A passive multi-beam narrow-band detection method under influence of near-field suppression type strong interference

Abstract

The present application relates to the technical field of sonar signal processing, and in particular to a passive multi-beam narrowband detection method under the influence of near-field suppression type strong interference, which realizes the estimation of the distance and azimuth of strong interference by multi-scale focusing distance scanning and conventional beam forming with low computational complexity, thereby realizing the correction of the near-field model; in combination with a tolerant interference suppression method, the strong interference can be effectively suppressed by using the corrected focusing steering vector, and the present application can well suppress the influence of near-field strong interference and effectively improve the narrowband target detection performance of passive sonar in a near-field strong interference environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sonar signal processing, and particularly relates to a passive multi-beam narrowband detection method under the influence of near-field suppressing strong interference. BACKGROUND

[0002] Under the actual underwater acoustic countermeasure interference environment, the detection performance of sonar equipment is sharply reduced, so the target detection technology under the underwater acoustic countermeasure interference gradually becomes one of the focuses in the detection field. The narrowband line spectrum detection is the core feature of the current quiet submarine detection, and the target feature under the current strong interference environment is seriously affected by the interference leakage. The interference suppression method is the main means to solve this problem. However, when the strong interference is located in the near field, the propagation model is mismatched, and the existing interference suppression method loses its spatial filtering performance when the model is mismatched, and the strong interference leakage is still very serious. SUMMARY

[0003] In view of the defects in the prior art, the purpose of the present application is to provide a passive multi-beam narrowband detection method under the influence of near-field suppressing strong interference.

[0004] To achieve the above purpose, the present application provides the following technical scheme: a passive multi-beam narrowband detection method under the influence of near-field suppressing strong interference, the steps of which are as follows:

[0005] (1) First, set the focusing distance scanning interval;

[0006] (2) Calculate the steering vector of different focusing distances, and weight the sonar array data to obtain the multi-focusing distance conventional spatial spectrum estimation result;

[0007] (3) The focusing distance and the direction corresponding to the maximum output energy of the near-field interference are searched to obtain the direction and distance estimation of the near-field interference;

[0008] (4) Then, calculate the interference steering power spectrum density matrix;

[0009] (5) Obtain the tolerant estimation result through feature space processing;

[0010] (6) Use it to construct the interference suppression distance, and perform spatial filtering processing on the sonar array data to obtain the sonar array data after near-field interference suppression;

[0011] (7) Finally, scan the steering vector of the specified focusing distance to obtain the multi-beam time domain data;

[0012] (8) After long-time coherence processing, the multi-beam narrowband detection result is obtained through time-frequency transformation.

[0013] In some embodiments, according to step (1), the specific manner is as follows:

[0014] Set the focus distance scanning gear, for near-field suppression type strong interference, set the focus distance unit meters), the gear can be adjusted according to the demand and computing resources; according to the focus distance gear, calculate the focusing steering vector under the spherical wave model

[0015]

[0016] In the formula, is the scanning direction, is the focus scanning position x-axis and y-axis coordinates, is the sonar array coordinate x-axis and y-axis coordinates, is the processing frequency, is the lower limit of the processing frequency, is the upper limit of the processing frequency, denotes an imaginary number, is the sound speed, is the sound path difference, is the focusing steering vector, is the number of sonar array elements.

[0017] In some embodiments, according to step (2), the specific way is:

[0018] Use the focusing steering vector to perform phase compensation on the frequency domain data of each element of the sonar Take square weighted processing to obtain the spatial spectrum estimation result under each focus distance

[0019]

[0020] In the formula, is the complex matrix conjugate transpose, uniformly weighted sum processing of each frequency point spatial spectrum result, to obtain the wideband detection result under each focus distance,

[0021]

[0022] In some embodiments, according to step (3), the specific way is:

[0023] Search near the suspected near-field interference direction under each focus distance Obtain the near-field interference distance and direction estimation value corresponding to the maximum interference output power

[0024]

[0025] In the formula, is the suspected near-field interference direction, calculated by the traditional plane wave processing model,​​ This is the range and azimuth estimate of the near-field interference obtained through a fast search.

[0026] In some embodiments, step (4) is specifically implemented as follows:

[0027] Calculate the interference focusing steering vector based on the range and azimuth estimates of near-field interference. ,

[0028] ;

[0029] in, The x and y coordinates are for near-field interference. The path difference of sound reaching each array element to suppress near-field interference;

[0030] Based on interference focusing guide vector With array element frequency domain data Calculate the interference-guided power spectral density matrix

[0031]

[0032] For corresponding Frequency point, The focusing guide vector corresponding to the direction The resulting diagonal matrix is ​​called the focusing matrix, and is defined as follows:

[0033]

[0034] In some embodiments, step (5) is specifically implemented as follows:

[0035] Singular value decomposition is performed on the steering power spectral density matrix, and the eigenspace is processed. The eigenspace corresponding to the largest eigenvalue is used to construct a fast-converging interference steering power spectral density matrix.

[0036]

[0037]

[0038] in It is a singular value decomposition function. and These are the eigenvalue and eigenvector matrices, respectively. and These are the largest eigenvalue and the eigenvector corresponding to the largest eigenvalue, respectively;

[0039] Estimating the optimal steering vector for interference using the projection method

[0040]

[0041] in It is a unit vector. .

[0042] In some embodiments, step (6) is specifically implemented as follows:

[0043] Using the modified interference steering vector An interference suppression matrix is ​​constructed, and the sonar array data in the pairwise frequency domain is filtered to obtain the near-field interference-suppressed data. ,

[0044]

[0045]

[0046] in A unit diagonal matrix, .

[0047] In some embodiments, step (7) is specifically implemented as follows:

[0048] Beamforming is performed using sonar array data after near-field interference suppression to recover the time-domain signal, and long-term coherent accumulation is then carried out.

[0049]

[0050]

[0051]

[0052] in, For beamforming output multi-beam frequency domain data, The guide vector for specifying the scan distance, , To specify the scanning distance, The number of points in the Fourier transform. It is the inverse Fourier transform function. To recover the time-domain signal, For long-term coherent accumulation of multibeam time-domain data, This refers to the duration of long-term coherent processing.

[0053] In some embodiments, step (8) is specifically performed as follows:

[0054] Long-time coherent cumulative multibeam data Time-frequency transformation was performed to obtain the multi-beam narrowband detection results.

[0055]

[0056] in This refers to the frequency corresponding to long-term coherent accumulation.

[0057] Compared with existing technologies, the advantages of this invention are as follows: Based on the study of the impact of near-field suppression interference on detection, a multi-beam narrowband detection technology under the influence of strong near-field suppression interference is proposed. Through multi-scale focusing range scanning, relying on conventional beamforming with low computational complexity, the range and azimuth of strong interference can be quickly estimated, thereby correcting the near-field model. Combined with a tolerant interference suppression method, and utilizing the corrected focusing steering vector, effective suppression of strong interference can be achieved. This method has been verified using sea trial data.

[0058] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. The embodiments of this application will provide a detailed description and understanding of the application. Attached Figure Description

[0059] Figure 1 This is a flowchart of the method of the present invention;

[0060] Figure 2 Traditional broadband detection results for sea trial data of towed linear arrays with 1m spacing;

[0061] Figure 3 Broadband detection results at different focusing distances;

[0062] Figure 4 The results show narrowband detection before and after near-field interference suppression under the traditional plane wave model.

[0063] Figure 5 This is to focus on the narrowband detection results before and after near-field interference suppression following distance matching. Detailed Implementation

[0064] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0065] Please see Figure 1This invention provides a technical solution: a passive multi-beam narrowband detection method under the influence of near-field suppression interference. First, a focusing distance scanning interval is set, and the steering vector for different focusing distances is calculated. The sonar array data is weighted and processed to obtain a conventional spatial spectrum estimation result for the multi-focusing distance. Since the near-field suppression interference is energy-intensive, the azimuth and range estimates of the near-field interference are obtained by searching for the focusing distance and azimuth corresponding to the moment when the near-field interference output energy is maximum. Then, the interference steering power spectral density matrix is ​​calculated, and a tolerance-based estimation result is obtained through feature space processing. This result is used to construct the interference suppression distance, and the sonar array data is spatially filtered to obtain the sonar array data after near-field interference suppression. Finally, the steering vector at a specified focusing distance is scanned to obtain multi-beam time-domain data. After long-time coherence processing, time-frequency transformation is performed to obtain the multi-beam narrowband detection result. Verification through sea trial data shows that this method can effectively suppress the influence of near-field interference and significantly improve the performance of passive sonar narrowband target detection under near-field interference conditions.

[0066] Based on the above plan, its specific implementation plan is as follows:

[0067] (1) Set the focus distance scanning mode. For near-field suppression of strong interference, the focus distance can be set. ( (Unit: meters); the focusing distance settings can be adjusted according to needs and computing resources; based on the focusing distance settings, the focusing guide vector under the spherical wave model is calculated.

[0068]

[0069] In the formula, For scanning orientation, To focus the scan position on the x-axis and y-axis coordinates, The x and y coordinates of the sonar array are shown. To handle frequency, To handle the lower frequency limit, To handle the upper frequency limit, represents an imaginary number, For the speed of sound, For sound path difference, To focus the guide vector, The number of sonar array elements;

[0070] (2) Using the focusing steering vector to analyze the frequency domain data of each sonar element Phase compensation is performed, and the results are weighted by square to obtain the spatial spectrum estimation results at each focusing distance.

[0071]

[0072] in, To obtain the broadband detection results at each focusing distance, the spatial spectrum results at each frequency point are uniformly weighted and summed using the conjugate transpose of the complex matrix.

[0073]

[0074] (3) For each focusing distance By searching near the suspected azimuth of strong near-field interference, the estimated near-field interference range and azimuth corresponding to the maximum interference output power are obtained.

[0075]

[0076] in, The suspected near-field interference location can be calculated using a traditional plane wave processing model. This is the range and azimuth estimate of the near-field interference obtained through a fast search.

[0077] (4) Calculate the interference focusing steering vector based on the range and azimuth estimates of near-field interference. ,

[0078]

[0079] in, The x and y coordinates are for near-field interference. The acoustic path difference reaching each array element is used to suppress near-field interference.

[0080] (5) Based on interference focusing guidance vector With array element frequency domain data Calculate the interference-guided power spectral density matrix

[0081]

[0082] in For corresponding Frequency point, The focusing guide vector corresponding to the direction The resulting diagonal matrix is ​​called the focusing matrix, and is defined as follows:

[0083] ;

[0084] (6) Perform singular value decomposition on the steering power spectral density matrix, process the eigenspace, and construct a fast-converging interference steering power spectral density matrix by taking the eigenspace corresponding to the largest eigenvalue.

[0085]

[0086]

[0087] in It is a singular value decomposition function. and These are the eigenvalue and eigenvector matrices, respectively. and These are the largest eigenvalue and the eigenvector corresponding to the largest eigenvalue, respectively;

[0088] (7) Correcting the interference optimal steering vector using the projection method

[0089]

[0090] in It is a unit vector. ;

[0091] (8) Using the modified interference steering vector Construct the interference suppression matrix After filtering the pairwise frequency domain data, the sonar array data with near-field interference suppression is obtained. ,

[0092]

[0093]

[0094] in A unit diagonal matrix, ;

[0095] (9) Beamforming is performed using sonar array data after near-field interference suppression to recover the time-domain signal and perform long-term coherent accumulation.

[0096]

[0097]

[0098]

[0099] in, For beamforming output multi-beam frequency domain data, The guide vector for specifying the scan distance, , To specify the scanning distance, The number of points in the Fourier transform. It is the inverse Fourier transform function. To recover the time-domain signal, For long-term coherent accumulation of multibeam time-domain data, This refers to the duration of long-term coherent processing;

[0100] (10) Time-frequency transformation is performed on long-time coherent cumulative multibeam data to obtain multibeam narrowband detection results.

[0101]

[0102] in The frequency corresponding to long-time coherent accumulation

[0103] The technical solution of this application is used to verify the data from sea trials:

[0104] Appendix Figure 2 The traditional broadband detection results for the towed linear array sea trial data with a 1m spacing, with a processing frequency band of 250-400Hz, show that strong near-field interference moves rapidly, shifting from 83° to around 150° in 6 minutes. The target signal in this trial was located around 130°, creating a large-scale interference blind zone, which severely restricted the detection of weak signals in the vicinity.

[0105] Appendix Figure 3 Broadband detection results at different focusing distances, Figure 3 (a) shows the broadband detection results at different focusing distances; Figure 3 (b) shows the broadband detection amplitude results under different focusing distances; the focusing distance settings are set to [1000:100:8000]m. It can be seen that the output energy and azimuth of the interference change with the focusing distance. The distance estimation and azimuth estimation results of the near-field interference are obtained by searching.

[0106] Appendix Figure 4 These are the narrowband detection results before and after near-field interference suppression under the traditional plane wave model. Figure 4 (a) shows the detection results before interference suppression; Figure 4 (a) shows the detection results after interference suppression. It can be seen from the figure that the strong interference energy is severely dispersed, completely masking the target line spectrum [270Hz, 370Hz] near 130°. Due to model mismatch, the interference suppression effect is not obvious.

[0107] Appendix Figure 5 To focus on the narrowband detection results before and after near-field interference suppression following distance matching, Figure 5 (a) shows the detection results before interference suppression; Figure 5 (b) shows the detection results after interference suppression. It can be seen from the figure that the strong interference energy is concentrated, and the interference suppression has a significant effect on the strong interference. The target line spectrum [270Hz, 370Hz] near 130° can be detected.

[0108] The above embodiments merely illustrate several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

[0109] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A passive multi-beam narrowband detection method under the influence of near-field suppression strong interference, characterized in that: The steps are as follows: (1) First, set the focusing distance and scanning interval; (2) Calculate the steering vector for different focusing distances, weight the sonar array data, and obtain the conventional spatial spectrum estimation results for multiple focusing distances; (3) By searching for the focusing distance and azimuth corresponding to the moment when the output energy of the near-field interference is at its maximum, the azimuth and distance estimates of the near-field interference are obtained; (4) Then, calculate the interference-guided power spectral density matrix; (5) Obtain the tolerance estimation results through feature space processing; (6) Using its interference suppression range, the sonar array data is spatially filtered to obtain the sonar array data after near-field interference suppression; (7) Finally, the multi-beam time domain data is obtained by scanning the guide vector with a specified focusing distance; (8) After long-time coherent processing, the multi-beam narrowband detection result is obtained by time-frequency transformation.

2. The passive multi-beam narrowband detection method under near-field suppression strong interference as described in claim 1, characterized in that: According to step (1), the specific method is as follows: Set the focus distance scanning level to target strong near-field suppression interference. , The unit is meters, and the focus distance settings can be adjusted according to needs and computing resources; based on the focus distance settings, the focus steering vector under the spherical wave model is calculated. , In the formula, For scanning orientation, To focus the scan position on the x-axis and y-axis coordinates, The x and y coordinates of the sonar array are shown. To handle frequency, To handle the lower frequency limit, To handle the upper frequency limit, represents an imaginary number, For the speed of sound, For the sound path difference, To focus the guide vector, The number of sonar array elements.

3. The passive multi-beam narrowband detection method under near-field suppression strong interference as described in claim 2, characterized in that: According to step (2), the specific method is as follows: Using the focusing guide vector to analyze the frequency domain data of each sonar element Phase compensation is performed, and the results are weighted by square to obtain the spatial spectrum estimation results at each focusing distance. in, By performing a conjugate transpose of the complex matrix, the spatial spectrum results at each frequency point are uniformly weighted and summed to obtain the broadband detection results at each focusing distance. 。 4. The passive multi-beam narrowband detection method under near-field suppression strong interference as described in claim 3, characterized in that: According to step (3), the specific method is as follows: For each focusing distance By searching near the suspected azimuth of strong near-field interference, the estimated near-field interference range and azimuth corresponding to the maximum interference output power are obtained. in, The suspected near-field interference location was calculated using a traditional plane wave processing model. This is the range and azimuth estimate of the near-field interference obtained through a fast search.

5. The passive multi-beam narrowband detection method under near-field suppression strong interference as described in claim 4, characterized in that: According to step (4), the specific method is as follows: Calculate the interference focusing steering vector based on the range and azimuth estimates of near-field interference. , ； in, The x and y coordinates are for near-field interference. The path difference of sound reaching each array element to suppress near-field interference; Based on interference focusing guide vector With array element frequency domain data Calculate the interference-guided power spectral density matrix For corresponding Frequency, The focusing guide vector corresponding to the direction The resulting diagonal matrix is ​​called the focusing matrix, and is defined as follows: 。 6. The passive multi-beam narrowband detection method under near-field suppression strong interference as described in claim 5, characterized in that: According to step (5), the specific method is as follows: Singular value decomposition is performed on the steering power spectral density matrix, and the eigenspace is processed. The eigenspace corresponding to the largest eigenvalue is used to construct a fast-converging interference steering power spectral density matrix. in It is a singular value decomposition function. and These are the eigenvalue and eigenvector matrices, respectively. and These are the largest eigenvalue and the eigenvector corresponding to the largest eigenvalue, respectively; Estimating the optimal steering vector for interference using the projection method in It is a unit vector. .

7. The passive multi-beam narrowband detection method under near-field suppression strong interference as described in claim 6, characterized in that: According to step (6), the specific method is as follows: Using the modified interference steering vector An interference suppression matrix is ​​constructed, and the sonar array data in the pairwise frequency domain is filtered to obtain the near-field interference-suppressed data. , in A unit diagonal matrix, .

8. The passive multi-beam narrowband detection method under near-field suppression strong interference as described in claim 7, characterized in that: According to step (7), the specific method is as follows: Beamforming is performed using sonar array data after near-field interference suppression to recover the time-domain signal, followed by long-term coherent accumulation. in, For beamforming output multi-beam frequency domain data, The guide vector for specifying the scan distance, , To specify the scanning distance, The number of points in the Fourier transform. It is the inverse Fourier transform function. To recover the time-domain signal, For long-term coherent accumulation of multibeam time-domain data, This refers to the duration of long-term coherent processing.

9. The passive multi-beam narrowband detection method under near-field suppression strong interference as described in claim 8, characterized in that: According to step (8), the specific method is as follows: Long-time coherent cumulative multibeam data Time-frequency transformation was performed to obtain the multi-beam narrowband detection results. in This refers to the frequency corresponding to long-term coherent accumulation.

Images