Joint estimation method and system for array shape correction and noise source positioning during towed line array rotation and calculation device

Abstract

The invention discloses a combined estimation method and system for array shape correction and noise source positioning during towed line array rotation, and a calculation device. The combined estimation method comprises the following steps: preliminarily estimating the positions of array elements of a towed line array; preliminarily positioning a sound source position; calculating the delay time of each array element relative to the first array element in the towed line array, and calculating a steering vector and an array manifold matrix; establishing a target cost function and a constraint condition to optimize and solve the correction of each array element in the towed line array; calculating the corrected array element position of the towed line array according to the array element position under the preliminarily estimated array shape and the correction amount of each array element of the towed line array; on the basis of a second-order polynomial fitting method, curve fitting is carried out on the positions of the array elements, and the positions of the array elements of the towed line array after curve fitting are obtained; and correcting the array flow pattern matrix based on the new array element position, and positioning the sound source position by using the minimum variance undistorted response algorithm again under the new array flow pattern.

Description

Technical Field

[0001] The present invention relates to the field of target positioning technology, and in particular to a method, system and computing device for jointly estimating formation correction and noise source positioning when a towed array rotates. The joint estimation method can realize formation correction and noise source joint estimation, and the noise source positioning accuracy is more accurate under the corrected formation, without generating virtual sources due to excessively high side lobes. Background Art

[0002] Towed linear array sonars (i.e., towed linear array sonars) offer excellent underwater detection performance and are relatively easy to operate. When finding targets, the array's formation is typically assumed to be a straight line. During application, users often need to maneuver the platform during various stages of target search, location, and tracking to achieve detection advantages, such as longer detection range, higher search rate, more accurate target location, and more advantageous evasive positions. These maneuvers inevitably affect the array's base formation, causing distortion and deviation from the assumed straight line. This mismatch between the actual array's base formation and the theoretical assumptions caused by platform maneuvers can severely impact the sonar's target detection capability and direction-finding accuracy, making it difficult for the towed array platform to maintain stable tracking and high-precision location of underwater targets, significantly reducing its effectiveness.

[0003] So far, the towed linear array formation estimation and calibration technology can be divided into the following categories: (1) Using non-acoustic sensor information to estimate the formation: Adding attitude sensors to the acoustic section of the towed linear array, using attitude information such as yaw, pitch and roll at different positions of the array, and estimating the array formation through polynomial fitting. The disadvantage of this method is that it requires very high measurement accuracy of the attitude sensor and requires a large data rate, which is currently difficult to meet actual engineering needs. (2) Mechanical modeling of the force state of the towed linear array, estimating the formation of the towed linear array by solving mechanical equations. This method requires real-time and accurate understanding of the force conditions of each section of the towed array, and the required amount of calculation is very large. At present, it is still difficult to achieve real-time prediction of the formation of the towed linear array during complex maneuvers of the ship. Only a few attempts have been made in the estimation of the towed body attitude. (3) The Paidoussis equation, an empirical equation for the forces acting on the cable array, is used to estimate the shape of the towed linear array. This method takes into account the forces acting on the cable array under the action of the seawater medium and solves the two-dimensional position transient distribution of the towed linear array by solving the motion control equation of the towed linear array. However, its drawback is that it requires accurate knowledge of the model constants in the Paidoussis equation under different motion states of the towed linear array, and the solution is complex. Therefore, it is currently difficult to achieve real-time and accurate shape estimation in actual engineering applications. It can be seen that the above three methods are relatively weak in operability and are not conducive to the shape estimation and calibration of the towed linear array. Summary of the Invention

[0004] To address the above technical issues, the present invention proposes a joint estimation method for formation correction and noise source positioning during towed array rotation. Based on the preliminary estimation of the towed array element positions using traditional dynamic methods, the method uses the output energy of the beamformer to more accurately estimate the towed array formation. This method does not rely on prior knowledge of the formation, can adapt to changes in the underwater acoustic environment, and can achieve joint estimation of formation correction and noise sources. The noise source positioning accuracy is more accurate under the corrected formation, and virtual sources are not generated due to excessively high sidelobes. The joint estimation method includes the following steps: S1, preliminarily estimate the position of the towed array elements based on the dynamic method; S2, preliminarily locates the sound source position based on the minimum variance distortion-free response focused beamforming algorithm; S3, calculating the delay time of each array element in the towed array relative to the first array element based on the estimated sound source position, and calculating the steering vector and array flow matrix; S4, based on the calculated array flow matrix, establishing a target cost function and constraint conditions to optimize and solve the correction amount of each array element in the towed array; S5, calculating the corrected positions of the elements of the towed array according to the preliminary estimated positions of the elements in the array and the correction values of the elements of the towed array; S6, performing curve fitting on each array element position based on a second-order polynomial fitting method to obtain the array element position of the towline array after curve fitting; In S7, the array flow matrix is modified based on the new array element positions, and the minimum variance distortionless response focused beamforming algorithm is used again to locate the sound source position under the new array flow pattern.

[0005] In step S1, the position of the array elements is preliminarily estimated according to the dynamic method. First, a group of motion control equations describing the real-time changes of the towed array must be established, and the boundary conditions for solving this group of motion control equations must be determined in combination with the characteristics of the towed array. The partial differential equations are discretized into a group of differential equations by differential analysis, and then the numerical solution is solved using the numerical calculation method to obtain the preliminary estimated position of the towed array during rotation. After the calculation, each array element The initial estimated coordinate vector on the axis is ; Each array element The initial estimated coordinate vector on the axis is .

[0006] In step S2, the sound source position is preliminarily located based on the minimum variance distortionless response focused beamforming algorithm, and the calculation formula is as follows: ,in, is the array steering vector; is the array covariance matrix; Indicates inversion. According to the peak value of the array spatial spectrum function, the estimated position of the sound source can be estimated ; 、 Respectively represent The sound source is axis, The two-dimensional coordinate values on the axis, The index representing the sound source; Represents the spatial spectrum.

[0007] In step S3, the delay time of each array element in the towed array relative to the first array element is calculated based on the estimated sound source position, and the steering vector and array flow matrix are calculated. Here, the delay time of each array element in the towed array relative to the first array element is calculated based on the estimated sound source position as follows: ,in 、 Respectively represent The sound source is axis, Two-dimensional coordinate values on the axis; Indicates the Element to The distance between the sound sources; represents the speed of sound; Indicates the reference element to the The distance between the sound sources. 、 Respectively represent Array elements in axis, Two-dimensional coordinate values on the axis; 、 Respectively represent the first array element in axis, The two-dimensional coordinate value on the axis, the first array element is used as the reference array element, and the calculation formula of the steering vector is: , where T represents the transpose and the angular frequency is , is the frequency of the noise source, Represents the total number of array elements. On this basis, calculate The array flow matrix of dimension is: , where each column of the array flow matrix corresponds to Steering vector of a sound source ; is the total number of incoherent sound sources.

[0008] In step S4, based on the calculated array flow matrix, a target cost function and constraint conditions are established to optimize the correction value of each element of the towed array. The target cost function The formula is: , The constraints are: , , , where the array flow matrix when the towed array rotates is ; for dimensional array flow matrix; 、 The position of the array element after formation correction and the position of the array element under the initial estimation formation are axis, Two-dimensional coordinate correction on the axis; 、 For the formation axis, When the array estimated shape is consistent with the actual shape, the array flow matrix Space and array receiving signal matrix The space is approximately parallel, represents the Euclidean norm, Indicates the index of the array element, Indicates the total number of array elements. Indicates the maximum value of the array element position correction, 、 Indicates the The correction amount of each array element.

[0009] In step S5, the corrected position of the towed array element is calculated based on the preliminary estimated position of the array element and the correction amount of each element of the towed array, wherein axis, The calculation formulas for the array element positions on the axis are: , ,in 、 The position of the array element after formation correction and the position of the array element under the initial estimation formation are axis, Two-dimensional coordinate correction on the axis; 、 For the formation axis, 2D coordinates on the axes; 、 is the position of the array element after formation correction.

[0010] In step S6, curve fitting is performed on each element position based on a second-order polynomial fitting method to obtain the element positions of the towline array after curve fitting. The solution formulas for the second-order coefficient, first-order coefficient, and constant term of the second-order polynomial are as follows: ,in For the first Array elements in The coordinates on the axis, is the position vector of the drag array The elements, For the first Array elements in The coordinates on the axis, is the position vector of the drag array The elements, is the total number of array elements in the towline array, Indicates the index of the array element.

[0011] In step S7, the array flow matrix is modified based on the new array element positions, and the minimum variance distortionless response focused beamforming algorithm is used again to locate the sound source position under the new array flow pattern. The calculation formula is: ,in is the modified array steering vector, which is a single column in the array flow matrix; is the array covariance matrix; Indicates inversion. According to the peak value of the array spatial spectrum function, the estimated position of the sound source can be estimated; Represents the spatial spectrum.

[0012] According to another aspect of the present invention, the present invention further provides a system for jointly estimating formation correction and noise source location during towed array rotation, for implementing formation correction and noise source joint estimation, wherein the joint estimation system comprises: A preliminary estimation unit, used for preliminarily estimating the position of the towed array element according to a dynamic method; A preliminary positioning unit, used for preliminarily locating the sound source position based on a minimum variance distortionless response focused beamforming algorithm; A first calculation unit is used to calculate the delay time of each array element in the towed array relative to the first array element according to the estimated sound source position, and calculate the steering vector and the array flow matrix; The second calculation unit is used to establish a target cost function and constraint conditions based on the calculated array flow matrix to optimize the correction amount of each array element in the towed array; A third calculation unit is used to calculate the corrected positions of the elements of the towed array according to the preliminary estimated positions of the elements in the array and the correction values of the elements of the towed array; A fitting unit is used to perform curve fitting on each array element position based on a second-order polynomial fitting method to obtain the array element position of the towline array after the curve fitting; The sound source localization unit is used to modify the array flow matrix based on the new array element position and to locate the sound source again using the minimum variance distortionless response focused beamforming algorithm under the new array flow pattern.

[0013] According to another aspect of the present invention, the present invention further provides a computing device comprising a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed in the processor, the processor executes a method for jointly estimating formation correction and noise source location during rotation of a towed array, wherein the joint estimation method comprises the following steps: S1, preliminarily estimate the position of the towed array elements based on the dynamic method; S2, preliminarily locates the sound source position based on the minimum variance distortion-free response focused beamforming algorithm; S3, calculating the delay time of each array element in the towed array relative to the first array element based on the estimated sound source position, and calculating the steering vector and array flow matrix; S4, based on the calculated array flow matrix, establishing a target cost function and constraint conditions to optimize and solve the correction amount of each array element in the towed array; S5, calculating the corrected positions of the elements of the towed array according to the preliminary estimated positions of the elements in the array and the correction values of the elements of the towed array; S6, performing curve fitting on each array element position based on a second-order polynomial fitting method to obtain the array element position of the towline array after curve fitting; In S7, the array flow matrix is modified based on the new array element positions, and the minimum variance distortionless response focused beamforming algorithm is used again to locate the sound source position under the new array flow pattern.

[0014] Compared with existing technologies, the present invention has at least the following advantages: the joint estimation method of the present invention enables formation correction and joint noise source estimation. Furthermore, the noise source positioning accuracy is more accurate under the corrected formation, and virtual sources are not generated due to excessively high sidelobes. Using the joint estimation method of the present invention, when the towed array is used as a range sensor for a towed platform, it can maintain high-precision positioning and stable tracking of underwater targets, enabling visualization of the underwater environment and satisfying the towed platform's search requirements for underwater targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is the processing flow of the method for jointly estimating the formation correction and noise source positioning when the towed array rotates according to the present invention.

[0016] Figure 2 These are the formation estimation and formation correction results during the rotation of the towed array of the present invention.

[0017] Figure 3 This is the minimum variance distortion-free response focused beamforming result based on the preliminary estimated array under a single sound source.

[0018] Figure 4This is the minimum variance distortion-free response focused beamforming result based on array correction under a single sound source.

[0019] Figure 5 This is the minimum variance distortion-free response focused beamforming result based on the preliminary estimated array under dual sound sources.

[0020] Figure 6 This is the minimum variance distortion-free response focused beamforming result based on array correction under dual sound sources.

[0021] Figure 7 This is a block diagram of the combined estimation system for array correction and noise source positioning during towed array rotation according to the present invention.

[0022] Figure 8 is a block diagram of a computing device of the present invention. DETAILED DESCRIPTION

[0023] Reference Attachment Figures 1 to 6 In the following description, a method for jointly estimating the formation correction and noise source positioning of a towed array during its rotation according to a preferred embodiment of the present invention will be disclosed and explained. In this method, the output energy of the beamformer is used to more accurately estimate the formation of the towed array based on the preliminary estimation of the position of the towed array elements by the traditional dynamic method. This method does not need to rely on prior knowledge of the formation, can adapt to changes in the underwater acoustic environment, and can realize joint estimation of the formation correction and noise source. In addition, the noise source positioning accuracy is more accurate under the corrected formation, and no virtual source is generated due to excessively high sidelobes.

[0024] Specifically, the joint estimation method of the present invention includes the following steps: S1, preliminarily estimating the position of the towed array element according to the dynamic method; S2, preliminarily locating the sound source position based on the minimum variance distortionless response focused beamforming algorithm; S3, calculating the delay time of each element in the towed array relative to the first element according to the estimated sound source position, and calculating the steering vector and the array flow matrix; S4, based on the calculated array flow matrix, establishing the target cost function and constraint conditions to optimize the correction amount of each element in the towed array; S5, calculating the corrected towed array element position based on the preliminary estimated array element position and the correction amount of each element of the towed array; S6, performing curve fitting on each element position based on the second-order polynomial fitting method to obtain the towed array element position after curve fitting; S7, correcting the array flow matrix based on the new element position, and again using the minimum variance distortionless response focused beamforming algorithm to locate the sound source position under the new array flow. Through the above steps, the joint estimation method of the present invention can use the output energy of the beamformer to more accurately estimate the towed array formation based on the preliminary estimation of the towed array elements using the traditional dynamic method, so as to realize formation correction and joint estimation of noise sources. The noise source positioning accuracy is more accurate under the corrected formation, and no virtual source is generated due to excessively high sidelobes.

[0025] More specifically, in step S1, the position of the array elements is preliminarily estimated according to the dynamic method. First, a group of motion control equations describing the real-time changes of the towed array is established, and the boundary conditions for solving the group of motion control equations are determined in combination with the characteristics of the towed array. Secondly, the partial differential equations are discretized into a group of differential equations through differential analysis, and then the numerical calculation method is used to solve the numerical solution to obtain the preliminary estimated position of the towed array during rotation. After the calculation, each array element The initial estimated coordinate vector on the axis is ; Each array element The initial estimated coordinate vector on the axis is .

[0026] In step S2, the sound source position is preliminarily located based on the minimum variance distortionless response focused beamforming algorithm, and the calculation formula is as follows: ,in, is the array steering vector, is the array covariance matrix, Indicates inversion. According to the peak value of the array spatial spectrum function, the estimated position of the sound source can be estimated , 、 Respectively represent The sound source is axis, The two-dimensional coordinate values on the axis, Indicates the index of the sound source, Represents the spatial spectrum. In the calculation formula Medium, superscript is the abbreviation of Hermitian, which means conjugate transpose, that is, Steering vector for array Perform transposition.

[0027] In step S3, the delay time of each array element in the towed array relative to the first array element is calculated based on the estimated sound source position, and the steering vector and array flow matrix are calculated. Here, the delay time of each array element in the towed array relative to the first array element is calculated based on the estimated sound source position as follows: ,in 、 Respectively represent The sound source is axis, Two-dimensional coordinate values on the axis; Indicates the Element to The distance between the sound sources, represents the speed of sound, Indicates the reference element to the The distance between the sound sources, 、 Respectively represent Array elements in axis, The two-dimensional coordinate values on the axis, 、 Respectively represent the first array element in axis, The two-dimensional coordinate value on the axis, the first array element is used as the reference array element; The calculation formula of the steering vector is: , where T represents the transpose and the angular frequency is , is the frequency of the noise source. Represents the total number of array elements. On this basis, calculate The calculation formula of the array flow matrix is: , where each column of the array flow matrix corresponds to Steering vector of a sound source ; is the total number of incoherent sound sources.

[0028] In step S4, based on the calculated array flow matrix, a target cost function and constraint conditions are established to optimize the correction value of each element of the towed array. The target cost function is The formula is: , the constraints are: , , , where the array flow matrix when the towed array rotates is , for dimensional array flow matrix; 、 The position of the array element after formation correction and the position of the array element under the initial estimation formation are axis, The two-dimensional coordinate correction on the axis, 、 For the formation axis, The two-dimensional coordinates on the axis, when the array estimated formation is consistent with the actual formation, the array flow matrix Space and array receiving signal matrix The space is approximately parallel, represents the Euclidean norm, Indicates the index of the array element, Represents the total number of array elements, Indicates the maximum value of the array element position correction, 、 Indicates the The correction amount of each array element. express right The partial derivative of express right The partial derivative of .

[0029] In step S5, the corrected position of the towed array element is calculated based on the preliminary estimated array element position and the correction value of each element of the towed array, wherein axis, The calculation formulas for the array element positions on the axis are: , ,in 、 The position of the array element after formation correction and the position of the array element under the initial estimation formation are axis, The two-dimensional coordinate correction on the axis, 、 For the formation axis, The two-dimensional coordinates on the axis, 、 is the position of the array element after formation correction.

[0030] In step S6, curve fitting is performed on each array element position based on a second-order polynomial fitting method to obtain the array element position of the towline array after curve fitting. The solution formulas for the second-order coefficient, first-order coefficient, and constant term of the second-order polynomial are as follows: ,in For the first Array elements in The coordinates on the axis, is the position vector of the drag array The elements, For the first Array elements in The coordinates on the axis, is the position vector of the drag array The elements, is the total number of array elements in the towline array, Indicates the index of the array element.

[0031] In step S7, the array flow matrix is modified based on the new array element positions, and the minimum variance distortionless response algorithm is used again to locate the sound source position under the new array flow pattern. The calculation formula is: ,in, is the modified array steering vector, which is a separate column in the array flow matrix. is the array covariance matrix, Indicates the inversion. According to the peak value of the array spatial spectrum function, the estimated position of the sound source can be estimated. Represents the spatial spectrum.

[0032] A simulation experiment of joint estimation of array element position correction and noise source location during the rotation of the towed array was carried out to verify the feasibility of the joint estimation method of the present invention. Specifically, the diameter of the towed array is 0.066m, the density is 3.5kg / m, the normal drag coefficient is 1.8, and the Young's modulus is The towed array has 64 elements, an array spacing of 0.75m, and a seawater sound speed of 1500m / s. Based on dynamic methods, the formation of the towed array during rotation can be estimated, i.e., a preliminary formation estimate. Figure 2 The solid line is the actual formation, the dashed line is the preliminary estimated formation, and the dotted line is the corrected formation obtained based on the joint estimation method of the present invention. Figure 1 It can be seen that compared with the initial estimated formation, the position deviation between the corrected formation and the actual formation is smaller.

[0033] Assuming a single sound source, the two-dimensional coordinate position of the sound source is (10, 50), the center frequency of the sound source is 1kHz, the array receiving signal-to-noise ratio is 10dB, and the background noise is Gaussian noise, the minimum variance distortion-free response focused beamforming results under the preliminary estimated formation and the corrected formation are calculated respectively, as shown below: Figure 3 and Figure 4As shown. The preliminary estimation results of the sound source localization based on the near-field minimum variance distortion-free response under the formation are (10,50) and (11,46). Due to the mismatch of the formation, the near-field Figure 3 The minimum variance distortion-free response focused beam sidelobes are too high, resulting in a virtual source with a two-dimensional coordinate of (11,46). After the array is corrected Figure 4 The sound source localization result based on the near-field minimum variance distortion-free response is (10,50), and the positioning error is 0m, which successfully avoids the generation of virtual sources. Figure 4 It can be seen that compared with the preliminary estimated formation, the noise source localization result based on the corrected formation does not have any virtual sources and has higher positioning accuracy.

[0034] Assuming that the noise source positions are (10, 50) and (32, 46) under incoherent dual sound sources, the center frequency of the sound source is 1kHz, the array receiving signal-to-noise ratio is 15dB, and other parameters remain unchanged, the minimum variance distortion-free response focused beamforming results under the preliminary estimated array and the corrected array are calculated respectively, as shown in the figure below: Figure 5 and Figure 6 As shown. Under the preliminary estimated formation, Figure 5 The sound source localization results based on the near-field minimum variance undistorted response are (10,55) and (32,44), with a positioning error of 5m. After formation correction, Figure 6 The sound source localization results based on the near-field minimum variance distortion-free response are (10,50), (32,46), and the positioning error is 0m. Figure 5 and Figure 6 It can be seen that compared with the results after the preliminary estimation of the formation, the dual noise source positioning accuracy based on the corrected formation is higher.

[0035] According to another aspect of the present invention, referring to the attached Figure 7The present invention further provides a system 700 for joint estimation of formation correction and noise source positioning during the rotation of a towed array, which is used to realize formation correction and noise source joint estimation, wherein the joint estimation system 700 includes a preliminary estimation unit 710, a preliminary positioning unit 720, a first calculation unit 730, a second calculation unit 740, a third calculation unit 750, a fitting unit 760 and a sound source positioning unit 770, wherein the preliminary estimation unit 710, the preliminary positioning unit 720, the first calculation unit 730, the second calculation unit 740, the third calculation unit 750, the fitting unit 760 and the sound source positioning unit 770. The second calculation unit 740, the third calculation unit 750, the fitting unit 760 and the sound source localization unit 770 cooperate with each other to enable the joint estimation system 700 to more accurately estimate the towed array formation based on the preliminary estimation of the towed array element positions by traditional dynamic methods using the output energy of the beamformer. This eliminates the need to rely on prior knowledge of the formation, adapts to changes in the underwater acoustic environment, and realizes formation correction and joint noise source estimation. In addition, the noise source localization accuracy is more accurate under the corrected formation, and virtual sources are not generated due to excessively high sidelobes.

[0036] Specifically, the preliminary estimation unit 710 is used to preliminarily estimate the position of the towed array element according to the dynamic method. More specifically, according to the dynamic method, the preliminary estimation unit 710 first establishes a group of motion control equations that describe the real-time changes in the towed array shape, and determines the boundary conditions for solving this group of motion control equations in combination with the characteristics of the towed array. Then, the partial differential equations are discretized into a group of differential equations through differential analysis, and then a numerical calculation method is used to solve the numerical solution to obtain the preliminary estimated position of the towed array during rotation. After calculation, each element The initial estimated coordinate vector on the axis is ; Each array element The initial estimated coordinate vector on the axis is .

[0037] The preliminary positioning unit 720 is used to preliminarily locate the sound source position based on the minimum variance distortionless response focused beamforming algorithm, and its calculation formula is as follows: ,in, is the array steering vector, is the array covariance matrix, Indicates inversion. According to the peak value of the array spatial spectrum function, the estimated position of the sound source can be estimated , 、 Respectively represent The sound source is axis, The two-dimensional coordinate values on the axis, Indicates the index of the sound source, Represents the spatial spectrum.

[0038] The first calculation unit 730 is used to calculate the delay time of each array element in the towed array relative to the first array element according to the estimated sound source position, and calculate the steering vector and the array flow matrix, wherein the estimated sound source position here calculates the delay time of each array element in the towed array relative to the first array element as follows: ,in 、 Respectively represent The sound source is axis, Two-dimensional coordinate values on the axis; Indicates the Element to The distance between the sound sources, represents the speed of sound, Indicates the reference element to the The distance between the sound sources, 、 Respectively represent Array elements in axis, The two-dimensional coordinate values on the axis, 、 Respectively represent the first array element in axis, The two-dimensional coordinate value on the axis, the first array element is used as the reference array element; the calculation formula of the steering vector is , where T represents the transpose and the angular frequency is , is the frequency of the noise source. Represents the total number of array elements. On this basis, calculate The calculation formula of the array flow matrix is , where each column of the array flow matrix corresponds to Steering vector of a sound source ; is the total number of incoherent sound sources.

[0039] The second calculation unit 740 is used to establish a target cost function and constraint conditions based on the calculated array flow matrix to optimize the correction amount of each array element in the towed array. The target cost function is The formula is The constraints are , , , where the array flow matrix when the towed array rotates is , for dimensional array flow matrix; 、 The position of the array element after formation correction and the position of the array element under the initial estimation formation are axis, The two-dimensional coordinate correction on the axis, 、 For the formation axis, The two-dimensional coordinates on the axis, when the array estimated formation is consistent with the actual formation, the array flow matrix Space and array receiving signal matrix The space is approximately parallel, represents the Euclidean norm, Indicates the index of the array element, Represents the total number of array elements, Indicates the maximum value of the array element position correction, 、 Indicates the The correction amount of each array element.

[0040] The third calculation unit 750 is used to calculate the corrected position of the towed array element according to the initial estimated array element position and the correction value of each array element of the towed array, wherein axis, The calculation formulas for the array element positions on the axis are , ,in 、 The position of the array element after formation correction and the position of the array element under the initial estimation formation are axis, The two-dimensional coordinate correction on the axis, 、 For the formation axis, The two-dimensional coordinates on the axis, 、 is the position of the array element after formation correction.

[0041] The fitting unit 760 is used to perform curve fitting on each array element position based on the second-order polynomial fitting method to obtain the array element position of the towline array after curve fitting. The solution formula for the second-order coefficient, first-order coefficient, and constant term of the second-order polynomial is as follows: ,in For the first Array elements in The coordinates on the axis, is the position vector of the drag array The elements, For the first Array elements in The coordinates on the axis, is the position vector of the drag array The elements, is the total number of array elements in the towline array, Indicates the index of the array element.

[0042] The sound source localization unit 770 is used to modify the array flow matrix based on the new array element position, and to locate the sound source position again using the minimum variance distortionless response focused beamforming algorithm under the new array flow pattern. The calculation formula is: ,in is the modified array steering vector, which is a separate column in the array flow matrix. is the array covariance matrix, Indicates the inversion. According to the peak value of the array spatial spectrum function, the estimated position of the sound source can be estimated. Represents the spatial spectrum.

[0043] Reference Attachment Figure 8 According to another aspect of the present invention, the present invention further provides a computing device 800, wherein the computing device 800 includes a processor 810 and a memory 820, wherein computer program instructions are stored in the memory 820, and when the computer program instructions are executed in the processor 810, the processor 810 executes a joint estimation method for array correction and noise source positioning when the towed array rotates, wherein the joint estimation method includes the following steps: preliminarily estimating the position of the towed array element according to a dynamic method; preliminarily locating the sound source position based on a minimum variance distortionless response focused beamforming algorithm; calculating the delay time of each element in the towed array relative to the first element according to the estimated sound source position, and calculating the steering vector and the array flow matrix; establishing a target cost function and constraint conditions based on the calculated array flow matrix to optimize the towed array. The invention relates to a method for calculating the correction amount of each element in the array; calculating the corrected element positions of the towed array based on the element positions under the preliminary estimation of the array shape and the correction amount of each element of the towed array; performing curve fitting on each element position based on a second-order polynomial fitting method to obtain the element positions of the towed array after the curve fitting; correcting the array flow pattern matrix based on the new element positions, and again using the minimum variance distortionless response focusing beamforming algorithm to locate the sound source position under the new array flow pattern. In this way, the computing device 800 can use the output energy of the beamformer to more accurately estimate the towed array shape based on the preliminary estimation of the element positions of the towed array by the traditional dynamic method, thereby eliminating the need to rely on prior knowledge of the array shape, adapting to changes in the underwater acoustic environment, and realizing joint estimation of the array shape correction and noise source. In addition, the noise source positioning accuracy is more accurate under the corrected array shape, and no virtual source is generated due to excessively high sidelobes.

[0044] In one embodiment of the computing device 800 of the present invention, the memory 820 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 810 may execute the program instructions to implement the functions of the joint estimation method of the present invention described above.

[0045] In one embodiment of the computing device 800 of the present invention, the processor 810 can be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, which can run the program instructions stored on the computer-readable storage medium to implement the functions of the joint estimation method of the present invention described above.

[0046] In one embodiment of the computing device 800 of the present invention, the computing device 800 may further include an input device 830 and an output device 840. The input device 830 may be, but is not limited to, a keyboard or a mouse; the output device 840 may be, but is not limited to, a display, a speaker, or a printer. The input device 830 and the output device 840 may be connected to the processor 820 via a bus system.

[0047] Those skilled in the art will appreciate that the embodiments of the present invention described above and shown in the accompanying drawings are intended to be illustrative only and are not intended to limit the present invention. The objectives of the present invention have been fully and effectively achieved. The functional and structural principles of the present invention have been demonstrated and illustrated in the embodiments. Any variations or modifications may be made to the embodiments of the present invention without departing from the principles described.

Claims

1. A method for joint estimation of formation correction and noise source positioning during the rotation of a towed array, which is used to achieve formation correction and noise source joint estimation, is characterized by: The joint estimation method comprises the following steps: S1, preliminarily estimate the position of the towed array elements based on the dynamic method; S2, preliminarily locates the sound source position based on the minimum variance distortion-free response focused beamforming algorithm; S3, calculating the delay time of each array element in the towed array relative to the first array element based on the estimated sound source position, and calculating the steering vector and array flow matrix; S4, based on the calculated array flow matrix, establish the target cost function and constraint conditions to optimize the correction amount of each array element in the towed array; S5, calculating the corrected positions of the elements of the towed array according to the preliminary estimated positions of the elements in the array and the correction values of the elements of the towed array; S6, performing curve fitting on each array element position based on a second-order polynomial fitting method to obtain the array element position of the towline array after curve fitting; In S7, the array flow matrix is modified based on the new array element positions, and the minimum variance distortionless response focused beamforming algorithm is used again to locate the sound source position under the new array flow pattern.

2. The method for joint estimation of formation correction and noise source location during towed array rotation according to claim 1 is characterized in that: In step S1, first, a set of motion control equations describing the real-time changes in the towed array's formation is established, and boundary conditions for solving the set of motion control equations are determined in combination with the characteristics of the towed array's use; second, the set of partial differential equations is discretized into a set of difference equations through difference analysis; Then, the numerical solution is solved by numerical calculation method to obtain the preliminary estimated position of the towed array in the rotation. After calculation, each array element The initial estimated coordinate vector on the axis is , each array element The initial estimated coordinate vector on the axis is .

3. The method for joint estimation of formation correction and noise source location during towed array rotation according to claim 1, characterized in that: In step S2, the calculation formula for preliminarily locating the sound source position based on the minimum variance distortionless response focused beamforming algorithm is as follows: ,in is the array steering vector, is the array covariance matrix, Indicates the inverse, Represents the spatial spectrum. According to the peak value of the array spatial spectrum function, the estimated position of the sound source can be estimated ,in 、 Respectively represent The sound source is axis, The two-dimensional coordinate values on the axis.

4. The method for joint estimation of formation correction and noise source location during towed array rotation according to claim 1, characterized in that: In step S3, the delay time of each array element in the towed array relative to the first array element is calculated based on the estimated sound source position: ,in Indicates the Element to The distance between the sound sources, Indicates the reference element to the The distance between the sound sources, represents the speed of sound, 、 Respectively represent The sound source is axis, The two-dimensional coordinate values on the axis, 、 Respectively represent Array elements in axis, The two-dimensional coordinate values on the axis, Indicates the index of the sound source, 、 Respectively represent the first array element in axis, The two-dimensional coordinate value on the axis, the first array element is used as the reference array element; The calculation formula of the steering vector is: , where T represents the transpose and the angular frequency is , is the frequency of the noise source, Represents the total number of array elements. On this basis, calculate The formula for the manifold matrix of a dimensional array is: , where each column of the array flow matrix corresponds to Steering vector of a sound source , is the total number of incoherent sound sources.

5. The method for joint estimation of formation correction and noise source location during towed array rotation according to claim 1, characterized in that: In step S4, based on the calculated array flow matrix, a target cost function and constraint conditions are established to optimize the correction value of each element of the towed array. The target cost function is The formula is: , The constraints are: , , , where the array flow matrix when the towed array rotates is , for dimensional array manifold matrix, 、 The position of the array element after formation correction and the position of the array element under the initial estimation formation are axis, The two-dimensional coordinate correction on the axis, 、 For the formation axis, The two-dimensional coordinates on the axis, when the array estimated formation is consistent with the actual formation, the array flow matrix Space and array receiving signal matrix The space is approximately parallel, represents the Euclidean norm, Indicates the index of the array element, Represents the total number of array elements, Indicates the maximum value of the array element position correction, 、 Indicates the The correction amount of each array element.

6. The method for joint estimation of formation correction and noise source location during towed array rotation according to claim 1, characterized in that: In step S5, the corrected position of the towed array element is calculated based on the preliminary estimated array element position and the correction value of each element of the towed array, wherein axis, The calculation formulas for the array element positions on the axis are: , ,in 、 The position of the array element after formation correction and the position of the array element under the initial estimation formation are axis, The two-dimensional coordinate correction on the axis, 、 For the formation axis, The two-dimensional coordinates on the axis, 、 is the position of the array element after formation correction.

7. The method for joint estimation of formation correction and noise source location during towed array rotation according to claim 1, characterized in that: In step S6, curve fitting is performed on each array element position based on a second-order polynomial fitting method to obtain the array element position of the towline array after curve fitting. The solution formulas for the second-order coefficient, first-order coefficient, and constant term of the second-order polynomial are as follows: ,in For the first Array elements in The coordinates on the axis, is the position vector of the drag array The elements, For the first Array elements in The coordinates on the axis, is the position vector of the drag array The elements, is the total number of array elements in the towline array, Indicates the index of the array element.

8. The method for joint estimation of formation correction and noise source location during towed array rotation according to claim 1, characterized in that: In step S7, the array flow matrix is modified based on the new array element positions, and the minimum variance distortionless response focused beamforming algorithm is again used under the new array flow pattern to locate the sound source position. The calculation formula is: ,in is the modified array steering vector, which is a separate column in the array flow matrix. is the array covariance matrix, Indicates the inversion. According to the peak value of the array spatial spectrum function, the estimated position of the sound source can be estimated. Represents the spatial spectrum.

9. A system for joint estimation of formation correction and noise source positioning during the rotation of a towed array, used to achieve formation correction and noise source joint estimation, characterized by: include: A preliminary estimation unit, used for preliminarily estimating the position of the towed array element according to a dynamic method; A preliminary positioning unit, used for preliminarily locating the sound source position based on a minimum variance distortionless response focused beamforming algorithm; A first calculation unit is used to calculate the delay time of each array element in the towed array relative to the first array element according to the estimated sound source position, and calculate the steering vector and the array flow matrix; The second calculation unit is used to establish a target cost function and constraint conditions based on the calculated array flow matrix to optimize the correction amount of each array element in the towed array; A third calculation unit is used to calculate the corrected positions of the elements of the towed array according to the preliminary estimated positions of the elements in the array and the correction values of the elements of the towed array; A fitting unit is used to perform curve fitting on each array element position based on a second-order polynomial fitting method to obtain the array element position of the towline array after the curve fitting; The sound source localization unit is used to modify the array flow matrix based on the new array element position and to locate the sound source again using the minimum variance distortionless response focused beamforming algorithm under the new array flow pattern.

10. A computing device, characterized in that The method comprises a processor and a memory, wherein computer program instructions are stored in the memory, and when the computer program instructions are executed in the processor, the processor is enabled to perform the joint estimation method according to any one of claims 1 to 8.

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