Near-field strong interference suppression method based on spherical wave deconvolution beam forming positioning

Abstract

The invention discloses a near-field strong interference suppression method based on spherical wave deconvolution beam forming positioning. The method comprises the following steps: carrying out fine grid division on a towed line array near-field scanning area; spherical wave focusing beam forming and distance-angle two-dimensional deconvolution beam forming under the condition of unknown sound source position are carried out in a near-field scanning area; calculating distribution entropy characteristics of a deconvolution beam forming result in an angle dimension, and performing interference positioning of an associated target by using a preset threshold value; constructing an array manifold matrix Al of each near-field target and generating a covariance matrix A; calculating an orthogonal complementary space projection matrix of the covariance matrix A, and enabling the orthogonal complementary space projection matrix to act on the array element domain covariance matrix C to perform near-field interference suppression; and performing deconvolution beam forming calculation on the covariance matrix for suppressing near-field interference by using a far-field plane wave model to obtain a passive detection result of near-field strong interference suppression. According to the invention, near-field interference positioning and interference suppression can be realized under the condition that the interference position is unknown.

Description

Technical Field

[0001] The invention belongs to the field of towed array passive target detection, and in particular relates to a near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning. Background Art

[0002] With the development of vibration and noise reduction technology, the target noise level, especially the high-frequency noise level, has dropped sharply, but the low-frequency noise is difficult to reduce. The towed array is suitable for underwater acoustic target detection due to its large aperture, low detection frequency, and low interference noise from the ship. When detecting with a large aperture towed array, strong near-field interference has a greater impact on the target detection performance, especially when the target of interest and the strong near-field interference are close in position.

[0003] Currently, the common near-field interference suppression method generally uses inverse beamforming combined with adaptive filtering to achieve interference cancellation. However, the position of the interference target is unknown or the position estimation is inaccurate, making it difficult to achieve good interference suppression performance. Summary of the invention

[0004] The purpose of the present invention is to provide a method for suppressing strong near-field interference of a large-aperture towed array based on spherical wave deconvolution beamforming positioning, so as to achieve accurate positioning of near-field interference, suppress near-field interference, and improve target detection performance.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning, the method comprising:

[0007] Fine-grained grid division of the near-field scanning area of ​​the towed array;

[0008] Spherical wave focusing beamforming in the near-field scanning area and 2D deconvolution beamforming with respect to range-angle when the sound source position is unknown;

[0009] Calculate the distribution entropy characteristics of the deconvolution beamforming results in the angle dimension, and use the preset threshold to locate the interference of the associated target;

[0010] Construct the array flow matrix A of each near-field target l And generate the covariance matrix A of the array flow matrix;

[0011] Calculate the orthogonal complement space projection matrix of the covariance matrix A, and apply the projection matrix to the array element domain covariance matrix C to suppress near-field interference;

[0012] The far-field plane wave model is used to perform deconvolution beamforming calculation on the covariance matrix for suppressing near-field interference, and the passive detection results for suppressing strong near-field interference are obtained.

[0013] Preferably, the fine-grained grid division of the near-field scanning area of ​​the towed array includes:

[0014] The far field and near field of the towed array are roughly divided to obtain the near field scanning area of ​​the towed array;

[0015] Based on the required near-field estimation resolution, the near-field scanning area of ​​the towed array is finely meshed.

[0016] Preferably, the coarse division of the far field and the near field of the towed array adopts a towed array focusing distance division method, including:

[0017] Assuming the target is a far-field plane wave, the scanning area R = [r1, r2, ..., r n ], according to the spherical wave beamforming, the signal level SL(r) after array gain at different focusing distances is obtained, and the signal loss Loss(r)=SL-SL(r) caused by the focus not rotating is calculated, where SL is the signal level obtained according to the plane wave beamforming;

[0018] Compare the signal loss Loss(r), r=1, 2, ..., n with the allowable signal loss σ. When Loss(r)≥σ and min(Loss(r)-σ), the corresponding r is the focusing distance when the signal loss Loss is closest to σ. The critical distance of the far and near fields of the towed array is R. m =r.

[0019] Preferably, the spherical wave focusing beamforming algorithm is expressed as

[0020]

[0021] Wherein, P′(r, θ) is the spatial spectrum when the focusing distance is r and the focusing azimuth is θ, c is the wave velocity, d is the array element spacing of the towed array, M is the number of array elements of the towed array, r is the focusing distance, θ is the focusing azimuth, x0 is the distance difference between the sound signal to each sound channel and to the reference sound channel, j is an imaginary number, f is the signal frequency, a is the steering vector, τ is the arrival delay of the signal with a distance of r and a focusing azimuth of θ in each sound channel, T is the transpose, X=[x1(f), x2(f), ..., x M (f)] represents the Fourier transform result of the array element domain signal at frequency f.

[0022] Preferably, the two-dimensional deconvolution beamforming with respect to distance-angle when the sound source position is unknown in the scanning area comprises:

[0023] Calculate the scattering function of the sound source at 90° as the distance r changes

[0024] Where, rs is the distance from the sound source to each element of the towed array, rr is the distance from the scanning point to each element of the towed array, and a is the reciprocal of the distance from the sound source to each element of the towed array;

[0025] The deconvolution beamforming result P1 is calculated based on the spatial spectrum P′(r, θ) and the scattering function PSF;

[0026] The spatial spectrum distribution at the center distance of P1 is taken as the deconvolution spatial spectrum P at the distance r deconv , scan the distance dimension and obtain the two-dimensional deconvolution beamforming result P deconv (r, θ).

[0027] Preferably, the step of calculating the distribution entropy characteristics of the deconvolution beamforming result in the angle dimension and using a preset threshold to perform interference positioning of the associated target comprises the following steps:

[0028] The two-dimensional deconvolution beamforming result P deconv (r, θ) is sliced ​​in the angle dimension θ = {θ1, θ2, ..., θ k , ...}, k is the slice index, calculate P deconv The distribution entropy of the (r, θ) angle-dimensional slice Entropy(θ k );

[0029] Determine the distribution entropy value Entropy(θ k ) is not greater than the threshold TEntropy of the set distribution entropy value. If so, extract P deconv (r, θ) k The distance r corresponding to the maximum value of the slice k , identify the scanning grid (r k ,θ k ) There is near-field interference.

[0030] Preferably, the orthogonal complement space projection matrix calculation formula of the covariance matrix A of the array flow matrix is:

[0031] P=IA T (AA T ) -1 A

[0032] Where T is the transpose and I is the identity matrix.

[0033] Preferably, the calculation formula of the projection matrix P acting on the array element domain covariance matrix C is: C=PC.

[0034] Preferably, the deconvolution beamforming calculation of the covariance matrix for suppressing near-field interference using the far-field plane wave model includes:

[0035] The far-field plane beamforming result ISCBF is calculated using the covariance matrix C of near-field interference suppression;

[0036] The far-field deconvolution beamforming scattering function PSF and the far-field planar beamforming result ISCBF are used as the input of the RL deconvolution algorithm to obtain the deconvolution beamforming result ISDBF after suppressing near-field interference.

[0037] Preferably, the RL deconvolution algorithm formula is expressed as:

[0038]

[0039] Where i is the number of iterations, r is the scanning distance range, θ is the scanning angle, is the distance angle two-dimensional spatial spectrum estimation result obtained by the i-th deconvolution iteration, and P(r, θ) is the distance angle two-dimensional spatial spectrum estimation obtained by conventional beamforming.

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

[0041] Based on the spherical wave model, the present invention realizes near-field target positioning in the distance-angle dimension by using a high-precision deconvolution beamforming method combined with distributed entropy information, and constructs an array flow matrix with strong interference of the near-field model according to the positioning result. Then, the covariance matrix of the received signal is projected in the orthogonal complement space of the flow matrix as a new covariance matrix and far-field beamforming is performed. It can realize near-field interference positioning and interference suppression when the interference position is unknown, thereby improving the target detection performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 Flow chart of the method of the present invention.

[0043] Figure 2 This is the result diagram of the near-field focusing distance division.

[0044] Figure 3 A plot of focused beamforming results for a finely meshed near field.

[0045] Figure 4 This is the result of two-dimensional deconvolution beamforming.

[0046] Figure 5 This is the distribution entropy and near-field target positioning result diagram.

[0047] Figure 6 It is the beam pattern after strong interference suppression. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of the present invention.

[0049] Reference Figure 1 As shown, a near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning includes the following 8 steps.

[0050] Step 1: Use the towed array focusing distance division method to roughly divide the far field and near field of the towed array to obtain the near field scanning area of ​​the towed array, such as Figure 2 shown.

[0051] The far-field and near-field division process of the towed array focusing distance division method is as follows:

[0052] Step 1.1, assume that the target sound source is a far-field plane wave, and the scanning area R = [r1, r2, ..., r n ], according to the spherical wave beamforming, the signal level SL(r) after array gain at different focusing distances is obtained, and the signal loss Loss(r)=SL-SL(r) caused by the focus not rotating is calculated, where SL is the signal level obtained according to the plane wave beamforming;

[0053] Step 1.2, compare the signal loss Loss(r) with the allowable signal loss σ. When Loss(r) ≥ σ and min(Loss(r)-σ), the corresponding r is the focusing distance when the signal loss Loss is closest to σ. The critical distance of the far and near fields of the towed array is R. m =r.

[0054] In step 1, the critical distance R of the far and near fields of the towed array is m , the near-field scanning area can be obtained as [R min , R m ], R min =min(R).

[0055] Step 2: Based on the required near-field estimation resolution, the near-field scanning area of ​​the towed array is finely meshed.

[0056] Here, the refined grid division result is also the beamforming focusing distance [0, R m ], uniform partition result with step size of Δr.

[0057] Step 3: According to equation (1), spherical wave focusing beamforming is performed on the array domain data in the near field scanning area to obtain the spatial spectrum P(r, θ) when the focusing distance is r and the focusing direction is θ, as shown in Figure 3 As shown,

[0058]

[0059] Where c is the wave velocity, d is the array element spacing of the towed array, M is the number of array elements of the towed array, r is the focusing distance, θ is the focusing azimuth, x0 is the distance difference between the sound signal to each sound channel and to the reference sound channel, j is an imaginary number, f is the signal frequency, a is the steering vector, τ is the arrival delay of the signal with a distance of r and a focusing azimuth of θ in each sound channel, T is the transpose, X = [x1(f), x2(f), ..., x M (f)] represents the Fourier transform result of the array element domain signal at frequency f. In this embodiment, the reference sound channel selects the middle sound channel.

[0060] Step 4: Calculate the scattering function psf(r, 90°) of the sound source at 90° azimuth with distance r, and calculate the deconvolution beamforming distance angle two-dimensional spatial spectrum estimate P according to the spatial spectrum P′(r, θ) and the scattering function psf(r, 90°). deconv (r, θ), and then perform angle-dimensional slicing θ={θ1, θ2, ..., θ k , ...}, calculate P deconv The distribution entropy of (r, θ) in the angle dimension is Entropy(θ k ), k=1, 2, ... .

[0061] Here, the calculation formula of the scattering function psf is shown in formula (2):

[0062]

[0063] Among them, rs is the distance from the sound source to each element of the towed array, and rr is the distance from the scanning point to each element of the towed array.

[0064] Regarding the calculation formula of distribution entropy, refer to the calculation method in probability theory. This is common knowledge in the field and will not be elaborated here.

[0065] The deconvolution beamforming result P is calculated based on the spatial spectrum P′(r, θ) and the scattering function psf(r, θ). deconv (r, θ) is specifically: the deconvolution beamforming result P1 is calculated according to the spatial spectrum P′(r, θ) obtained in step 3 and the scattering function PSF(r, θ), and the spatial spectrum distribution at the center distance of P1 is used as the deconvolution spatial spectrum P at a distance of r. deconv , scan the distance dimension and obtain the two-dimensional deconvolution beamforming result P deconv (r, θ) Figure 4 shown.

[0066] Step 5: Using the preset threshold value of the distribution entropy feature, interference positioning of the associated target is performed. Specifically:

[0067] The judgment angle is θ k The distribution entropy value Entropy(θ k )≤ the threshold TEntropy of the distribution entropy value. If so, it is determined that at the angle slice θ k There is a near-field interference target, extract P deconv (r, θ) k The distance r corresponding to the maximum value of the slice k , identify the scanning grid (r k ,θ k ) There is near-field interference such as Figure 5 Otherwise, no processing is performed.

[0068] Step 6: Based on the identified near-field interference target, construct the lth near-field target array flow matrix denoted as A l , the array flow matrix formed by all targets is summed up to obtain the covariance matrix A.

[0069] Step 7, calculate the projection matrix P of the covariance matrix A of the array flow matrix in the orthogonal complement space, apply the matrix P to the array element domain covariance matrix C, update the covariance matrix C, and obtain the covariance matrix for suppressing near-field interference.

[0070] Here, the calculation formula of the projection matrix P of the covariance matrix A of the array flow matrix in the orthogonal complement space is:

[0071] P=IA T (AA T )- 1 A (3)

[0072] Where I is the identity matrix.

[0073] Step 8: Use the far-field plane wave model to perform deconvolution beamforming calculation on the covariance matrix for suppressing near-field interference, and obtain the passive detection result of near-field strong interference suppression. Specifically:

[0074] (8-1) Construct the far-field deconvolution beamforming scattering function PSF, and use the updated covariance matrix C to calculate the far-field planar beamforming result ISCBF;

[0075] (8-2) The far-field deconvolution beamforming scattering function PSF and the far-field planar beamforming result ISCBF are used as the input of the RI deconvolution algorithm to obtain the deconvolution beamforming result after suppressing the near-field interference; wherein, the RI deconvolution algorithm formula is expressed as:

[0076]

[0077] Where i is the number of iterations, r is the scanning distance range, θ is the scanning angle, is the distance angle two-dimensional spatial spectrum estimation result obtained by the t-th deconvolution iteration, P(r, θ) is the distance angle two-dimensional spatial spectrum estimation obtained by conventional beamforming, Ω and Θ are the integration ranges of the angle dimension and the distance dimension respectively, and α and β are the corresponding integration variables.

[0078] In this embodiment, the deconvolution beamforming result ISDBF after suppressing near-field interference is calculated as follows: Figure 6 shown.

[0079] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning, characterized in that: The method comprises: Fine-grained grid division of the near-field scanning area of ​​the towed array; Spherical wave focusing beamforming in the near-field scanning area and 2D deconvolution beamforming with respect to range-angle when the sound source position is unknown; Calculate the distribution entropy characteristics of the deconvolution beamforming results in the angle dimension, and use the preset threshold to locate the interference of the associated target; Construct the array flow matrix A of each near-field target l And generate the covariance matrix A of the array flow matrix; Calculate the orthogonal complement space projection matrix of the covariance matrix A, and apply the projection matrix to the array element domain covariance matrix C to suppress near-field interference; The far-field plane wave model is used to perform deconvolution beamforming calculation on the covariance matrix for suppressing near-field interference, and the passive detection results for suppressing strong near-field interference are obtained.

2. The near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning as claimed in claim 1, characterized in that: The fine grid division of the near-field scanning area of ​​the towed array includes: The far field and near field of the towed array are roughly divided to obtain the near field scanning area of ​​the towed array; Based on the required near-field estimation resolution, the near-field scanning area of ​​the towed array is finely meshed.

3. The near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning as claimed in claim 2, characterized in that: The rough division of the far field and the near field of the towed array adopts the towed array focusing distance division method, which includes: Assuming the target is a far-field plane wave, the scanning area R = [r1, r2, ..., r n ], according to the spherical wave beamforming, the signal level SL(r) after array gain at different focusing distances is obtained, and the signal loss Loss(r)=SL-SL(r) caused by the focus not rotating is calculated, where SL is the signal level obtained according to the plane wave beamforming; Compare the signal loss Loss(r), r=1, 2, ..., n with the allowable signal loss σ. When Loss(r)≥σ and min(Loss(r)-σ), the corresponding r is the focusing distance when the signal loss Loss is closest to σ. The critical distance between the far and near fields of the towed array is R. m =r.

4. The near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning as claimed in claim 1, characterized in that: The spherical wave focusing beamforming algorithm is expressed as Wherein, P′(r, θ) is the spatial spectrum when the focusing distance is r and the focusing azimuth is θ, c is the wave velocity, d is the array element spacing of the towed array, M is the number of array elements of the towed array, r is the focusing distance, θ is the focusing azimuth, x0 is the distance difference between the sound signal to each sound channel and to the reference sound channel, j is an imaginary number, f is the signal frequency, a is the steering vector, τ is the arrival delay of the signal with a distance of r and a focusing azimuth of θ in each sound channel, T is the transpose, X=[x1(f), x2(f), ..., x M (f)] represents the Fourier transform result of the array element domain signal at frequency f.

5. The near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning as claimed in claim 1, characterized in that: The two-dimensional deconvolution beamforming about distance-angle when the position of the sound source is unknown in the scanning area includes: Calculate the scattering function of the sound source at 90° as the distance r changes Where, rs is the distance from the sound source to each element of the towed array, rr is the distance from the scanning point to each element of the towed array, and a is the reciprocal of the distance from the sound source to each element of the towed array; The deconvolution beamforming result P1 is calculated based on the spatial spectrum P′(r, θ) and the scattering function PSF; The spatial spectrum distribution at the center distance of P1 is taken as the deconvolution spatial spectrum P at the distance r deconv , scan the distance dimension and obtain the two-dimensional deconvolution beamforming result P deconv (r, θ).

6. The near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning as claimed in claim 1, characterized in that: The method of calculating the distribution entropy characteristics of the deconvolution beamforming result in the angle dimension and using a preset threshold to perform interference positioning of the associated target includes the following steps: The two-dimensional deconvolution beamforming result P deconv (r, θ) is sliced ​​in the angle dimension θ = {θ1, θ2, ..., θ k , ...}, k is the slice index, calculate P deconv The distribution entropy of the (r, θ) angle-dimensional slice Entropy(θ k ); Determine the distribution entropy value Entropy(θ k ) is not greater than the threshold TEntropy of the set distribution entropy value. If so, extract P deconv (r, θ) k The distance r corresponding to the maximum value of the slice k , identify the scanning grid (r k ,θ k ) There is near-field interference.

7. The near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning as claimed in claim 1, characterized in that: The orthogonal complement space projection matrix calculation formula of the covariance matrix A of the array flow matrix is: P=I-A T (AA T )- 1 A Where T is the transpose and I is the identity matrix.

8. The near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning as claimed in claim 1, characterized in that: The calculation formula of the projection matrix P acting on the array element domain covariance matrix C is: C=PC.

9. The near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning as claimed in claim 1, characterized in that: The deconvolution beamforming calculation of the covariance matrix for suppressing near-field interference using the far-field plane wave model includes: The far-field planar beamforming result ISCBF is calculated using the covariance matrix C of near-field interference suppression; The far-field deconvolution beamforming scattering function PSF and the far-field planar beamforming result ISCBF are used as the input of the RL deconvolution algorithm to obtain the deconvolution beamforming result ISDBF after suppressing near-field interference.

10. The near-field strong interference suppression method based on spherical wave deconvolution beamforming positioning as claimed in claim 9, characterized in that: The RI deconvolution algorithm formula is expressed as: Where i is the number of iterations, r is the scanning distance range, θ is the scanning angle, is the distance angle two-dimensional spatial spectrum estimation result obtained by the i-th deconvolution iteration, and P(r, θ) is the distance angle two-dimensional spatial spectrum estimation obtained by conventional beamforming.

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