a time domain with the length of L to obtain a time domain frequency spectrum X (m, f) of the nth snapshot signal of the mth array element:

wherein t is time, f is frequency, L is the number of sampling points, and the value is a natural number; if the signal sampling rate is F_sThen, the number of sampling points L is:

mu is the resolution of the frequency domain,represents the smallest integer no less than;

step 1-2) dividing the space linear array into y +1 overlapped sub-arrays according to the number y of the interference needing to be suppressed; setting the ith and (i + 1) th sub-arrays of two adjacent overlapped sub-arrays; the difference of the serial numbers of the first array elements of the ith and the (i + 1) th sub-arrays is D; the serial numbers of the first array elements of the two adjacent overlapping subarrays are m respectively_i(i-1) D and m_i+1The number of each subarray element is M-yD, and the time domain spectrums of the two adjacent overlapping subarray signals are respectively marked as X⁽ⁱ⁾(f) And X⁽ⁱ⁺¹⁾(f)：

X⁽ⁱ⁾(f)＝[X(m_i+1,f),X(m_i+2,f),…,X(m_i+M-yD,f)]^T(3)

X⁽ⁱ⁺¹⁾(f)＝[X(m_i+1+1,f),X(m_i+1+2,f),…,X(m_i+1+M-yD,f)]^T(4)

Wherein i is 1,2,. y; y ═ 1, T denotes the transposition operation;

step 1-3) determining the frequency band range [ f ] of the frequency spectrum X (m, f) of the mth array element_min,f_max]，f_minIs a minimum value of frequency, f_maxFor the frequency maximum value, respectively carrying out phase compensation on each frequency component in the frequency band range, respectively synthesizing the data after the phase compensation into the two adjacent overlapped subarray wave beams and outputting BF_l ⁽ⁱ⁾(theta) and BF_l ⁽ⁱ⁺¹⁾(θ)；

BF_l ⁽ⁱ⁾(θ)＝w^(i)H(θ)·X⁽ⁱ⁾(m,f) (5)

BF_l ⁽ⁱ⁺¹⁾(θ)＝w^(i+1)H(θ)·X⁽ⁱ⁺¹⁾(m,f) (6)

The method comprises the following steps that theta is a scanning azimuth angle and takes a value of 0-180 degrees, superscript H represents complex conjugate transpose operation, l is the first interference needing to be suppressed, and l is 1, 2. The weighting vectors of the two adjacent overlapping sub-arrays are respectively w⁽ⁱ⁾(theta) and w⁽ⁱ⁺¹⁾(θ)：

c is the speed of sound propagation in the ocean.

3. The wide-beam interference suppression method for weak target detection according to claim 2, wherein in the step 1-3), θ ═ θ_mThe directional interference, the beam output relationship of the two adjacent overlapping subarrays is:

outputting BF according to the wave beams of the two adjacent overlapped sub-arrays_l ⁽ⁱ⁾(theta) and BF_l ⁽ⁱ⁺¹⁾And (theta) obtaining an azimuth spectrogram of two adjacent overlapping sub-arrays.

4. The method for suppressing wide-beam interference for weak target detection according to claim 3, wherein the step 2) specifically comprises:

step 2-1) outputting BF according to the wave beams of the two adjacent overlapped sub-arrays_l ⁽ⁱ⁾(theta) and BF_l ⁽ⁱ⁺¹⁾Determining an interference direction by an overlapping subarray direction spectrogram formed by (theta), wherein a peak value formed by strong interference is far larger than a signal peak value, and taking the direction with the maximum peak value in the direction spectrogram as the interference direction theta_m；

Step 2-2) based on the interference orientation theta_mCalculating and correcting an interference suppression weighted vector to obtain a corrected interference suppression weighted vector w'_IS(θ|θ_m)：

w′_IS(θ|θ_m)＝weight_null(θ)·w_IS(θ_m) (13)

Wherein, the sub-array level interference suppression weighting vector w_IS(θ_m)：

Null-steering weight vector weight_null(theta) the first array element number difference D and the interference direction theta of the ith and the (i + 1) th sub-arrays_mThe width of null desired to be suppressed, Δ, is determined as:

step 2-3) Using the corrected weight vector w'_IS(θ|θ_m) Carrying out interference suppression weighting on the beam outputs of the two adjacent overlapped subarrays to obtain a pair direction theta_mSuppressed ith beam output

Step 2-4) solving the beam output of all adjacent overlapping sub-arrays in sequence, and writing the beam output into a vector form:

judging whether other interference orientations needing to be suppressed exist or not, namely whether l < y is true or not, if the other interference orientations needing to be suppressed exist, judging that the result is 'yes', then l is l +1, and returning to the step 2-1) to continue execution;

if not, the interference direction which is expected to be suppressed is traversed, and the output of the wave beam is recorded as BF_y+1(θ), performing step 2-5);

step 2-5) outputting BF based on the beam_y+1And (theta) outputting a result to obtain an orientation spectrogram after interference suppression, so that suppression of strong interference and detection of a weak target under a strong interference background are realized.

5. The wide-beam interference suppression method for weak target detection according to claim 4, wherein the null width Δ in step 2-3) satisfies the following condition:

101g|2·sin(πfDd(cos(θ_m+Δ)-cosθ_m)/c)|≤U (14)

and U is a null depth threshold, and the null width delta is controlled by changing the null depth threshold U.

6. The method according to claim 4, wherein the difference D between the first array element numbers of the adjacent subarrays takes an intermediate value between the subarray gain G (M-yD) and the null width Δ, and the value of D is 1 or 2.

Technical Field

The invention belongs to the field of sonar digital signal processing, and particularly relates to a wide-beam interference suppression method for weak target detection.

Background

The detection of weak signals is one of the key technologies for array signal processing. The spectral peak of the weak target on the space spectrum under the background of strong interference can be covered by the side lobe of the interference spectrum, which greatly influences the detection of the weak signal and the estimation of the direction of arrival. Therefore, the interference should be suppressed effectively first.

Researchers at home and abroad have conducted extensive and intensive studies on the interference suppression problem, and many effective solutions are proposed, for example, document 1[ Robust generated large-scaled cell with an eigen-based blocking scheme ] international control on electrical engineering control,2017] and document 2[ a worst-case performance optimization feature analysis adaptive beamforming method. Among the interference suppression methods based on beam forming, there are null techniques (document 4[ a design method of a dimension-reduced spatial filter matrix, electronics, 2017]), array polarization techniques, and the like. The null technology aims at the main lobe direction of a wave beam to a target signal and forms null in the interference direction, thereby achieving the purposes of retaining the signal and inhibiting the interference. The interference suppression algorithm based on the signal separation technology achieves the purpose of suppression by separating signals from interference and eliminating the interference from array receiving data. The interference suppression algorithm in special cases mainly performs interference suppression on the aspects of coherent interference, co-channel interference and the like. Document 5[ Interference Suppression of robust Adaptive beamforming Presence of Sensor dispersion, ieee Transactions on Signal Processing,2010] proposes a Subarray strong Interference Suppression algorithm suitable for a triple linear array, which performs feature decomposition on a Subarray narrow-band Signal covariance matrix, removes a maximum feature value representing a strong Interference Signal to perform Interference Suppression, and obtains a certain effect; document 6[ a uniform circular array subarray interference suppression DOA estimation algorithm, signal processing,2010] utilizes a least square beam forming algorithm to form interference nulls for subarray beams of a uniform circular array, and then utilizes subarray output to perform super-resolution spectrum estimation, so that a good effect is achieved; document 7[ study of interference suppression algorithm for inverse beam forming with good wide-tolerance, study of electronics and information, 2015] constructs an interference reconstruction matrix, and output of a subarray in an interference azimuth replaces output of an array element domain interference azimuth, so that a certain suppression effect is obtained; the algorithm carries out interference suppression in an array element domain. In addition, in document 8[ multivariate array signal phase matching method, proceedings of northwest university of industry, 2002] a method for reducing random noise and improving interference cancellation performance by using a three-subarray is proposed based on a coherent interference phase matching principle, and it is pointed out that an algorithm has uncertainty on signal solution of a binary array. Document 9[ a robust beamforming algorithm under coherent interference, proceedings of harbin university of engineering, 2013] suppresses interference by using a forward and backward spatial smoothing technique and an MVDR algorithm, but the computation amount is large, and real-time processing is not facilitated. An anti-Beamforming (IBF) interference suppression algorithm (Towed shift-Noise suppression using interference, technical Acoustics,2007) is an interference suppression algorithm proposed by national scholars in recent years, which reconstructs an interference signal by making full use of azimuth knowledge of interference and then performs interference suppression by using the reconstructed interference signal. The algorithm is simple in structure and easy to implement in engineering, but in a complex marine environment, due to factors such as channel random disturbance and array distortion, the phase of an array receiving signal has certain random disturbance, the interference suppression effect of the algorithm is reduced, and further detection of a target signal is influenced; in addition, in order to suppress the wide-beam interference, the algorithm needs to perform peak searching suppression for multiple times near the interference azimuth, and the algorithm complexity is high.

In practical applications, an interference suppression real-time processing method with high robustness against wide-beam interference is needed.

Disclosure of Invention

The invention aims to overcome the defects that the existing interference suppression algorithm is low in calculation speed and low in feasibility, multiple peak seeking suppression is needed near a wide-beam interference azimuth in practical application, and meanwhile, the interference suppression effect is not ideal due to the fact that the algorithm is sensitive to phase random disturbance in a complex marine environment.

In order to achieve the above object, the present invention provides a wide-beam interference suppression method for weak target detection, which uses overlapping sub-arrays to estimate the interference signals of each sub-array, and weights the beam output results of the sub-arrays to achieve interference suppression. The effectiveness of the algorithm is verified by theoretical simulation and offshore test data processing.

The invention provides a wide beam interference suppression method for weak target detection, which comprises the following steps:

step 1) receiving a broadband signal of a remote target by a spatial linear array, and performing fast Fourier transform on the signal received by each array element of the linear array in a time domain to generate a time domain frequency spectrum of each array element signal of the linear array; dividing the space linear array into a plurality of overlapped sub-arrays; performing phase compensation on the signal time domain frequency spectrum of the overlapped subarrays, and forming a beam domain for output to obtain a subarray azimuth spectrogram;

and 2) determining an interference azimuth by using a sub-array azimuth spectrogram, performing interference suppression weighting on the output of the beam domain, correcting the interference suppression weighting by using an expected null width to obtain a null weighting, controlling the interference suppression width output by the beam domain through the null weighting vector to obtain the azimuth spectrogram after interference suppression, and realizing suppression of strong interference and detection of a weak target under a strong interference background.

As an improvement of the method, the step 1) specifically includes:

step 1-1) receiving a broadband signal of a remote target by a spatial linear array to obtain M array element signals x [ d ]_m,t]M is array element number, M is 1,2_mMd is the position of the mth array element, and d is the array element interval; dividing the signal into N snapshots in time domain, and recording as snapshots 1,2, …, N, …, N, each snapshot x_n[d_m,t]And (3) performing fast Fourier transform on the nth snapshot signal in a time domain with the length of L to obtain a time domain frequency spectrum X (m, f) of the nth snapshot signal of the mth array element:

wherein t is time, f is frequency, L is the number of sampling points, and the value is a natural number; if the signal sampling rate is F_sThen, the number of sampling points L is:

mu is the resolution of the frequency domain,represents the smallest integer no less than;

step 1-2) dividing the space linear array into y +1 overlapped sub-arrays according to the number y of the interference needing to be suppressed; setting the ith and (i + 1) th sub-arrays of two adjacent overlapped sub-arrays; the difference of the serial numbers of the first array elements of the ith and the (i + 1) th sub-arrays is D; the serial numbers of the first array elements of the two adjacent overlapping subarrays are m respectively_i(i-1) D and m_i+1The number of each subarray element is M-yD, and the time domain spectrums of the two adjacent overlapping subarray signals are respectively marked as X⁽ⁱ⁾(f) And X⁽ⁱ⁺¹⁾(f)：

X⁽ⁱ⁾(f)＝[X(m_i+1,f),X(m_i+2,f),…,X(m_i+M-yD,f)]^T(3)

X⁽ⁱ⁺¹⁾(f)＝[X(m_i+1+1,f),X(m_i+1+2,f),…,X(m_i+1+M-yD,f)]^T(4)

Wherein i is 1,2,. y; y ═ 1, T denotes the transposition operation;

step 1-3) determining the frequency band range [ f ] of the frequency spectrum X (m, f) of the mth array element_min,f_max]，f_minIs a minimum value of frequency, f_maxFor the frequency maximum value, respectively carrying out phase compensation on each frequency component in the frequency band range, respectively synthesizing the data after the phase compensation into the two adjacent overlapped subarray wave beams and outputting BF_l ⁽ⁱ⁾(theta) and BF_l ⁽ⁱ⁺¹⁾(θ)；

BF_l ⁽ⁱ⁾(θ)＝w^(i)H(θ)·X⁽ⁱ⁾(m,f) (5)

BF_l ⁽ⁱ⁺¹⁾(θ)＝w^(i+1)H(θ)·X⁽ⁱ⁺¹⁾(m,f) (6)

The method comprises the following steps that theta is a scanning azimuth angle and takes a value of 0-180 degrees, superscript H represents complex conjugate transpose operation, l is the first interference needing to be suppressed, and l is 1, 2. The weighting vectors of the two adjacent overlapping sub-arrays are respectively w⁽ⁱ⁾(theta) and w⁽ⁱ⁺¹⁾(θ)：

c is the speed of sound propagation in the ocean.

As a modification of the method, in step 1-3), θ ═ θ_mThe directional interference, the beam output relationship of the two adjacent overlapping subarrays is:

outputting BF according to the wave beams of the two adjacent overlapped sub-arrays_l ⁽ⁱ⁾(theta) and BF_l ⁽ⁱ⁺¹⁾And (theta) obtaining an azimuth spectrogram of two adjacent overlapping sub-arrays.

As an improvement of the method, the step 2) specifically includes:

step 2-1) outputting BF according to the wave beams of the two adjacent overlapped sub-arrays_l ⁽ⁱ⁾(theta) and BF_l ⁽ⁱ⁺¹⁾Determining an interference direction by an overlapping subarray direction spectrogram formed by (theta), wherein a peak value formed by strong interference is far larger than a signal peak value, and taking the direction with the maximum peak value in the direction spectrogram as the interference direction theta_m；

Step 2-2) based on the interference orientation theta_mCalculating and correcting an interference suppression weighted vector to obtain a corrected interference suppression weighted vector w'_IS(θ|θ_m)：

w′_IS(θ|θ_m)＝weight_null(θ)·w_IS(θ_m) (13)

Wherein, the sub-array level interference suppression weighting vector w_IS(θ_m)：

Null-steering weight vector weight_null(theta) the first array element number difference D and the interference direction theta of the ith and the (i + 1) th sub-arrays_mThe width of null desired to be suppressed, Δ, is determined as:

step 2-3) Using the corrected weight vector w'_IS(θ|θ_m) Carrying out interference suppression weighting on the beam outputs of the two adjacent overlapped subarrays to obtain a pair direction theta_mSuppressed ith beam output

Step 2-4) solving the beam output of all adjacent overlapping sub-arrays in sequence, and writing the beam output into a vector form:

judging whether other interference orientations needing to be suppressed exist or not, namely whether l < y is true or not, if the other interference orientations needing to be suppressed exist, judging that the result is 'yes', then l is l +1, and returning to the step 2-1) to continue execution;

if not, the interference direction which is expected to be suppressed is traversed, and the output of the wave beam is recorded as BF_y+1(θ), performing step 2-5);

step 2-5) outputting BF based on the beam_y+1Output of (theta)And as a result, an orientation spectrogram after interference suppression is obtained, so that strong interference suppression and weak target detection under a strong interference background are realized.

As a modification of the method, the width Δ of the null in step 2-3) satisfies:

10lg|2·sin(πfDd(cos(θ_m+Δ)-cosθ_m)/c)|≤U (14)

and U is a null depth threshold, and the null width delta is controlled by changing the null depth threshold U.

As a modification of the method, the difference D between the first array element numbers of adjacent subarrays takes an intermediate value between the subarray gain G of 10lg (M-yD) and the null width Δ, and the value of D is 1 or 2.

The invention has the advantages that:

1. the method for suppressing the wide-beam interference for detecting the weak target utilizes a plurality of overlapped sub-arrays to respectively estimate the beam output of each sub-array, realizes the interference suppression by the output weighting in the sub-array beam domain, and simultaneously adopts a reasonably designed null weighting vector to realize the wide-beam interference suppression with controllable width. The interference of a wider wave beam can be inhibited, the inhibition width can be controlled by a null weighting vector, and the inhibition capability of strong interference is more excellent;

2. compared with the conventional IBF interference suppression algorithm, the wide-beam interference suppression method for weak target detection has better tolerance to interference phase random disturbance, and is beneficial to further detection and estimation of target signals;

3. when the wide-beam interference suppression method for weak target detection is used for performing interference suppression on a wider beam, multiple peak searching interference suppression near an interference azimuth is not needed, the algorithm is less in time consumption, low in complexity and high in calculation efficiency;

4. the simulation data processing result shows that the wide-beam interference suppression method for weak target detection can effectively suppress strong interference signals of wider beams, improve the detection performance of weak targets and improve the output signal-to-interference ratio by about 15 dB;

5. sea test data prove that the wide-beam interference suppression method for weak target detection is effective.

Drawings

FIG. 1 is a schematic diagram of a linear array model for a wide-beam interference suppression method for weak target detection according to the present invention;

FIG. 2 is a schematic illustration of a conventional linear array towed by a ship in the prior art;

FIG. 3 is a flowchart of an algorithm of a wide beam interference suppression method for weak target detection according to the present invention;

FIG. 4 is a conditional wave number spectral density diagram and its expansion diagram along the wave number k direction adopted by the wide beam interference suppression method for weak target detection according to the present invention;

FIG. 5 is a purified spectrogram of the conditional wave number spectral density employed by the wide-beam interference suppression method for weak target detection of the present invention;

fig. 6 is a comparison of the output of the azimuth spectrum obtained by the method for suppressing the interference of the wide beam for weak target detection according to the present invention and by other algorithms.

Detailed Description

The invention is further described with reference to the following figures and specific examples.

The method for suppressing the wide-beam interference for detecting the weak target utilizes a plurality of overlapped sub-arrays to respectively estimate the beam output of each sub-array, realizes interference suppression by output weighting in a sub-array beam domain, and simultaneously adopts a reasonably designed null weighting vector to realize the wide-beam interference suppression with controllable width.

In order to achieve the purpose, the linear array sonar device adopted by the method can be a towed array or a broadside array, the linear array sonar consists of a plurality of hydrophones, the actual array element number N and the array element spacing D are set, the array is divided into 2 overlapped subarrays, the serial number difference D of the first array element of the subarrays is set, the number of each subarray element is N-D, the data received by the subarrays 1 and 2 are respectively represented as x⁽¹⁾(t)＝[x[0,t],x[d,t],…,x[(M-D-1)d,t]]^TAnd x⁽²⁾(t)＝[x[Dd,t],x[(D+1)d,t],…,x[(M-1)d,t]]^TAnd T denotes a transposition operation.

The invention provides a novel wide beam interference suppression method with good robustness for weak target detection, which comprises the following steps:

step 1) receiving a broadband signal of a remote target by a spatial linear array, and performing fast Fourier transform on received data of each array element of the linear array in a time domain to generate a frequency spectrum of a time domain signal of each array element of the linear array; dividing the space linear array into a plurality of overlapped sub-arrays; performing phase compensation on the overlapped subarray frequency spectrum, synthesizing a beam domain for output, and obtaining an azimuth spectrogram of the subarray; the array model and sub-array partitioning are shown in fig. 1.

And 2) determining an interference azimuth by using an azimuth spectrogram obtained by outputting the beam domain of each subarray, performing interference suppression weighting on the beam domain output of the subarray, correcting the interference suppression weighting by using an expected null width to obtain null weighting, obtaining the azimuth spectrogram after interference suppression, and realizing suppression of strong interference and detection of a weak target under a strong interference background.

The step 1) specifically comprises the following steps:

step 1-1) receiving a broadband signal of a remote target by a space linear array to obtain time domain signals x [ d ] of M array elements_m,t]M is array element number, M is 1,2_mMd is the position of the mth array element, and d is the array element interval; dividing the data into N snapshots in time domain, and recording as snapshots 1,2, …, N, …, N, each snapshot x_n[d_m,t]And (3) performing fast Fourier transform on the nth snapshot data in a time domain with the length of L to obtain a frequency spectrum X (m, f) of the mth array element:

wherein t is time, f is frequency, L is the number of sampling points, and the value is a natural number; if the signal sampling rate is F_sThen, the number of sampling points L is:

mu is the resolution of the frequency domain,represents the smallest integer no less than;

step 1-2) dividing the space linear array into y +1 overlapped sub-arrays according to the number y of the interference needing to be suppressed; setting the ith and (i + 1) th sub-arrays of two adjacent overlapped sub-arrays; the difference of the serial numbers of the first array elements of the ith and the (i + 1) th sub-arrays is D; the serial numbers of the first array elements of the two adjacent overlapping subarrays are m respectively_i(i-1) D and m_i+1The number of each subarray element is M-yD, and the time domain spectrums of the two adjacent overlapping subarray signals are respectively marked as X⁽ⁱ⁾(f) And X⁽ⁱ⁺¹⁾(f)：

X⁽ⁱ⁾(f)＝[X(m_i+1,f),X(m_i+2,f),…,X(m_i+M-yD,f)]^T(3)

X⁽ⁱ⁺¹⁾(f)＝[X(m_i+1+1,f),X(m_i+1+2,f),…,X(m_i+1+M-yD,f)]^T(4)

Wherein i is 1,2,. y; y ═ 1, T denotes the transposition operation;

step 1-3) determining the frequency band range [ f ] of the frequency spectrum X (m, f) of the mth array element_min,f_max]，f_minIs a minimum value of frequency, f_maxFor the frequency maximum value, respectively carrying out phase compensation on each frequency component in the frequency band range, respectively synthesizing the data after the phase compensation into the two adjacent overlapped subarray wave beams and outputting BF_l ⁽ⁱ⁾(theta) and BF_l ⁽ⁱ⁺¹⁾(θ)；

BF_l ⁽ⁱ⁾(θ)＝w^(i)H(θ)·X⁽ⁱ⁾(m,f) (5)

BF_l ⁽ⁱ⁺¹⁾(θ)＝w^(i+1)H(θ)·X⁽ⁱ⁺¹⁾(m,f) (6)

Wherein theta is a scanning azimuth angle and takes a value of 0-180 degrees, superscript H represents complex conjugate transpose operation, l is the first interference needing to be suppressed, an initial value is 1, and the values are 1-y; the weighting vectors of the two adjacent overlapping sub-arrays are respectively w⁽ⁱ⁾(theta) and w⁽ⁱ⁺¹⁾(θ)：

c is the propagation speed of sound in the ocean, and theta is the scanning azimuth angle and takes a value of 0-180 degrees. For theta ═ theta_mThe directional interference, the beam output relationship of the two adjacent overlapping subarrays is:

the steps 1-3) may adopt conventional beam forming or adaptive beam forming method, specifically adopt weighting beam forming method, and only change the weighting vector w⁽¹⁾(theta) and w⁽²⁾(θ)。

The step 2) specifically comprises the following steps:

step 2-1) outputting BF according to the wave beams of the two adjacent overlapped sub-arrays_l ⁽ⁱ⁾(theta) and BF_l ⁽ⁱ⁺¹⁾Determining the interference orientation by the overlapping subarray orientation spectrogram formed by (theta), wherein the peak value formed by strong interference is usually far larger than the signal peak value, and taking the orientation with the maximum peak value in the orientation spectrogram as the interference orientation theta_m，θ_mTaking a value of 0-180 degrees;

step 2-2) based on the interference orientation theta_mCalculating an interference suppression weighting vector and correcting to obtain a corrected interference suppression weighting vector;

interference rejection weight vector w_IS(θ_m)：

The non-null-weighted subarray directional function DI obtained from equation (6)_sub(θ) is:

wherein, theta₀The target signal orientation is set to be 0-180 degrees. In the interference orientation theta ═θ_mNon-null weighted subarray directivity function DI_subThe output (θ) is 0, and it is known that the disturbance azimuth energy is suppressed, but the suppression width is not controllable.

According to the serial number difference D of the first array elements of the ith and the (i + 1) th sub-arrays and the interference direction theta_mDetermining the null weighting vector weight by the null width delta expected to be suppressed_null(θ) is:

correcting interference suppression weight, wherein the corrected weight vector is w'_IS(θ|θ_m)：

w′_IS(θ|θ_m)＝weight_null(θ)·w_IS(θ_m) (13)

Controllable suppression width is realized through designed null weighting vector, and the aim of interference orientation theta is realized_mWide beam interference suppression of (3);

the null weighting vector is different from the selected first array element D and the interference direction theta_mThe width Δ of the null desired to be suppressed is all related;

the null width delta is an important factor influencing interference suppression, the selection of delta is too narrow to suppress interference in a wide range, and the selection of delta is too wide to degrade into the situation of unweighted subarray interference suppression.

The invention provides an optional method, firstly, a null depth threshold U is selected, and the value of a critical null width delta satisfies the following conditions:

10lg|2·sin(πfDd(cos(θ_m+Δ)-cosθ_m)/c)|≤U (14)；

step 2-3) utilizing the corrected weighting vector to carry out interference suppression weighting on the beam outputs of the two adjacent overlapped subarrays to obtain the azimuth theta_mSuppressed ith beam output

The modified directional function DI after the weighted vector interference suppression adopted by the invention_s′_ub(θ) and Coef' are:

Coef′＝|2*sin(πDdf(cosθ-cosθ_m)/c)|*weight_null(17)

wherein, theta₀The target signal orientation is set to be 0-180 degrees. In the interference azimuth, the directivity function DI 'after the interference suppression'_subThe output (theta) is 0, which indicates that the interference azimuth energy is suppressed, and the null width can be controlled by a proper amount of null formaldehyde.

Step 2-4) solving the beam output of all adjacent sub-arrays in sequence, and writing the beam output into a vector form

Judging whether other interference orientations which need to be suppressed exist or not, namely whether l < y is true or not, if the other interference orientations which need to be suppressed exist, if yes, l is l +1, and returning to the step 2-1) to continue execution;

if not, the interference direction which is expected to be suppressed is traversed, and the output of the wave beam is recorded as BF_y+1(θ), performing step 2-5);

step 2-5) outputting BF based on the beam_y+1And (theta) outputting a result to obtain an orientation spectrogram after interference suppression, so that suppression of strong interference and detection of a weak target under a strong interference background are realized.