An Optimization Method for the Layout of an Underwater Active Electric Field Detection Array and Related Devices

Abstract

An optimization method for the layout of an underwater active electric field detection array and related devices, comprising: generating a streamline curve to be arranged; arranging a transmitting electrode at each of the head and tail of the obtained streamline curve; determining a detection area according to an underwater typical target detection scenario, and discretizing the detection area into rectangular grids; based on the discretized grids, determining the minimum spacing of receiving electrodes and the number of receiving electrodes according to the actual installation size of the receiving electrodes, and establishing an objective function based on the average Cramer-Rao lower bound; performing iterative solution on the established objective function, and the obtained optimal individual corresponds to the optimal layout mode of the array. The array layout method proposed by the present invention has high calculation efficiency, and has higher positioning accuracy compared with the uniform arrangement of sensors under the condition of the same number of sensors, providing a design reference and theoretical basis for the layout optimization of underwater active electric field detection arrays.

Description

Technical Field

[0001] The present invention relates to the field of underwater detection, and particularly to an optimization method for the layout of an underwater active electric field detection array and related devices. Background Art

[0002] Weakly electric fish in nature can stimulate an underwater electric field through the electric organs at their tails, and then receive the distortion information of the surrounding electric field through the "ampullae of Lorenzini" to achieve the purpose of accurately perceiving targets. The "ampullae of Lorenzini" of weakly electric fish cover the surface of the fish body, and the number of electric field sensing cells is as many as thousands. The structure of the "ampullae of Lorenzini" of weakly electric fish is the result of natural selection. From the perspective of engineering practice, it is almost impossible to completely replicate the "ampullae of Lorenzini" of weakly electric fish. In existing active electric field detection research, the array structures are mostly in the forms of simple linear arrays, circular arrays, rectangular arrays, etc., and the elements are evenly arranged, lacking a theoretical basis for the selection of array layout methods and element spacing. Therefore, it is particularly important to study how to maximize the positioning accuracy of surrounding targets through the layout design of sensors under limited sensor conditions. Summary of the Invention

[0003] The purpose of the present invention is to provide an optimization method for the layout of an underwater active electric field detection array and related devices to solve the problems of low positioning accuracy of existing underwater active electric field detection arrays and lack of theoretical basis for the selection of array layout methods and element spacing.

[0004] To achieve the above purpose, the present invention adopts the following technical solutions:

[0005] An optimization method for the layout of an underwater active electric field detection array includes:

[0006] According to the actual size and dimensions of the detection array, determine the length parameter and shape parameter of the array, and generate a streamline curve for element layout according to the length parameter and shape parameter of the array;

[0007] Arrange a transmitting electrode at each of the head and tail of the obtained streamline curve, and apply alternating currents with the same magnitude and opposite directions to the two transmitting electrodes;

[0008] According to the underwater typical target detection scenario, determine the detection area, and discretize the detection area into rectangular grids. The discretized grids represent the possible positions where the target may appear;

[0009] Based on the discretized grids, determine the minimum spacing of the receiving electrodes and the number of receiving electrodes according to the actual installation size of the receiving electrodes, and establish an objective function based on the average Cramer-Rao lower bound with these as constraint conditions;

[0010] Iteratively solve the established objective function, and the optimal individual obtained by the solution corresponds to the optimal layout of the array.

[0011] Furthermore, a conformal mapping method is adopted to generate a streamline curve for array layout:

[0012] Conformal mapping method: For the complex plane C and a point ξ ∈ C, if the transformation satisfying the following formula is met, ξ is mapped from the complex plane C to the z plane;

[0013]

[0014] ξ = Re βi -λ, β ∈ [-π, π)

[0015] b = R - λ

[0016] In the formula, R defines the length of the streamlined body, and λ / R defines the shape of the streamlined body. Conformal mapping can map a circle to a symmetric streamlined body while ensuring that the angle remains unchanged after mapping.

[0017] Furthermore, the current frequency and magnitude are adjusted according to the size of the detection range.

[0018] Furthermore, the objective function is obtained by the following formula:

[0019]

[0020] In the formula, I -1 (r) is the inverse matrix of the Fisher information matrix I(r), R(r) is defined as the distance between the target and the center of the array; M is the number of discrete grids in the detection water area; Ω represents the array layout method, and Ψ represents the constraint conditions, that is, the number and minimum spacing of receiving electrodes;

[0021] Furthermore, the Fisher information matrix describes the information measure that can be obtained from the observed data. The calculation formula of the Fisher information matrix is as follows:

[0022]

[0023] In the formula, σ 2 is the variance of the noise signal, N represents the number of sampling points, and the parameter r to be estimated is defined as the position of the target r = [x y] T , s = [n; r] represents the change value of the signal on the receiving electrode at the nth sampling when the target position is r.

[0024] Furthermore, the grey wolf optimization algorithm is used to iteratively solve the established objective function:

[0025] The specific steps for the grey wolf optimization algorithm to solve the optimal value of the array layout objective function are as follows:

[0026] Initialize the grey wolf population and define the population size and the number of iterations.

[0027] Calculate the individual fitness of the grey wolf population according to the established objective function, and save the top 3 wolves with the smallest fitness values, namely, the α wolf, the β wolf, and the δ wolf.

[0028] The individual fitness value F(Ω) of the grey wolf population can be calculated according to the following formula:

[0029]

[0030] In the formula, f(Ω) is the established optimization objective function, and g j (Ω)≥0 represents all the constraint conditions, and f max represents the maximum value of the objective function among all individuals in the wolf pack that satisfy the constraint conditions.

[0031] Step 5.3: Update the positions of other search wolves ω, as well as the values of parameters a, A, and C, according to the wolf pack position update formula.

[0032] Step 5.4: Calculate the fitness of all individuals in the grey wolf population and replace the positions of the α wolf, the β wolf, and the δ wolf.

[0033] Step 5.5: Repeat the above steps until the global optimal solution is found or the preset number of iterations is reached, and select the optimal grey wolf individual as the optimal layout method of the array.

[0034] Furthermore, the wolf pack position update formula is calculated according to the following formula:

[0035]

[0036]

[0037]

[0038] In the formula, t is the current iteration number, X p (t) is the position vector of the prey, X(t) is the position vector of the search wolf, and A and C are coefficient vectors.

[0039] Furthermore, an underwater active electric field detection array layout optimization system includes:

[0040] A streamline curve acquisition module, which is used to determine the length parameter and shape parameter of the array according to the actual size and dimensions of the detection array, and generate a streamline curve for array layout according to the length parameter and shape parameter of the array.

[0041] A transmitting electrode arrangement module, which is used to arrange a transmitting electrode at each end of the obtained streamline curve, and an alternating current with the same magnitude and opposite direction is applied to the two transmitting electrodes.

[0042] A detection area determination module, configured to determine a detection area according to an underwater typical target detection scenario, discretize the detection area into rectangular grids, and the grids after discretization represent the possible positions where the target may appear;

[0043] An objective function establishment module, configured to determine the minimum spacing and the number of receiving electrodes based on the grids after discretization and according to the actual installation size of the receiving electrodes, and establish an objective function based on the average Cramer-Rao lower bound with this as a constraint condition;

[0044] A solution module, configured to perform iterative solution on the established objective function, and the optimal individual obtained by the solution corresponds to the optimal layout mode of the array.

[0045] Furthermore, a computer device includes 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 an underwater active electric field detection array layout optimization method are implemented.

[0046] Furthermore, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of an underwater active electric field detection array layout optimization method are implemented.

[0047] Compared with the prior art, the present invention has the following beneficial technical effects:

[0048] The underwater active electric field detection array layout optimization method of the present invention has the following advantages: (1) The conformal mapping method is used to design the streamline curve of the underwater vehicle (torpedo, robotic fish, etc.) to be arranged. Compared with the rotary body structure, the resistance it receives during movement can be reduced, thereby improving the propulsion efficiency; (2) By establishing the average Cramer-Rao lower bound as the optimization objective function, specific targets and positioning algorithms can be effectively avoided, and the optimization results have good universality; (3) The grey wolf optimization algorithm is used to solve the optimal value of the objective function. Compared with the traditional optimization algorithm, the grey wolf optimization algorithm has good global search ability and high calculation efficiency.

[0049] The underwater active electric field detection array layout optimization method of the present invention has smaller positioning error and higher positioning accuracy compared with the uniform arrangement of sensors when the number of sensors is the same, providing a design reference and theoretical basis for the layout optimization of the underwater active electric field detection array. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a flowchart of the underwater active electric field detection array layout optimization method described in an embodiment of the present invention;

[0051] Figure 2 is the streamline curve described in the embodiment of the present invention;

[0052] Figure 3 is the schematic diagram of the target detection scenario described in the embodiment of the present invention;

[0053] Figure 4 is the optimization iteration process curve described in the embodiment of the present invention;

[0054] Figure 5 is the optimization result of the detection array layout described in the embodiment of the present invention;

[0055] Figure 6 is a comparison of the positioning results of the optimized array and the uniform array under different positioning algorithms in the embodiment of the present invention; among them, Figure 6(a) is the positioning result of the MUSIC algorithm, Figure 6(b) is the positioning result of the MVDR algorithm, Figure 6(c) is the positioning result of the ML algorithm, and Figure 6(d) is the positioning result of the LS algorithm. Specific implementation manners

[0056] To make the purpose, advantages and technical solutions of the present invention more obvious, the technical solutions in the embodiments of the present invention will be described more completely and in detail below in conjunction with the attached drawings and tables in the embodiments of the present invention.

[0057] As Figure 1 shown, an underwater active electric field detection array layout optimization method provided in this embodiment includes the following steps:

[0058] S1: According to the actual size and dimensions of the detection array, determine the length parameter R and the shape parameter λ / R of the array, and generate a streamline curve for the array to be arranged by using the conformal mapping method according to the length parameter R and the shape parameter λ / R of the array;

[0059] The "conformal mapping" method can be described as follows: For the complex plane C and the point ξ ∈ C, if the transformation satisfying the following formula is satisfied, ξ can be mapped from the complex plane C to the z plane (physical plane).

[0060]

[0061] ξ = Re βi -λ, β ∈ [-π, π)

[0062] b = R - λ

[0063] In the formula, R defines the length of the streamline body, λ / R defines the shape of the streamline body, and the conformal mapping can map a circle to a symmetric streamline body while ensuring that the angle remains unchanged after mapping.

[0064] In this embodiment, the length parameter R of the array is 6, the shape parameter λ / R is 0.2, and the generated streamline curve is asFigure 2 as shown

[0065] S2: At both ends of the streamline curve obtained in step 1, arrange one emission electrode each, where the two emission electrodes are connected to alternating currents with the same magnitude and opposite directions, and the current frequency and magnitude are determined according to the detection range.

[0066] In this embodiment, the detection range is a two-dimensional space of 0.4m × 0.2m. The frequency of the current connected to the emitter is selected as 1000Hz, and the current magnitude is selected as 10A.

[0067] S3: According to the underwater typical target detection scenario, determine the detection area, and discretize the detection area into rectangular grids. The discretized grids represent the possible positions where the target may appear;

[0068] In this embodiment, the target is a metal ball with a diameter of 50mm, the detection range is a two-dimensional space of 0.4m × 0.2m, the discretized grid resolution is 0.01m × 0.01m, and the detection area is discretized into a grid area of 41×16. Each grid represents the possible position where the target may appear, as Figure 3 as shown

[0069] S4: According to the actual installation size of the receiving electrode, determine the minimum spacing of the receiving electrode and the number of receiving electrodes, and use this as a constraint condition to establish an objective function based on the average Cramer-Rao lower bound.

[0070] The objective function can be obtained by the following formula:

[0071]

[0072] In the formula, I -1 (r) is the inverse matrix of the Fisher information matrix I(r), and R(r) is defined as the distance between the target and the center of the array. M is the number of discrete grids in the detection water area. Ω represents the array layout method, and Ψ represents the constraint condition, that is, the number of receiving electrodes and the minimum spacing.

[0073] The Fisher information matrix describes the information measure that can be obtained from the observed data. The calculation formula of the Fisher information matrix is as follows:

[0074]

[0075] In the formula, σ 2 is the variance of the noise signal, N represents the number of sampling points, and the parameter r to be estimated is defined as the position of the target r = [x y] T , and s = [n; r] represents the change value of the signal on the receiving electrode at the nth sampling when the target position is r.

[0076] In this embodiment, the minimum installation spacing of the receiving electrodes is 10 mm, and the number of receiving electrodes is 4. This condition will be used as a constraint condition for the objective function of array optimization.

[0077] S5: Use the Grey Wolf Optimization Algorithm to iteratively solve the objective function established in Step 4. The optimal Grey Wolf individual obtained by the solution corresponds to the optimal layout of the array.

[0078] The specific steps for the Grey Wolf Optimization Algorithm to solve the optimal value of the objective function of the array layout are as follows:

[0079] Step 5.1: Initialize the Grey Wolf population and define the population size and the number of iterations.

[0080] Step 5.2: Calculate the individual fitness of the Grey Wolf population according to the objective function established in Step 4, and save the first three wolves with the smallest fitness values, namely, the α wolf, β wolf, and δ wolf.

[0081] The individual fitness value F(Ω) of the Grey Wolf population can be calculated according to the following formula:

[0082]

[0083] In the formula, f(Ω) is the optimization objective function established in Step 4, g j (Ω)≥0 represents all constraint conditions, and f max represents the maximum value of the objective function among all individuals in the wolf pack that satisfy the constraint conditions.

[0084] Step 5.3: Update the positions of the other search wolves ω, as well as the values of the parameters a, A, and C, according to the wolf pack position update formula.

[0085] The wolf pack position update formula can be calculated according to the following formula:

[0086]

[0087]

[0088]

[0089] In the formula, t is the current iteration number, X p (t) is the position vector of the prey (optimal solution), X(t) is the position vector of the search wolf, and A and C are coefficient vectors.

[0090] Step 5.4: Calculate the fitness of all individuals in the Grey Wolf population and replace the positions of the α wolf, β wolf, and δ wolf.

[0091] Step 5.5: Repeat Steps 5.2 - 5.4 until the global optimal solution is found or the preset number of iterations is reached. Select the optimal Grey Wolf individual as the optimal layout of the array.

[0092] In this embodiment, the number of wolves is 10, the number of iterations is 50, and the curve of the objective function value changing with the number of iterations is as follows: Figure 4 As shown. After the Grey Wolf optimization algorithm is iteratively solved, the optimal layout of the sensor array is obtained as follows Figure 5 shown.

[0093] Verification of algorithm effectiveness

[0094] To verify the effectiveness and advancement of the proposed underwater active electric field detection array layout optimization method, the positioning performance of the optimized array was compared with that of a uniform array (unoptimized) under different positioning algorithms. The comparison results are shown in Figure 6 and Table 1. It can be seen that although the positioning performance varies between different positioning algorithms, the optimized array achieves smaller positioning error and higher positioning accuracy compared to the uniformly arranged array under different positioning algorithms.

[0095] Table 1

[0096]

[0097] In yet another embodiment of the present invention, a system for optimizing the layout of an underwater active electric field detection array is provided, which can be used to implement the above-mentioned method for optimizing the layout of an underwater active electric field detection array. Specifically, the system includes:

[0098] A streamline curve acquisition module is used to determine the length parameters and shape parameters of the array according to the actual size and dimensions of the detection array, and to generate a streamline curve to be arranged according to the length parameters and shape parameters of the array;

[0099] An emitting electrode arrangement module is used to arrange an emitting electrode at the beginning and end of the obtained streamline curve, wherein the two emitting electrodes are connected to alternating currents of equal magnitude and opposite directions;

[0100] The detection area determination module is used to determine the detection area based on the typical underwater target detection scenario and discretize the detection area into rectangular grids. The discretized grids represent the possible locations of the target.

[0101] An objective function establishment module is used to determine the minimum spacing and number of receiving electrodes based on the discretized grid and the actual installation size of the receiving electrodes, and to establish an objective function based on the average Cramer-Rao lower bound using these as constraints;

[0102] The solution module is used to iteratively solve the established objective function, and the optimal individual obtained by the solution is the optimal layout mode of the corresponding array.

[0103] The division of modules in the embodiments of the present invention is illustrative, merely a logical function division. In actual implementation, there may be other division methods. Additionally, in each embodiment of the present invention, the functional modules can be integrated in one processor, can exist separately physically, or two or more modules can be integrated in one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules.

[0104] In another embodiment of the present invention, a computer device is provided. The computer device includes a processor and a memory. The memory is used to store a computer program. The computer program includes program instructions. The processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function; the processor described in the embodiments of the present invention can be used for the operation of an underwater active electric field detection array layout optimization method.

[0105] In another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a computer device and is used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and, of course, the extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, and the operating system of the terminal is stored in this storage space. Moreover, one or more instructions suitable for being loaded and executed by the processor are stored in this storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. One or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the method for optimizing the layout of an underwater active electric field detection array in the above embodiment.

[0106] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0107] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0108] These computer program instructions can also be stored in a computer-readable memory that can guide the computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device implements the functions in Figure 1 one process or multiple processes and / or blocksFigure 1 The functions specified in one or more boxes.

[0109] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the steps of the functions specified in one or more processes and / or boxes Figure 1 One or more processes and / or boxes Figure 1 The steps of the functions specified in one or more boxes.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific implementation manners of the present invention, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for optimizing the layout of an underwater active electric field detection array, characterized in that: include: According to the actual size and dimensions of the detection array, the length parameters and shape parameters of the array are determined, and the streamline curve to be arranged is generated according to the length parameters and shape parameters of the array; Arrange an emitting electrode at the beginning and end of the obtained streamline curve, wherein the two emitting electrodes are connected to alternating currents of the same magnitude and opposite directions; According to the typical underwater target detection scenario, the detection area is determined and discretized into rectangular grids. The discretized grids represent the possible locations of the target. Based on the discretized grid and the actual installation size of the receiving electrodes, the minimum spacing and number of receiving electrodes are determined, and the objective function based on the average Cramer-Rao lower bound is established based on these constraints. The established objective function is iteratively solved, and the optimal individual obtained is the optimal layout of the corresponding array; Use the conformal mapping method to generate the streamline curve to be deployed: Conformal mapping method: For a complex plane C and a point ξ∈C, if the following transformation is satisfied, then ξ is mapped from the complex plane C to the z plane; ξ=Re βi -λ,β∈[-π,π) b=R-λ Where R defines the length of the streamline, and λ / R defines the shape of the streamline. Conformal mapping can map a circle onto a symmetrical streamline while ensuring that the angle remains unchanged after mapping.

2. The method for optimizing the layout of an underwater active electric field detection array according to claim 1, characterized in that: The frequency and magnitude of the current are adjusted according to the size of the detection range.

3. The method for optimizing the layout of an underwater active electric field detection array according to claim 1, wherein: The objective function is obtained as follows: Where, I -1 (r) is the inverse matrix of the Fisher information matrix I(r), R(r) is defined as the distance between the target and the center of the array; M is the number of discrete grids in the detection water area; Ω represents the array layout, and Ψ represents the constraint condition, namely the number of receiving electrodes and the minimum spacing.

4. The method for optimizing the layout of an underwater active electric field detection array according to claim 3, wherein: The Fisher information matrix describes the information measure that can be obtained from the observed data. The calculation formula of the Fisher information matrix is as follows: Where, σ 2 is the variance of the noise signal, N is the number of sampling points, and the parameter to be estimated r is defined as the position of the target r = [xy] T , s = [n; r] represents the change value of the signal on the receiving electrode when the nth sampling and the target position is r.

5. The method for optimizing the layout of an underwater active electric field detection array according to claim 1, wherein: The established objective function is iteratively solved using the Grey Wolf optimization algorithm: The specific steps of the Gray Wolf Optimization Algorithm to solve the optimal value of the array layout objective function are as follows: Initialize the gray wolf population, define the population size and number of iterations; Calculate the individual fitness of the gray wolf population according to the established objective function, and save the top three wolves with the smallest fitness values: α wolf, β wolf, and δ wolf; The individual fitness value F(Ω) of the gray wolf population can be calculated according to the following formula: Where f(Ω) is the established optimization objective function, g j (Ω)≥0 represents all constraints, f max Represents the maximum value of the objective function among all individuals in the wolf pack that meet the constraints; Step 5.3: Update the positions of other search wolves ω and the values of parameters a, A, and C according to the wolf pack position update formula; Step 5.4: Calculate the fitness of all individuals in the gray wolf population and replace the positions of α wolf, β wolf and δ wolf; Step 5.5: Repeat the above steps until the global optimal solution is found or the preset number of iterations is met, and select the optimal gray wolf individual as the optimal layout of the array.

6. The method for optimizing the layout of an underwater active electric field detection array according to claim 5, characterized in that: The wolf pack position update formula is calculated as follows: Where t is the current iteration number, X p (t) is the position vector of the prey, X(t) is the position vector of the searching wolf, and A and C are coefficient vectors.

7. An underwater active electric field detection array layout optimization system, characterized in that: include: A streamline curve acquisition module is used to determine the length parameters and shape parameters of the array according to the actual size and dimensions of the detection array, and to generate a streamline curve to be arranged according to the length parameters and shape parameters of the array; An emitting electrode arrangement module is used to arrange an emitting electrode at the beginning and end of the obtained streamline curve, wherein the two emitting electrodes are connected to alternating currents of equal magnitude and opposite directions; The detection area determination module is used to determine the detection area based on the typical underwater target detection scenario and discretize the detection area into rectangular grids. The discretized grids represent the possible locations of the target. An objective function establishment module is used to determine the minimum spacing and number of receiving electrodes based on the discretized grid and the actual installation size of the receiving electrodes, and to establish an objective function based on the average Cramer-Rao lower bound using these as constraints; The solution module is used to iteratively solve the established objective function, and the optimal individual obtained by the solution is the optimal layout of the corresponding array; Use the conformal mapping method to generate the streamline curve to be deployed: Conformal mapping method: For a complex plane C and a point ξ∈C, if the following transformation is satisfied, then ξ is mapped from the complex plane C to the z plane; ξ=Re βi -λ,β∈[-π,π) b=R-λ Where R defines the length of the streamline, and λ / R defines the shape of the streamline. Conformal mapping can map a circle onto a symmetrical streamline while ensuring that the angle remains unchanged after mapping.

8. A computer 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 computer program, the steps of the underwater active electric field detection array layout optimization method as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for optimizing the layout of an underwater active electric field detection array as claimed in any one of claims 1 to 6 are implemented.

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