A smoothing filtering method based on multi-beam narrow-band warning line integral

Abstract

The present application relates to the technical field of sonar signal processing, and particularly relates to a smoothing filtering method based on multi-beam narrow-band warning line integration, which comprises the following steps: (1) obtaining multi-beam narrow-band data; (2) pre-processing the obtained multi-beam narrow-band data, and supplementing data values of a half-beam size before and after the data; (3) converting the multi-beam narrow-band data into projection data through line integration transformation, and performing filtering processing on the projection data in the projection domain; and (4) back-projecting the filtered projection data to obtain reconstructed narrow-band data. After the line integration smoothing filtering of the multi-beam narrow-band data, high-resolution spatial energy spectrum can be obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sonar signal processing, and particularly relates to a smoothing filtering method based on multi-beam narrow-band warning line integration. BACKGROUND

[0002] Multi-path propagation in a sonar system refers to the reflection, refraction, scattering and other phenomena caused by different medium interfaces or obstacles in the process of sound wave propagation, which causes the sound signal to reach the receiving point through multiple paths. Different propagation paths cause differences in time, phase and amplitude of the received signal, which further affects the quality of the signal and the accuracy of target detection. In actual working conditions, the detection process of the sonar is affected by various noises. The noises are mainly divided into ocean environmental noise and platform self-noise, and various noise sources together form the receiving noise model of the sonar, and the multi-path effect caused thereby brings challenges to the sonar signal detection.

[0003] The phenomenon of multi-path propagation of towed platform noise is particularly obvious. The multi-path propagation of towed platform noise, strong interference sidelobes / grating lobes and the like have characteristics inconsistent with real target signals on the multi-beam narrow-band spatial spectrum. That is, the real signal has a spatial consistency feature, and the signal components at different frequencies are basically near the same spatial beam, while the multi-path propagation of towed platform noise, strong interference sidelobes / grating lobes and the like are distributed on different beams in the narrow-band beam space, showing the characteristics of "non-vertical, inclined arc".

[0004] The traditional high-resolution narrow-band warning method of the towed line array directly performs weighted averaging or summation processing on each sub-band when obtaining the multi-beam sub-band spatial energy spectrum, which causes the multi-path propagation of towed platform noise introduced by the mismatch of the array model, strong interference sidelobes / grating lobes to be all superimposed on the wide-band spatial energy spectrum, thereby weakening the detection ability of the algorithm for weak signals. Line integration is an important concept in mathematical analysis, which is used to calculate the cumulative effect of the function value or distribution along a certain path, so that these false interferences can be suppressed by line integration smoothing filtering processing in the narrow-band beam space, and the real target signal spectrum feature purification processing in the narrow-band beam space is realized, and then the high-resolution spatial energy spectrum after suppression of the multi-path propagation of towed platform noise, strong interference sidelobes / grating lobes can be obtained through weighted averaging or summation processing of each sub-band. SUMMARY

[0005] In view of the deficiencies in the prior art, the purpose of the present application is to provide a smoothing filtering method based on multi-beam narrow-band warning line integration.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical scheme: a smoothing filtering method based on multi-beam narrow-band warning line integration, characterized in that the steps are as follows:

[0007] (1) Obtain multi-beam narrow-band data;

[0008] (2) Preprocessing the acquired multi-beam narrowband data, and supplementing data values of half-beam size before and after the data;

[0009] (3) Converting the multi-beam narrowband data into projection data through line integral transformation, and performing filtering processing on the projection data in the projection domain;

[0010] (4) Re-projecting the filtered projection data to obtain reconstructed narrowband data.

[0011] In some embodiments, according to step (1), the specific manner is as follows:

[0012] ① Calculate the array manifold matrix: , wherein, N is the total number of array elements, is the element spacing, is the sound speed, , is the upper and lower limits of the processing frequency band, ;

[0013] ② Direct and weight each channel frequency domain array data using the array manifold matrix to obtain the phase-compensated array output matrix:

[0014]

[0015] wherein, is the complex matrix conjugate transpose, is a diagonal matrix composed of the array manifold matrix corresponding to the frequency point, direction, and is called a focusing matrix, and is defined as:

[0016] ;

[0017] ③ Focus processing of the frequency domain array data using the focusing matrix to obtain the directivity power spectral density matrix:

[0018]

[0019] wherein, is the covariance matrix of the frequency point, wherein, is the frequency domain data snapshot number;

[0020] ④ Calculate the optimal weight vector of adaptive waveform recovery and beam output:

[0021]

[0022] array beam output data is:

[0023]

[0024] wherein is the inverse of the steering power spectral density matrix, is an identity matrix.

[0025] In some embodiments according to step (2), the specific way is:

[0026] Adding data values of half-beam size in front of the column and behind the column, data values of half-frequency point size in front of the row and behind the row, data values of half-beam size in front of the column, and so on, to the multi-beam narrowband data;

[0027] Suppose a two-dimensional multi-beam data with a size of , is the number of beams, is the number of frequency points, and the data after data preprocessing has a size of .

[0028] In some embodiments according to step (3), the specific way is:

[0029] Converting the multi-beam narrowband data into projection data by Radon transform,

[0030]

[0031] wherein, is the distance of a straight line to the origin, the projection angle is set to 0 to 180 degrees, is a Dirac function, indicating integration along the straight line .

[0032] The projection data value obtained after narrowband data conversion is , which is a function of distance and angle.

[0033] In some embodiments according to step (3), the value corresponding to the direction of 0° projection angle is reserved, and the values of the remaining directions are filtered.

[0034] In some embodiments according to step (4), the specific way is:

[0035] Performing line integral inverse transform on the filtered data,

[0036]

[0037] wherein, ​is the projection angle, the range is 0 to 180 degrees, is The point is in the projection position at the angle , is a filter function for eliminating high-frequency noise, and the filter function uses a Ram-Lak filter,

[0038]

[0039] After Radon inverse transformation, two-dimensional data is obtained , intercepting , obtaining Multi-beam data of size.

[0040] Compared with the prior art, the beneficial effects of the present application are: by using vertical line integration, reducing the proportion of non-vertical direction after integration, eliminating the noise energy of arc-shaped distribution, and reducing the influence of strong interference sidelobes / grating lobes.

[0041] The line integration smoothing method proposed in the present application is designed based on the multi-path and grating lobe phenomenon existing in the towed array platform. After the multi-beam narrowband data is subjected to line integration smoothing filtering by the method, high-resolution spatial energy spectrum can be obtained.

[0042] The details of one or more embodiments of the present application are presented in the following drawings and description, so that other features, objects and advantages of the present application are more concise and easy to understand. The present application is described and understood in detail through the embodiments of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 is a flow chart of the method of the present application;

[0044] Figure 2 is a multi-path propagation and grating lobe phenomenon diagram in multi-beam narrowband;

[0045] Figure 3 is a result distribution diagram of Radon transformation;

[0046] Figure 4 is a result diagram after line integration filtering processing;

[0047] Figure 5 is a spatial energy spectrum;

[0048] Figure 6 is a processing result of the traditional background equalization method;

[0049] Figure 7 is an algorithm performance comparison diagram. DETAILED DESCRIPTION

[0050] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0051] Please refer to Figures 1 to 4 , the present application provides a technical solution: a smoothing filtering method based on multi-beam narrowband warning line integral, the technical steps and specific implementation are as follows:

[0052] (1) Multi-beam narrowband data acquisition:

[0053] 1) Calculate the array manifold matrix: , is the total number of array elements of the linear array, is the element spacing, is the sound speed, , is the upper and lower limits of the processing frequency band, .

[0054] 2) Use the array manifold matrix to guide and weight each channel frequency domain array data , and get the array output matrix after phase compensation

[0055]

[0056] Among them, is the complex matrix conjugate transpose, is the diagonal matrix composed of the array manifold matrix corresponding to frequency point, direction, called focusing matrix, defined as:

[0057] ;

[0058] 3) Use the focusing matrix to focus process the frequency domain base array data, and get the guide power spectrum density matrix,

[0059]

[0060] Among them is the covariance matrix of frequency point, , wherein is the frequency domain data snapshot number;

[0061] 4) Calculate the optimal weight vector of adaptive waveform recovery and beam output

[0062]

[0063] Array beam output data for

[0064]

[0065] in To find the inverse of the power spectral density matrix, It is a unit array.

[0066] (2) Preprocessing of multi-beam narrowband data

[0067] To prevent data from exceeding limits during online integration and to ensure the accuracy of subsequent processing, a data value equal to half the beam number is added before and after the column of multi-beam narrowband data; a data value equal to half the frequency point number is added before and after the row; a data value equal to the second half of the beam number is added before the column, and so on. For a data of size... Two-dimensional multibeam data , For the number of beams, The number of frequency points refers to the data after preprocessing. Size is .

[0068] (3) Line integral transform and filtering

[0069] Multibeam narrowband data is converted into projected data using Radon transform.

[0070]

[0071] in, It is the distance from the straight line to the origin, and the projection angle. Typically, the temperature ranges from 0 to 180 degrees. It is the Dirac function, representing the function along the straight line. integral.

[0072] Narrowband data is transformed to obtain projected data values , It is a function of distance and angle. This method retains the value corresponding to the 0° direction and filters the values ​​in other directions. Figure 3 For example, the area with the highest brightness is This indicates that it is perpendicular to The region with the highest value represents the distribution area of ​​multipath propagation. This range... The value is set to 0. and The threshold value for the region is set as an adjustment factor. and mean , The threshold value is set to 0.1. Projected values ​​exceeding the threshold are set to 0, while the rest are retained, resulting in the final filtered data. .

[0073] (4) Inverse line integral transform

[0074] Perform an inverse line integral transform on the filtered data.

[0075]

[0076] in, It refers to the projection angle, which ranges from 0 to 180 degrees. yes Point at angle The projection position below. This is a filtering function used to eliminate high-frequency noise. The filtering function uses a Ram-Lak filter.

[0077]

[0078] The inverse Radon transform yields two-dimensional data. ,right Extract the data to obtain the desired result. Multi-beam data of varying sizes.

[0079] According to the technical solution of this application, the noise and interference model of the towing platform shows that the noise multipath propagation and strong interference sidelobe / grating lobe phenomenon exhibit a "non-vertical, inclined arc" characteristic in the narrowband spatial distribution. The final spatial energy spectrum is obtained by summing the energy according to the orientation. Therefore, by using the vertical line integral and reducing the proportion of the non-vertical direction after integration, the arc-shaped noise energy can be eliminated, and the influence of strong interference sidelobe / grating lobe can be reduced.

[0080] The Radon transform is a special type of line integral. Its core principle is to integrate two-dimensional data along a set of straight lines to obtain projected data containing both the projected values ​​and the projected orientation. This projected data can be viewed as the line integrals of the data at different angles. Based on the idea of ​​transform domain filtering, the projected domain data can be filtered to eliminate the effects of multipath propagation and interference. The filtering process can be carried out in two ways. First, because the real signal exhibits consistency in the multi-beam narrowband, it is continuous in the frequency domain and invariant in the beam domain. Noise multipath propagation and strong interference sidelobe / grating lobe effects exhibit a tilted arc-shaped characteristic. After projection through the line integral, they converge at larger angle values. By weakening the line integral values ​​in non-perpendicular directions and retaining the line integral values ​​in the perpendicular directions, the multipath propagation of noise and grating lobe phenomena (such as...) can be effectively suppressed. Figure 2The image shows the effect of noise, exhibiting significant multipath propagation and grating lobe phenomena, requiring post-processing correction. Secondly, considering that the size of the projection domain data corresponds to the continuous value of the integration angle, the impact of multipath propagation does not cover the entire multibeam narrowband region. When reducing the line integral value in non-perpendicular directions, the mean and coefficient factor of that direction are used as a threshold to filter out larger projection values. This cleans up the continuous linear region formed by multipath propagation while retaining useful information in that azimuth. Finally, the projection values ​​are converted back to narrowband data using the inverse Radon transform.

[0081] The proposed line integral smoothing method is designed based on the multipath and grating lobe phenomena present in towed array platforms. After applying line integral smoothing filtering to multibeam narrowband data, the method yields a high-resolution spatial energy spectrum. This work has been validated using simulation and real sea trial data.

[0082] The implementation process is as follows: First, to avoid data out of bounds, the multi-beam narrowband data is preprocessed by adding half-beam-sized data values ​​before and after the data; second, the multi-beam narrowband data is converted into projection data through line integral transform, and the projection data is filtered in the projection domain; finally, the filtered projection data is back-projected to obtain the reconstructed narrowband data.

[0083] like Figure 5 As shown, the spatial energy spectrum of the multibeam narrowband data after line integral filtering has a much higher azimuth resolution than the original method, which indicates that the present invention effectively enhances the system's ability to detect weak targets.

[0084] like Figure 6 The image shown is the result obtained by processing using the traditional background equalization method;

[0085] like Figure 7 As shown, the spatial energy spectrum of multibeam narrowband data after line integral filtering is shown. Blue represents the phenomenon under multipath propagation and strong interference sidelobes / grating lobes, red represents the result of traditional background equalization processing, and yellow represents the effect of processing by this intellectual achievement. After post-processing using this method, the azimuth resolution capability of the algorithm far exceeds that of traditional methods, which indicates that this intellectual achievement effectively enhances the system's ability to detect weak targets.

[0086] 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.

[0087] 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 smoothing filtering method based on multi-beam narrowband warning line integration, characterized in that: The steps are as follows: (1) Acquire multi-beam narrowband data; (2) Preprocess the acquired multi-beam narrowband data by adding half-beam size data values ​​before and after the data; (3) Convert the multibeam narrowband data into projection data by line integral transform, and then filter the projection data in the projection domain; (4) Backproject the filtered projection data to obtain the reconstructed narrowband data.

2. The smoothing filtering method based on multi-beam narrowband warning line integration according to claim 1, characterized in that: According to step (1), the specific method is as follows: ① Calculate the array manifold matrix: , This represents the total number of array elements in the linear array. For the spacing between array elements, For the speed of sound, , To handle the upper and lower limits of the frequency band, ; ② Utilize the array manifold matrix to analyze the frequency domain array data of each channel. By performing guided weighting, the phase-compensated array output matrix is ​​obtained: in, This is the conjugate transpose of a complex matrix. For corresponding Frequency point, The diagonal matrix formed by the array manifold matrices corresponding to the directions is called the focusing matrix, and is defined as: ； ③ By focusing the frequency domain array data using the focusing matrix, the steering power spectral density matrix is ​​obtained: in for The covariance matrix of frequency points ,in For frequency domain data snapshots; ④ Calculate the optimal weight vector and beam output for adaptive waveform restoration: Array beam output data for: in To find the inverse of the power spectral density matrix, It is a unit array.

3. The smoothing filtering method based on multi-beam narrowband warning line integration according to claim 2, characterized in that: According to step (2), the specific method is as follows: Add a value equal to half the number of beams to the beginning and end of the column for multibeam narrowband data, add a value equal to half the number of frequency points to the beginning and end of the row, add a value equal to the second half the number of beams to the beginning of the column, and so on. Suppose that for a size of Two-dimensional multibeam data , For the number of beams, The number of frequency points refers to the data after preprocessing. Size is .

4. The smoothing filtering method based on multi-beam narrowband warning line integration according to claim 3, characterized in that: According to step (3), the specific method is as follows: Multibeam narrowband data is converted into projected data using Radon transform. in, It is the distance from the straight line to the origin, and the projection angle. Set to 0 to 180 degrees. It is the Dirac function, representing the function along the straight line. integral; Narrowband data is transformed to obtain projected data values , It is a function of distance and angle.

5. The smoothing filtering method based on multi-beam narrowband warning line integration according to claim 4, characterized in that: According to step (3), the value corresponding to the direction with a projection angle of 0° is retained, and the values ​​in other directions are filtered.

6. The smoothing filtering method based on multi-beam narrowband warning line integration according to claim 5, characterized in that: According to step (4), the specific method is as follows: Perform an inverse line integral transform on the filtered data. in, It refers to the projection angle, which ranges from 0 to 180 degrees. yes Point at angle The projection position below, This is a filtering function used to eliminate high-frequency noise. The filtering function uses a Ram-Lak filter. The inverse Radon transform yields two-dimensional data. ,right Extract the data to obtain the desired result. Multi-beam data of varying sizes.

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