Sonar platform self-noise interference removal method and system, device, and storage medium

Abstract

A sonar platform self-noise interference removal method and system, a device, and a storage medium. The method comprises: mounting a hydrophone array on one side of a sonar platform; dividing a sonar platform space into a grid, and constructing matrix A1 using an acoustic transfer function between each point on the grid and each array element; dividing a target radiation sound source space into a grid, and constructing matrix A2 using an acoustic transfer function between each point on the grid and each array element; concatenating matrix A1 and matrix A2 to form matrix A; using an acoustic transfer function of a unit point sound source at the position of an i-th array element at each point in the sonar platform space to construct matrix B1i, and constructing an all-zero matrix B2; concatenating matrix B1i and the all-zero matrix B2 to form matrix Bi; solving using matrix A and matrix Bi to obtain a weighting coefficient qi: assuming that a signal acquired by the hydrophone array is matrix X, and thus a self-noise component on the i-th array element is expressed as ni＝qiX, subtracting ni from a signal received by the i-th array element to obtain a signal not containing the self-noise component; and implementing removal of self-noise on each array element.

Description

A method, system, device and storage medium for removing self-noise interference from a sonar platform Technical Field

[0001] The present invention belongs to the technical field of sonar array noise reduction, and specifically relates to a method, system, device and storage medium for removing self-noise interference from a sonar platform. Background Art

[0002] When sonar detects a target, two types of signals are present on the sonar array element: the sonar platform's self-noise and the target's radiated acoustic signal. To reduce the impact of the sonar platform's self-noise on the sonar system's detection performance, scholars both domestically and internationally have proposed various solutions, ultimately aiming to achieve separation of the sonar platform's self-noise from the target's radiated acoustic signal.

[0003] The complex components of the target's acoustic signal and the variable acoustic propagation channels make it difficult to initially determine the target's acoustic signal components at the array element. However, the sonar platform is close to the sonar, the acoustic propagation path remains essentially unchanged, and the spatial relative position of the sound source and the sonar array element is fixed, making the self-noise components at the sonar array element relatively easy to determine. Therefore, the key to separating the sonar platform's self-noise from the target's acoustic signal lies in accurately and effectively obtaining the self-noise components at the sonar platform.

[0004] Summary of the Invention

[0005] Purpose of the invention: To address the impact of sonar platform self-noise on the detection performance of the sonar system, the present invention discloses a sonar platform self-noise interference removal method, system, device and storage medium.

[0006] Technical solution: A method for removing self-noise interference from a sonar platform, comprising the following steps:

[0007] Step 1: Install a hydrophone array with Q elements on one side of the sonar platform;

[0008] Step 2: Divide the sonar platform space into a grid, with the number of grid points being N. Under the assumption that the sound wave propagates in a free field, the N×Q matrix A1 is constructed using the acoustic transfer function between each point on the grid and each array element.

[0009] Step 3: Define a target radiation source space in the far field of the hydrophone array and divide the target radiation source space into a grid. The number of points in the grid is M. Under the assumption that the sound wave propagates in a free field, use the acoustic transfer function between each point on the grid and each array element to construct an M×Q matrix A2.

[0010] Step 4: Concatenate matrix A1 and matrix A2 to form matrix A;

[0011] Step 5: Use the sound transfer function of the unit point sound source at the location of the i-th array element at each point in the sonar platform space to construct an N×1 matrix B 1i , and construct an M×1 all-zero matrix B2 using the response requirements of the unit point sound source at the location of the i-th array element to each point in the target radiation sound source space;

[0012] Step 6: Transform the matrix B 1i Concatenate with the all-zero matrix B2 to form matrix B i ;

[0013] Step 7: Using Matrix A and Matrix B i , solve to get the weighted coefficient q i :

[0014] Step 8: Assume that the signal collected by the hydrophone array is a matrix X, then the self-noise component on the i-th array element is expressed as n i =q i X, subtract n from the signal received by the i-th array element i , get the signal without self-noise;

[0015] Step 9: Repeat steps 5 to 8 to remove the self-noise on each array element.

[0016] Furthermore, in step 2, the sonar platform space is divided into grids, and the specific operation is: the sonar platform space is divided into grids with half the shortest wavelength as the interval.

[0017] Furthermore, in step 3, a target radiation sound source space is defined in the far field of the hydrophone array, and the target radiation sound source space is gridded. The specific operations are:

[0018] In the far field of the hydrophone array, a region with a thickness greater than the longest wavelength is defined and recorded as the target radiation sound source space;

[0019] The target radiation sound source space is divided into grids with an interval of half the shortest wavelength.

[0020] Furthermore, in step 7, the matrix A and matrix B are used i , solve to get the weighted coefficient q i , specifically including:

[0021] Using matrix A and matrix B i , the least squares method is used to solve the weighted coefficient q i , so that B i =A×q i .

[0022] Furthermore, the acoustic transfer function is expressed as:

[0023] Where, and are the coordinates of two points, ω is the angular frequency, is the wave number and λ is the wavelength.

[0024] The present invention discloses a sonar platform self-noise interference removal system, comprising:

[0025] A hydrophone array having Q array elements is mounted on one side of the sonar platform;

[0026] The weighting coefficient calculation module is used to perform the following steps:

[0027] The sonar platform space is divided into a grid, with the number of grid points being N. Under the assumption that the sound wave propagates in a free field, an N×Q matrix A1 is constructed using the acoustic transfer function between each point on the grid and each array element. A target radiation sound source space is defined in the far field of the hydrophone array, and the target radiation sound source space is divided into a grid, with the number of grid points being M. Under the assumption that the sound wave propagates in a free field, an M×Q matrix A2 is constructed using the acoustic transfer function between each point on the grid and each array element. Matrix A1 and matrix A2 are concatenated to form matrix A.

[0028] The N×1 matrix B is constructed using the acoustic transfer function of the unit point sound source at the location of the i-th array element at each point in the sonar platform space. 1i , and use the response requirements of the unit point sound source at the location of the i-th array element to each point in the target radiation sound source space to construct an M×1 all-zero matrix B2; the matrix B 1i Concatenate with the all-zero matrix B2 to form matrix B i ;

[0029] Using matrix A and matrix B i , solve to get the weighted coefficient q i :

[0030] The self-noise removal module is used to assume that the signal collected by the hydrophone array is a matrix X, then the self-noise component on the i-th array element is expressed as n i =q i X, subtract n from the signal received by the i-th array element i , and obtain a signal that does not contain self-noise.

[0031] Furthermore, in the weighted coefficient calculation module, the sonar platform space is divided into grids, specifically by dividing the sonar platform space into grids with half the shortest wavelength as the interval;

[0032] The specific operations of defining a target radiation sound source space in the far field of the hydrophone array and dividing the target radiation sound source space into grids are as follows:

[0033] In the far field of the hydrophone array, a region with a thickness greater than the longest wavelength is defined and recorded as the target radiation sound source space;

[0034] The target radiation sound source space is divided into grids with an interval of half the shortest wavelength.

[0035] Furthermore, in the weighted coefficient calculation module, the matrix A and matrix B are used i , solve to get the weighted coefficient q i , specifically including:

[0036] Using matrix A and matrix B i , the least squares method is used to solve the weighted coefficient q i .

[0037] The present invention discloses a device, comprising a memory, a processor and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, steps of a method for removing self-noise interference of a sonar platform are implemented.

[0038] The present invention discloses a storage medium storing a self-noise interference removal program. When the self-noise interference removal program is executed by at least one processor, the steps of a method for removing self-noise interference from a sonar platform are implemented.

[0039] Beneficial effects: Compared with the prior art, the present invention has the following advantages:

[0040] (1) The present invention can accurately measure the self-noise of the sonar platform and remove the self-noise;

[0041] (2) The present invention has a clear physical meaning, is not affected by the working frequency bandwidth, and is not limited by the properties of the sound source such as the motion state, material, and shape. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] FIG1 is a flow chart of a method for removing self-noise interference from a sonar platform according to the present invention;

[0043] FIG2 is a working scene layout diagram of the present invention;

[0044] FIG3 is a diagram of the sound field radiated by the sonar platform of the present invention;

[0045] FIG4 shows the direct measurement results and the equivalent field transformation measurement results of the present invention;

[0046] FIG5 is a target radiated acoustic interference of the present invention;

[0047] FIG6 is a measurement result of the present invention when there is target radiated sound interference;

[0048] FIG7 is a diagram showing the relative error of the measurement results in FIG6 of the present invention;

[0049] FIG8 is a comparison of the results of the present invention using equivalent field constraints and far-field target radiation sound suppression constraints with direct measurement results;

[0050] FIG9 shows the relative error of FIG8 of the present invention. DETAILED DESCRIPTION

[0051] The technical solution of the present invention will now be further described with reference to the accompanying drawings and embodiments.

[0052] Example 1:

[0053] As shown in Figure 1, this embodiment discloses a method for removing self-noise interference from a sonar platform. By accurately measuring the self-noise of the sonar platform, the self-noise is removed. Taking the self-noise of the sonar platform as the research object, the main implementation steps are as follows:

[0054] Step 1: As shown in Figure 2, a hydrophone array with Q elements is installed on one side of the sonar platform;

[0055] Step 2: Divide the sonar platform space into a grid with intervals of half the shortest wavelength. The number of points in the grid is N. Under the assumption that the sound wave propagates in a free field, the acoustic transfer function between each point on the grid and each hydrophone is recorded as matrix A1, which is an N×Q matrix.

[0056] The acoustic transfer function between each point on the grid and each hydrophone is expressed as:

[0057] Where, and are the coordinates of the i-th point and the j-th hydrophone on the grid, ω is the angular frequency, is the wave number and λ is the wavelength.

[0058] Step 3: In Figure 2, the vertical dashed line is the boundary between the near field and the far field of the hydrophone array. Outside the boundary, a region of a certain thickness (greater than the longest wavelength) is defined, which is recorded as the target radiation source space. The target radiation source space is divided into a grid with an interval of half the shortest wavelength. The number of points in the grid is M. Under the assumption that the sound wave propagates in a free field, the acoustic transfer function between each point on the grid and each hydrophone is recorded as the matrix A2, which is an M×Q matrix.

[0059] Step 4: Concatenate matrix A1 and matrix A2 to form matrix A, which is a (N+M)×Q matrix.

[0060] Step 5: The acoustic transfer function of the unit point sound source at the location of the i-th hydrophone at each point in the sonar platform space is recorded as B 1i . B 1i It is an N×1 matrix. Since the hydrophone array is required to have no response to each point in the target radiation sound source space, the response of the hydrophone array to each point in the target radiation sound source space requires that the matrix B2 is an all-zero matrix. B2 is an M×1 all-zero matrix.

[0061] Step 6: B 1i Combined with B2 to form matrix B i , B i is a (N+M)×1 matrix;

[0062] Step 7: For the self-noise measurement of each element in the hydrophone array, assume that there is a weighting coefficient q i , so that B i =A i q i If it is established, then the sonar array can be adjusted with the weighting coefficient q i The self-noise signal on the i-th hydrophone that does not contain far-field radiation sound is obtained under the action of .

[0063] Weighting coefficient q i The least square method can be used to solve it, as shown in formula (1);

[0064] Weighting coefficient q i It can also be solved through other optimization algorithms such as artificial intelligence.

[0065] Step 8: Assuming that the signal collected by the sonar array is matrix X, the self-noise component on the i-th hydrophone is n i =q i X, then the signal received by the i-th hydrophone minus n i , the signal obtained does not contain the self-noise separation, thereby achieving the removal of the sonar platform self-noise on the i-th hydrophone.

[0066] Step 9: By repeating steps 5 to 8, the platform self-noise on each element of the hydrophone array can be removed.

[0067] Figure 3 shows the radiated acoustic field from the sonar platform. When there is no external field interference, the sound pressure amplitudes for each element in the sonar array (a total of 19 elements) are shown in Figure 4. When there is external field interference, the sound pressure amplitudes for each element in the sonar array are shown in Figure 5, and the error compared to Figure 4 is shown in Figure 7. Figure 7 shows that the measurement error of self-noise increases significantly when there is external field interference.

[0068] The scattered points in Figure 8 are the results obtained using this method and are consistent with the measurement results without external field interference. The error compared to Figure 4 is shown in Figure 9. Compared with the direct measurement method, there is almost no error, and the measurement results are not affected by external fields.

[0069] Example 2:

[0070] This embodiment discloses a sonar platform self-noise interference removal system, comprising:

[0071] A hydrophone array having Q array elements is mounted on one side of the sonar platform;

[0072] The weighting coefficient calculation module is used to perform the following steps:

[0073] The sonar platform space is divided into a grid, with the number of grid points being N. Under the assumption that the sound wave propagates in a free field, an N×Q matrix A1 is constructed using the acoustic transfer function between each point on the grid and each array element. A target radiation sound source space is defined in the far field of the hydrophone array, and the target radiation sound source space is divided into a grid, with the number of grid points being M. Under the assumption that the sound wave propagates in a free field, an M×Q matrix A2 is constructed using the acoustic transfer function between each point on the grid and each array element. Matrix A1 and matrix A2 are concatenated to form matrix A.

[0074] The N×1 matrix B is constructed using the acoustic transfer function of the unit point sound source at the location of the i-th array element at each point in the sonar platform space. 1i , and use the response requirements of the unit point sound source at the location of the i-th array element to each point in the target radiation sound source space to construct an M×1 all-zero matrix B2; the matrix B 1i Concatenate with the all-zero matrix B2 to form matrix B i ;

[0075] Using matrix A and matrix B i , solve to get the weighted coefficient q i :

[0076] The self-noise removal module is used to assume that the signal collected by the hydrophone array is a matrix X, then the self-noise component on the i-th array element is expressed as n i =q i X, subtract n from the signal received by the i-th array element i , and obtain a signal that does not contain self-noise.

[0077] Example 3:

[0078] This embodiment discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps disclosed in any one of the above embodiments are implemented.

[0079] Example 4:

[0080] This embodiment discloses a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps disclosed in any one of the above embodiments are implemented.

[0081] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0082] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0083] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for removing self-noise interference from a sonar platform. Features: The following steps are involved: Step 1: Install a hydrophone array with Q array elements on one side of the sonar platform; Step 2: Divide the sonar platform space into grids, and record the number of grid points as N. Under the assumption that the sound wave propagates in a free field, use the acoustic transfer function between each point on the grid and each array element to construct an N×Q matrix A. 1 ; Step 3: Define a target radiation sound source space in the far field of the hydrophone array, divide the target radiation sound source space into a grid, and record the number of grid points as M. Under the assumption that the sound wave propagates in the free field, use the acoustic transfer function between each point on the grid and each array element to construct an M×Q matrix A 2 ; Step 4: Transform the matrix A 1 With the matrix A 2 Splice to form matrix A; Step 5: Use the sound transfer function of the unit point sound source at the location of the i-th array element at each point in the sonar platform space to construct an N×1 matrix B 1i , and the M×1 all-zero matrix B is constructed by using the response requirements of the unit point sound source at the location of the i-th array element to each point in the target radiation sound source space 2 ; Step 6: Transform the matrix B 1i With all zero matrix B 2 Splice to form matrix B i ; Step 7: Using Matrix A and Matrix B i , solve for the weighted coefficient q i , so that B i =A×q i : Step 8: Assume that the signal collected by the hydrophone array is a matrix X, then the self-noise component on the i-th array element is expressed as n i =q i X, subtract n from the signal received by the i-th array element i , and obtain a signal that does not contain self-noise; Step 9: By repeating steps 5 to 8, self-noise removal is achieved on each array element.

2. A method for removing self-noise interference from a sonar platform according to claim 1, Features: In step 2, the sonar platform space is divided into grids, and the specific operation is: the sonar platform space is divided into grids with half the shortest wavelength as the interval.

3. A method for removing self-noise interference of a sonar platform according to claim 1, Features: In step 3, a target radiation sound source space is defined in the far field of the hydrophone array, and the target radiation sound source space is gridded. The specific operations are as follows: A region with a thickness greater than the longest wavelength is defined in the far field of the hydrophone array, which is recorded as the target radiation sound source space; The target radiation sound source space is meshed at intervals of half the shortest wavelength.

4. A method for removing self-noise interference from a sonar platform according to claim 1, Features: In step 7, the matrix A and matrix B are used i , solve for the weighted coefficient q i , so that B i =A×q i , specifically including: Using matrix A and matrix B i , the least squares method is used to solve the weighted coefficient q i .

5. The method for removing self-noise interference of a sonar platform according to claim 1, Features: The acoustic transfer function is expressed as: In the formula, and are the coordinates of two points, ω is the angular frequency, is the wave number and λ is the wavelength.

6. A sonar platform self-noise interference removal system, Features: include: A hydrophone array having Q array elements is installed on one side of the sonar platform; The weighting coefficient calculation module is used to perform the following steps: The sonar platform space is divided into grids, and the number of grid points is recorded as N. Under the assumption that the sound wave propagates in a free field, the N×Q matrix A is constructed using the acoustic transfer function between each point on the grid and each array element. 1 ; Define a target radiation sound source space in the far field of the hydrophone array, divide the target radiation sound source space into a grid, and record the number of grid points as M. Under the assumption that the sound wave propagates in the free field, use the acoustic transfer function between each point on the grid and each array element to construct an M×Q matrix A 2 ; The matrix A 1 With the matrix A 2 Splice to form matrix A; The N×1 matrix B is constructed using the acoustic transfer function of the unit point sound source at the location of the i-th array element at each point in the sonar platform space. 1i , and the M×1 all-zero matrix B is constructed by using the response requirements of the unit point sound source at the location of the i-th array element to each point in the target radiation sound source space 2 ; Matrix B 1i With all zero matrix B 2 Splice to form matrix B i ; Using matrix A and matrix B i , solve for the weighted coefficient q i , so that B i =A×q i : The self-noise removal module is used to assume that the signal collected by the hydrophone array is a matrix X, then the self-noise component on the i-th array element is expressed as n i =q i X, subtract n from the signal received by the i-th array element i , and obtain a signal that does not contain self-noise.

7. A sonar platform self-noise interference removal system according to claim 6, Features: In the weighted coefficient calculation module, the sonar platform space is divided into grids, and the specific operation is: the sonar platform space is divided into grids with half the shortest wavelength as the interval; The specific operation of defining a target radiation sound source space in the far field of the hydrophone array and dividing the target radiation sound source space into grids is as follows: A region with a thickness greater than the longest wavelength is defined in the far field of the hydrophone array, which is recorded as the target radiation sound source space; The target radiation sound source space is meshed at intervals of half the shortest wavelength.

8. A sonar platform self-noise interference removal system according to claim 6, Features: In the weighted coefficient calculation module, the matrix A and matrix B are used i , solve for the weighted coefficient q i Make B i =A×q i , specifically including: Using matrix A and matrix B i , the least squares method is used to solve the weighted coefficient q i .

9. A device, It is characterized in that The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of a method for removing self-noise interference of a sonar platform as claimed in claims 1 to 5 are implemented.

10. A storage medium, It is characterized in that The storage medium stores a self-noise interference removal program, and when the self-noise interference removal program is executed by at least one processor, the steps of a sonar platform self-noise interference removal method according to claims 1 to 5 are implemented.

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