Direction estimation method of multi-element three-dimensional hydrophone array

Abstract

The invention relates to the technical field of ultra-short baseline direction measurement data processing, in particular to a direction estimation method of a multi-element stereoscopic hydrophone array. According to the method, sound waves are approximated to plane waves, a mathematical relational expression between time difference of arrival (TDOA) and a direction vector is established, the TDOA serves as an observation value, a direction vector estimated value is calculated according to a weighted least square method, then the equivalence weight of the observation value is calculated according to an equivalence weight function, an original observation value weight matrix is replaced with an equivalence weight matrix, and the observation value is calculated according to the equivalence weight matrix. And calculating the direction vector again according to the weighted least square method, iteratively calculating the equivalence weight and the direction vector until the difference between two continuous direction vectors is smaller than a manually set threshold value, and outputting the direction vector as the direction of the multi-element three-dimensional hydrophone array. According to the direction estimation method, the influence that the direction estimation function model does not consider the sound ray bending can be weakened, and the influence of the array element spacing and the target orientation on the direction estimation is considered, so that the accuracy and the reliability of the direction estimation of the multi-element three-dimensional hydrophone array are improved.

Description

Technical Field

[0001] The invention relates to the technical field of ultra-short baseline direction measurement data processing, and in particular to a direction estimation method for a multi-element stereo hydrophone array. Background Art

[0002] The accuracy of the direction estimation value is one of the main factors affecting the positioning accuracy of the ultra-short baseline and reverse ultra-short baseline positioning systems. Therefore, using the phase difference (PD) or time delay difference (TDD) between the hydrophones in the receiving array to estimate the direction is a key data processing link in the ultra-short baseline direction measurement. At present, in terms of improving the accuracy of the direction estimation value of the hydrophone array, the current research methods are mainly in two aspects: one is to use advanced signal processing methods; the other is to optimize the structure of the hydrophone array, especially to design a multi-element stereo hydrophone array. The former mainly draws on signal processing technology in acoustic communication systems, such as using adaptive minimum mean square error, recursive least squares, Fourier transform and other algorithms to estimate the phase difference or time delay difference, and improve the estimation accuracy of the phase difference or time delay difference; the latter mainly improves the direction measurement performance by increasing the number of receiving array elements (hydrophones) and optimizing the receiving array structure.

[0003] With the three-dimensionalization and diversification of hydrophone receiving arrays, improving the direction estimation accuracy only from the perspective of signal processing can no longer meet the requirements of new receiving arrays. This is mainly manifested in two aspects: first, the receiving array structure is a key factor affecting the quality of observation data. For example, the direction finding accuracy of a planar array under the same measurement environment depends on the spacing between array elements; second, different pairs of array elements in a three-dimensional array are affected differently by changes in underwater sound speed. For example, the phase difference or delay difference measured by two vertically distributed array elements is different from that of two horizontally distributed array elements due to the bending of sound lines. Based on the above two reasons, a new direction estimation method suitable for multi-element three-dimensional arrays needs to be established. Summary of the invention

[0004] In order to solve the problem that the existing direction estimation methods can no longer meet the direction estimation needs of a multi-element stereo hydrophone array, the present invention provides a direction estimation method for a multi-element stereo hydrophone array. By adopting the idea of ​​weighted iteration in anti-error estimation, the function model of direction estimation can weaken the influence of sound line bending that is not considered, and take into account the influence of array element spacing and target azimuth on direction estimation, thereby improving the accuracy and reliability of direction estimation.

[0005] In a first aspect, the present invention provides a method for estimating the direction of a multi-element stereo hydrophone array, comprising:

[0006] Step 1: Obtain the time when each hydrophone in the multi-element stereo hydrophone array receives the acoustic signal, calculate the observation value of the signal received by two adjacent hydrophones, approximate the acoustic wave to a plane wave, and establish a relationship between the direction vector and the observation value;

[0007] Step 2: Based on the relationship in step 1, the unit matrix is ​​used as the observation value weight matrix, and the direction vector estimation is calculated according to the weighted least squares method;

[0008] Step 3: obtaining an observation value residual vector based on the direction vector estimation and the observation vector; wherein the observation vector represents a sequence of observation values ​​arranged in the order of hydrophone numbers in the multivariate stereo hydrophone array;

[0009] Step 4: Standardize the observed value residual vector using the median method to obtain a standardized residual vector;

[0010] Step 5: Calculate the equivalent weight of the observation value through the equivalent weight function based on the standardized residual vector to obtain an equivalent weight matrix;

[0011] Step 6: Use the equivalent weight matrix as the new observation value weight matrix and estimate the direction vector according to the least squares method; and calculate whether the iteration condition is met. If it is met, output the direction vector; if not, use the direction vector as the new direction vector estimate and repeat steps 3 to 6.

[0012] Furthermore, in step 1, the relationship is:

[0013]

[0014] Among them, δ i,j represents the observed value of the received signal of two adjacent hydrophones, i and j represent the hydrophone numbers in the hydrophone array, t i and t j represent the time when hydrophone i and j receive the acoustic signal, c represents the underwater sound speed, p i and p j They represent the position vectors of hydrophones i and j in the hydrophone array respectively, d represents the direction vector of the sound source, and N represents the number of array elements, that is, the number of stereo hydrophones.

[0015] Furthermore, in step 2, the direction vector estimation is calculated according to the weighted least squares method, which is calculated by formula (3):

[0016]

[0017] in, represents the direction vector estimation, δ=[δ 1,2 δ 2,3 … δ N-1,N ]T represents the observation vector, which is composed of all the observation values ​​in the multivariate stereo hydrophone array, P represents the observation value weight matrix, ||·|| represents the vector modulus, A represents the position coefficient matrix,

[0018]

[0019] Furthermore, in step 3, the observation residual vector is calculated by formula (4):

[0020]

[0021] in, represents the direction vector estimation, δ=[δ 1,2 δ 2,3 … δ N-1,N ] T represents the observation vector, v = [v1 v2 …v N-1 ] T represents the observation residual vector, A represents the location coefficient matrix,

[0022]

[0023] Furthermore, the step 4 specifically includes:

[0024] Step 401: Calculate the unit weighted mean error using the median method;

[0025] Step 402: Calculate a standardized residual vector using the unit weighted error and the observed value residual vector.

[0026] Furthermore, in step 401, the unit weighted mean error is calculated by formula (5):

[0027]

[0028] in, Represents the unit weight error, P i represents the i-th diagonal element of the observation weight matrix, v i represents the i-th observation residual of the observation residual vector, and med{·} represents the median.

[0029] Furthermore, in step 402, the standardized residual in the standardized residual vector is calculated by formula (6):

[0030]

[0031] in, represents the i-th standardized residual in the standardized residual vector, Denotes the unit weight error, v irepresents the residual of the ith observation in the observation residual vector.

[0032] Furthermore, in step 5, the equivalent weight of the observation value is calculated by the IGGⅢ equivalent weight function, and the calculation formula is as follows:

[0033]

[0034] in, represents the i-th standardized residual in the standardized residual vector, represents the equivalent weight, which is the i-th diagonal element of the equivalent weight matrix, k0 and k1 represent the manually set parameters, P i Represents the i-th element of the observation weight matrix.

[0035] Further, in step 6, the iteration condition is:

[0036]

[0037] Among them, max(·) means calculating the maximum value of the vector; |·| means taking the absolute value; ε means the manually set threshold; represents the direction vector calculated for the kth time, Represents the direction vector calculated for the k+1th time.

[0038] In a second aspect, an embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a direction estimation method for a multi-element stereo hydrophone array as described above is implemented.

[0039] Beneficial effects of the present invention:

[0040] The present invention approximates the sound wave to a plane wave and establishes a mathematical relationship between the arrival time difference TDOA and the direction vector, takes TDOA as the observation value, calculates the direction vector estimate according to the weighted least square method, then calculates the equivalent weight of the observation value according to the equivalent weight function, and then replaces the original observation value weight matrix with the equivalent weight matrix, and recalculates the direction vector according to the weighted least square method, iteratively calculates the equivalent weight and the direction vector until the difference between two consecutive direction vector estimates is less than a manually set threshold, and outputs the direction vector estimate as the direction of the multi-element stereo hydrophone array. The present invention adopts the idea of ​​weighted iteration in anti-error estimation, which can weaken the influence of the direction estimation function model not considering the sound line bending, and takes into account the influence of the array element spacing and the target azimuth on the direction estimation, thereby improving the accuracy and reliability of the direction estimation of the multi-element stereo hydrophone array. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1A schematic flow chart of a method for estimating the direction of a multi-element stereo hydrophone array provided in an embodiment of the present invention;

[0042] Figure 2 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] An embodiment of the present invention provides a method for estimating the direction of a multi-element stereo hydrophone array, comprising:

[0045] Step 1: Obtain the time when each hydrophone in the multi-element stereo hydrophone array receives the acoustic signal, and calculate the observation value of the received signal of two adjacent hydrophones.

[0046] Approximate the sound wave as a plane wave and establish the relationship between the direction vector and the observed value:

[0047]

[0048] Among them, δ i,j represents the observed value of the received signals of two adjacent hydrophones, that is, the arrival time difference TDOA; i and j represent the hydrophone numbers in the hydrophone array, t i and t j represent the time when hydrophone i and j receive the acoustic signal, c represents the underwater sound speed, p i and p j They represent the position vectors of hydrophones i and j in the hydrophone array respectively, d is a unit vector, representing the direction vector of the sound source, and N represents the number of array elements, that is, the number of stereo hydrophones.

[0049] Step 2: Based on the relationship in step 1, use the unit matrix as the observation value weight matrix and calculate the direction vector estimate according to the weighted least squares method.

[0050] Specifically, the position coefficient matrix composed of the position coefficient vector is calculated by equation (1):

[0051]

[0052] Where A represents the position coefficient matrix.

[0053] Compute an estimate of the direction vector using the weighted least squares method:

[0054]

[0055] in, represents the direction vector estimation, δ=[δ 1,2 δ 2,3 …δ N-1,N ] T represents the observation vector, which is composed of all the observation values ​​in the multivariate stereo hydrophone array, P represents the observation value weight matrix, ||·|| represents the modulus of the vector, and A represents the position coefficient matrix, which is composed of the position coefficient vector. It should be noted that the purpose of normalization in formula (3) is to prevent the modulus of the calculated direction vector from being equal to 1 due to numerical calculation errors.

[0056] Step 3: Obtain an observation value residual vector based on the direction vector estimation and the observation vector; wherein the observation vector represents a sequence of observation values ​​arranged in the order of the hydrophone numbers in the multivariate stereo hydrophone array.

[0057] Specifically, the estimated value of the observation is obtained by calculating the direction vector estimation and the position coefficient matrix, and the estimated value is added to the observation vector to obtain the residual vector of the observation value;

[0058] The observation residual vector is calculated by formula (4):

[0059]

[0060] Where v = [v1 v2 … v N-1 ] T represents the observation residual vector.

[0061] Step 4: Use the median method to standardize the observed value residual vector to obtain the standardized residual vector.

[0062] Step 401: Calculate the unit weighted mean error of the observation vector using the median method.

[0063] Specifically, the unit weighted mean error is calculated by formula (5)

[0064]

[0065] in, Represents the unit weight error, P i represents the i-th diagonal element of the observation weight matrix, v i represents the i-th observation residual of the observation residual vector, and med{·} represents the median.

[0066] Step 402: Calculate a standardized residual vector using the unit weighted error and the observed value residual vector.

[0067] Specifically, the standardized residual in the standardized residual vector is calculated by formula (6):

[0068]

[0069] in, represents the i-th standardized residual in the standardized residual vector, Denotes the unit weight error, v i represents the residual of the ith observation in the observation residual vector.

[0070] Step 5: Calculate the equivalent weight of the observation value based on the standardized residual vector through the equivalent weight function to obtain the equivalent weight matrix.

[0071] Specifically, the equivalent weight of the observation value is calculated by the IGGⅢ equivalent weight function, and the calculation formula is as follows:

[0072]

[0073] in, represents the i-th standardized residual in the standardized residual vector, represents the equivalent weight, which is the i-th diagonal element of the equivalent weight matrix, and k0 and k1 represent manually set parameters.

[0074] Step 6: Use the equivalent weight matrix as the new observation value weight matrix and estimate the direction vector according to the least squares method; and calculate whether the iteration condition is met. If it is met, output the direction vector; if not, use the direction vector as the new direction vector estimate and repeat steps 3 to 6.

[0075] Specifically, the equivalent weight matrix is ​​used as the new observation weight matrix (that is, ), and re-estimate the direction vector according to the least squares formula (3), and calculate whether the iteration condition is met. If it is met, the direction vector is output as the final estimated direction. If it is not met, the direction vector is used as the new direction vector estimation, and steps 3 to 6 are repeated until the iteration condition is met and the direction is output;

[0076] The iteration conditions are:

[0077]

[0078] Among them, max(·) is the maximum value of the calculated vector; |·| is the absolute value; ε>0 is the manually set threshold; the superscript is the iteration number, represents the direction vector calculated for the kth time, Represents the direction vector calculated for the k+1th time.

[0079] The embodiment of the present invention provides a new direction estimation method that can take into account the characteristics of sound line bending and receiving array structure. The method approximates the sound wave as a plane wave and establishes a mathematical relationship between the arrival time difference TDOA and the direction vector. The TDOA is used as the observation value, and the direction vector estimation is calculated according to the weighted least squares method. Then, the equivalent weight of the observation value is calculated according to the equivalent weight function, and then the original observation value weight matrix is ​​replaced by the equivalent weight matrix. The direction vector is recalculated according to the weighted least squares method, and the equivalent weight and direction vector are iteratively calculated until the difference between two consecutive direction vector estimations is less than a manually set threshold. The direction vector estimation is output as the direction of the multi-element stereo hydrophone array. The present invention adopts the idea of ​​weight selection iteration in anti-error estimation, which can weaken the influence of the direction estimation function model not considering the sound line bending, and takes into account the influence of the array element spacing and the target azimuth on the direction estimation, thereby improving the accuracy and reliability of the direction estimation of the multi-element stereo hydrophone array.

[0080] like Figure 2 As shown, an embodiment of the present invention further provides an electronic device, including: a processor (processor) 201, a communication interface (Communications Interface) 202, a memory (memory) 203 and a communication bus 204, wherein the processor 201, the communication interface 202, and the memory 203 communicate with each other through the communication bus 204. The processor 201 can call the logic instructions in the memory 203 to execute the method in the above embodiment, and the method includes:

[0081] Step 1: Obtain the time when each hydrophone in the multi-element stereo hydrophone array receives the acoustic signal, calculate the observed values ​​of the signals received by two adjacent hydrophones, approximate the acoustic wave to a plane wave, and establish a relationship between the direction vector and the observed value;

[0082] Step 2: Based on the relationship in step 1, the identity matrix is ​​used as the observation value weight matrix, and the direction vector estimation is calculated according to the weighted least squares method;

[0083] Step 3: Obtain an observation value residual vector based on the direction vector estimation and the observation vector; wherein the observation vector represents a sequence of observation values ​​arranged in the order of hydrophone numbers in the multivariate stereo hydrophone array;

[0084] Step 4: Use the median method to standardize the observed value residual vector to obtain the standardized residual vector;

[0085] Step 5: Calculate the equivalent weight of the observation value through the equivalent weight function based on the standardized residual vector to obtain the equivalent weight matrix;

[0086] Step 6: Use the equivalent weight matrix as the new observation value weight matrix and estimate the direction vector according to the least squares method; and calculate whether the iteration condition is met. If it is met, output the direction vector; if not, use the direction vector as the new direction vector estimate and repeat steps 3 to 6.

[0087] In addition, when the logic instructions in the above-mentioned memory 203 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for estimating the direction of a multi-element stereo hydrophone array, characterized in that: include: Step 1: Obtain the time when each hydrophone in the multi-element stereo hydrophone array receives the acoustic signal, calculate the observation value of the signal received by two adjacent hydrophones, approximate the acoustic wave to a plane wave, and establish a relationship between the direction vector and the observation value; Step 2: Based on the relationship in step 1, the unit matrix is ​​used as the observation value weight matrix, and the direction vector estimation is calculated according to the weighted least squares method; Step 3: obtaining an observation value residual vector based on the direction vector estimation and the observation vector; wherein the observation vector represents a sequence of observation values ​​arranged in the order of hydrophone numbers in the multivariate stereo hydrophone array; Step 4: Standardize the observed value residual vector using the median method to obtain a standardized residual vector; Step 5: Calculate the equivalent weight of the observation value through the equivalent weight function based on the standardized residual vector to obtain an equivalent weight matrix; Step 6: Use the equivalent weight matrix as the new observation value weight matrix and estimate the direction vector according to the least squares method; and calculate whether the iteration condition is met. If it is met, output the direction vector; if not, use the direction vector as the new direction vector estimate and repeat steps 3 to 6.

2. The method for estimating the direction of a multi-element stereo hydrophone array according to claim 1, characterized in that: In step 1, the relationship is: Among them, δ i,j represents the observed value of the received signal of two adjacent hydrophones, i and j represent the hydrophone numbers in the hydrophone array, t i and t j represent the time when hydrophone i and j receive the acoustic signal, c represents the underwater sound speed, p i and p j They represent the position vectors of hydrophones i and j in the hydrophone array respectively, d represents the direction vector of the sound source, and N represents the number of array elements, that is, the number of stereo hydrophones.

3. The method for estimating the direction of a multi-element stereo hydrophone array according to claim 2, characterized in that: In step 2, the direction vector estimate is calculated using the weighted least squares method, using formula (3): in, represents the direction vector estimation, δ=[δ 1,2 δ 2,3 …δ N-1,N ] T represents the observation vector, which is composed of all the observation values ​​in the multivariate stereo hydrophone array, P represents the observation value weight matrix, ||·|| represents the vector modulus, A represents the position coefficient matrix, 4. The method for estimating the direction of a multi-element stereo hydrophone array according to claim 2, characterized in that: In step 3, the observation residual vector is calculated by formula (4): in, represents the direction vector estimation, δ=[δ 1,2 δ 2,3 …δ N-1,N ] T represents the observation vector, v=[v1 v2 … v N-1 ] T represents the observation residual vector, A represents the location coefficient matrix, 5. The method for estimating the direction of a multi-element stereo hydrophone array according to claim 1, characterized in that: The step 4 specifically includes: Step 401: Calculate the unit weighted mean error using the median method; Step 402: Calculate a standardized residual vector using the unit weighted error and the observed value residual vector.

6. The method for estimating the direction of a multi-element stereo hydrophone array according to claim 5, characterized in that: In step 401, the unit weighted mean error is calculated by formula (5): in, Represents the unit weight error, P i represents the i-th diagonal element of the observation weight matrix, v i represents the i-th observation residual of the observation residual vector, and med{·} represents the median.

7. The method for estimating the direction of a multi-element stereo hydrophone array according to claim 5, characterized in that: In step 402, the standardized residual in the standardized residual vector is calculated by formula (6): in, represents the i-th standardized residual in the standardized residual vector, Denotes the unit weight error, v i represents the residual of the ith observation in the observation residual vector.

8. The method for estimating the direction of a multi-element stereo hydrophone array according to claim 1, characterized in that: In step 5, the equivalent weight of the observation value is calculated by the IGGⅢ equivalent weight function, and the calculation formula is as follows: in, represents the i-th standardized residual in the standardized residual vector, represents the equivalent weight, which is the i-th diagonal element of the equivalent weight matrix, k0 and k1 represent the manually set parameters, P i Represents the i-th element of the observation weight matrix.

9. The method for estimating the direction of a multi-element stereo hydrophone array according to claim 1, characterized in that: In step 6, the iteration condition is: Among them, max(·) means calculating the maximum value of the vector; |·| means taking the absolute value; ε means the manually set threshold; represents the direction vector calculated for the kth time, Represents the direction vector calculated for the k+1th time.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method according to any one of claims 1 to 9 is implemented.

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