Horizontal line array direction finding error correction method, system, device and medium

Abstract

This invention discloses a method, system, device, and readable medium for correcting the direction finding error of a horizontal linear array. It includes three steps: constructing a priori mapping curve, dynamically querying the elevation angle, and inversely compensating for the observation azimuth angle. By pre-constructing a priori empirical curve showing the variation of the lower limit of the non-direct wave elevation angle with the detection distance, the estimated lower limit of the elevation angle is obtained by querying the prior empirical curve based on the current detection distance. Inverse compensation is then performed on the observation azimuth angle output by conventional beamforming. This solves the systematic direction finding projection deviation problem caused by multipath acoustic rays at large elevation angles in horizontal linear arrays under deep-sea thermocline detection conditions, achieving the technical effect of improving the passive direction finding accuracy of the linear array.

Description

Technical Field

[0001] This invention relates to the field of underwater acoustic array signal processing technology, and in particular to a method, system, device, and medium for correcting the direction finding error of a horizontal linear array. Background Technology

[0002] Passive sonar detection of underwater targets is a key technology in the field of underwater acoustics. Among various underwater acoustic devices, horizontal linear arrays are widely used in shipborne and unmanned underwater vehicle platforms due to their simple engineering implementation and stable spatial gain. Conventional beamforming of a horizontal linear array involves weighted compensation and summation of the received signals from the array elements to enhance the signal from a sound source in a specific direction. Assuming a uniform horizontal linear array is arranged on the horizontal axis of a three-dimensional Cartesian coordinate system, when a far-field plane wave is incident on the array at a horizontal azimuth angle, the array compensates for the spatial phase difference between adjacent elements, forming a directional beam in the corresponding direction to estimate the target's azimuth.

[0003] In actual deep-sea exploration, sound waves are affected by non-uniform sound velocity profiles and the sea surface and seabed boundaries. Sound signals radiated from the target often undergo multiple reflections from the sea surface and seabed, arriving at the receiving array sequentially via multipath propagation. For horizontal linear arrays lacking vertical spatial resolution, this multipath effect introduces direction-finding errors. When sound rays are incident on the array at a non-zero elevation angle, the array's spatial steering vector can only resolve the horizontal projection of the incident signal. This projection of the three-dimensional incident wave onto a one-dimensional horizontal plane causes a deviation in the observed azimuth angle. Specifically, a non-zero elevation angle makes the cosine of the observed azimuth angle equal to the product of the true azimuth cosine and the elevation cosine. When the elevation angle is non-zero, the observed azimuth angle will systematically shift towards the transverse direction of the linear array. The amount of this shift increases dramatically with the degree to which the target deviates from the transverse direction and with the increase of the elevation angle. In the context of deep-sea thermocline exploration, when both the exploration platform and the target are located in the negative gradient region of the thermocline and the exploration distance exceeds the distance where the direct wave exists, the formation of the beam dominated by non-direct multipath acoustic rays at large elevation angles results in a system direction finding error of several degrees or even more than ten degrees for the linear array, which restricts the direction finding performance of the linear array.

[0004] To address the direction-finding error of linear arrays caused by multipath acoustic ray elevation angles, existing research largely focuses on shallow-sea acoustic environments, with few studies exploring the impact of multipath elevation angle variations on direction-finding accuracy in deep-sea acoustic environments. Existing technologies suffer from the following shortcomings: First, there is a lack of systematic research on the spatial variation of multipath elevation angles with detection distance in deep-sea environments, failing to provide effective prior information for direction-finding error correction. Second, there is a lack of methods for inversely compensating for horizontal linear array direction-finding errors using the evolution of deep-sea acoustic fields, resulting in the direction-finding accuracy of linear arrays in deep-sea thermocline conditions being limited by elevation angle projection deviations and unable to be improved. Third, existing research lacks sufficient analysis of the spatial evolution of multipath elevation angles under different transmission and reception depth configurations, and the depth applicability of existing error correction methods lacks theoretical support. These shortcomings lead to low passive direction-finding accuracy of horizontal linear arrays in complex deep-sea acoustic environments, affecting the positioning and tracking performance of underwater targets. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a method, system, device and readable medium for correcting the direction finding error of a horizontal linear array, so as to solve the problem of systematic direction finding projection deviation caused by multipath sound rays at large elevation angles of the horizontal linear array under the situation of deep-sea thermocline detection.

[0006] Technical solution: In a first aspect, embodiments of this application provide a method for correcting the direction-finding error of a horizontal linear array, comprising the following steps:

[0007] Constructing a priori mapping curve: Using a ray acoustic model, multipath sound field simulation of the deep-sea environment is performed, and discrete data points of the lower limit of the non-direct wave elevation angle as a function of the detection distance are extracted. A nonlinear smooth fitting is performed on the discrete data points using a conformal piecewise cubic interpolation algorithm to generate a priori empirical curve of the lower limit of the non-direct wave elevation angle as a function of the detection distance.

[0008] Pitch angle dynamic query: Obtain the current detection distance, query the prior experience curve based on the current detection distance, and obtain the estimated lower limit of the pitch angle of the dominant sound ray at the corresponding detection distance;

[0009] Inverse compensation of observation azimuth angle: The observation azimuth angle output by conventional beamforming is inversely compensated using the estimated lower limit of elevation angle to obtain a corrected azimuth angle estimate. The inverse compensation calculation process is as follows: the cosine value of the observation azimuth angle is divided by the cosine value of the estimated lower limit of elevation angle, and the inverse cosine of the quotient is taken.

[0010] Secondly, embodiments of this application provide a horizontal linear array direction-finding error correction system, the system comprising:

[0011] The prior mapping curve construction module is used to simulate the multipath sound field of the deep-sea environment using the ray acoustic model, extract discrete data points of the lower limit of the non-direct wave elevation angle as a function of the detection distance, and use the conformal piecewise cubic interpolation algorithm to perform nonlinear smooth fitting on the discrete data points to generate a prior empirical curve of the lower limit of the non-direct wave elevation angle as a function of the detection distance.

[0012] The pitch angle dynamic query module is used to obtain the current detection distance, query the prior experience curve based on the current detection distance, and obtain the estimated lower limit value of the pitch angle of the dominant sound ray at the corresponding detection distance;

[0013] The observation azimuth angle inverse compensation module is used to inversely compensate the observation azimuth angle output by conventional beamforming using the estimated lower limit value of the elevation angle, so as to obtain the corrected azimuth angle estimate.

[0014] Thirdly, embodiments of this application provide an electronic device, including:

[0015] At least one processor;

[0016] and a memory communicatively connected to the at least one processor;

[0017] The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the horizontal linear array direction finding error correction method according to any one of claims 1 to 7.

[0018] Fourthly, embodiments of this application provide a computer program product, including a computer program, wherein when the computer program is executed by a processor, it implements any of the horizontal linear array direction finding error correction methods in the embodiments of this application.

[0019] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0020] This invention solves the problem of systematic direction finding projection deviation caused by multipath acoustic rays at large elevation angles in the detection of the deep-sea thermocline, and achieves the technical effect of improving the passive direction finding accuracy of the linear array. Attached Figure Description

[0021] Figure 1 This is a flowchart of the present invention.

[0022] Figure 2 This is a schematic diagram of the geometric relationship of the arrival angle of the horizontal linear array in this invention.

[0023] Figure 3 This is a graph showing the trend of the lower limit of the non-direct wave elevation angle as a function of the detection distance under the thermocline detection situation of this invention.

[0024] Figure 4 This is a graph showing the trend of non-direct wave multipath delay difference as a function of detection distance under the thermocline detection situation of this invention.

[0025] Figure 5 This is a schematic diagram of the test point arrangement for verifying the applicability of the azimuth angle in this invention.

[0026] Figure 6 This is a comparison diagram of the change in azimuth angle before and after correction in this invention.

[0027] Figure 7 This is a schematic diagram of the test point layout for distance applicability verification in this invention.

[0028] Figure 8 This is a comparison chart showing the change of direction finding error with detection distance before and after correction in this invention.

[0029] Figure 9 This is a schematic diagram of the device structure of the present invention.

[0030] Figure 10 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0031] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0032] Example 1

[0033] like Figure 1 As shown, this invention discloses a method for correcting the direction-finding error of a horizontal linear array:

[0034] (1) Implementation environment

[0035] This embodiment employs a horizontally constant single-layer seabed model. The seabed depth is 5000 meters, the P-wave velocity is 1600 meters per second, the S-wave velocity is 1000 meters per second, the seabed density is 1.8 grams per cubic centimeter, the P-wave attenuation is 0.8 dB per wavelength, and the S-wave attenuation is 0.5 dB per wavelength. The sound velocity profile has a channel axis depth of 1350 meters, and an inverse sound velocity gradient layer exists from 0 to 20 meters near the sea surface. The detection platform is equipped with a 24-element uniform horizontal linear array on its side, with an element spacing of 0.25 meters, and the target signal center frequency is 1500 Hz. This embodiment adopts a thermocline detection configuration: the target depth is 200 meters, the detection platform depth is 300 meters, and both the transmitter and receiver are located within the negative gradient region of the thermocline.

[0036] (2) Constructing the prior mapping curve

[0037] The Bellhop ray model was used to simulate the multipath acoustic field in the aforementioned deep-sea environment. When extracting multipath features, the intrinsic acoustic rays output by the Bellhop ray model were arranged in descending order of energy, starting with the eigenray ray with the highest energy. The set of eigenray rays whose cumulative energy percentage reached a preset cumulative energy percentage threshold constituted the effective acoustic ray set. In this embodiment, the preset cumulative energy percentage threshold was set to 99.9%, meaning that the set of eigenray rays corresponding to a cumulative energy percentage of 99.9% was retained as the effective acoustic ray set, and all other eigenray rays outside this threshold were discarded as weakly scattered acoustic rays. For each detection distance, the trajectory of the eigenray ray output by the Bellhop ray model was used to determine whether there were direct acoustic rays that were not reflected by the sea surface or the seabed under the current transmission and reception configuration. If no direct acoustic rays were found, the minimum absolute value of the elevation angle in the effective acoustic ray set was taken as the lower limit of the non-direct wave elevation angle for that detection distance.

[0038] Simulation results show that, under the thermocline conditions of this embodiment, only a short-range direct sound ray with a small elevation angle exists within a range of approximately 3 to 5 kilometers. The elevation angle of the direct sound ray varies with the transmission and reception depth configuration, typically being a small angle close to zero but not strictly equal to zero. As the detection distance increases, the direct sound ray gradually weakens, disappearing completely at approximately 10 kilometers. After the disappearance of the direct sound ray, large-elevation-angle non-direct multipath sound rays dominate the receiver energy, becoming the core cause of the linear array direction-finding error.

[0039] Reference Figure 3 The variation pattern of the lower limit of the non-direct wave elevation angle with detection distance is as follows: Overall, it decreases with increasing detection distance. In the near-to-mid range (approximately 10 to 40 kilometers), it shows a significant decreasing trend, with the lower limit of the elevation angle gradually decreasing from over 40 degrees at near range to the 10 to 15 degrees range at mid-range. In the medium-to-long range (approximately 50 to 70 kilometers), due to the deep-sea acoustic channel convergence effect, the lower limit of the elevation angle exhibits a fluctuation phenomenon of local decline followed by a slight rebound at certain depths. Beyond 70 kilometers, the curves show differentiated fluctuations at different depths. At longer detection distances, the acoustic ray corresponding to the lower limit of the elevation angle experiences fewer boundary reflections, retains more acoustic energy, and accounts for the highest energy proportion at the receiver, playing a dominant role in the direction finding results of beamforming.

[0040] A conformal piecewise cubic interpolation algorithm is used to perform nonlinear smooth fitting on discrete data points, and a priori empirical curve of the lower limit of the elevation angle of the non-direct wave as a function of the detection distance is constructed.

[0041] (3) Dynamic query of pitch angle

[0042] After obtaining the current detection range, the estimated lower limit of the elevation angle of the dominant sound ray can be obtained by querying the existing prior empirical curve of the lower limit of the elevation angle of the non-direct wave at the corresponding detection range.

[0043] (4) Inverse compensation of observation azimuth angle

[0044] like Figure 1 and 2 As shown, the projection relationship of the horizontal linear array is as follows: Assume the true direction vector of the incoming wave from the target is determined by the true horizontal azimuth angle in three-dimensional space. With the angle of incidence of the signal The phase difference between elements is determined jointly. Since a horizontal linear array has spatial gain only along its array axis, the phase difference depends solely on the component of the direction vector along the horizontal array axis. Conventional beamforming outputs the observation azimuth angle under the assumption that all incoming waves are located in the horizontal plane. The observation azimuth angle Compared with the true azimuth Satisfying projection relationship: Observation azimuth angle The cosine value is equal to the true azimuth angle. The cosine value multiplied by the incident elevation angle The cosine value.

[0045] When the pitch angle is non-zero, the above projection relationship results in the observation azimuth angle. A deviation occurs in the lateral direction. The relationship is inverted to observe the azimuth angle. The predicted pitch angle lower limit is input, and the observed azimuth angle is used as input. The cosine value of the azimuth is divided by the cosine value of the estimated lower limit of the elevation angle, and the inverse cosine of the quotient is taken to obtain the corrected azimuth estimate. The estimated lower limit of the elevation angle is obtained by consulting the prior empirical curve of the lower limit of the elevation angle for non-direct waves.

[0046] (5) Error propagation analysis

[0047] In actual direction finding, there is a deviation between the estimated elevation angle and the true value. This deviation propagates to the azimuth estimation result through a correction formula. Analysis shows that the closer the target is to the transverse direction of the linear array, the more robust the correction method and the wider the allowable deviation in elevation angle estimation; the closer it is to the end-fire direction of the linear array, the more stringent the accuracy requirements of the prior parameters. The larger the elevation angle of the dominant acoustic ray, the more sensitive the correction method is to the accuracy of the prior parameters. The elevation angle estimation error mainly comes from two aspects: one is the indirect deviation introduced by the distance estimation process, and the other is the mismatch between the prior curve and the actual environment.

[0048] (6) Simulation verification

[0049] like Figure 5 and 6As shown, in the azimuth applicability verification, the detection platform was stationary at the coordinate origin, with the bow pointing due north. A horizontal linear array with 24 elements and an element spacing of 0.25 meters was deployed on the starboard side. The target depth was 200 meters, the detection platform depth was 300 meters, and the fixed detection range was 20 kilometers. Figure 5 As shown, on a semicircular arc with a radius of 20 kilometers centered on the detection platform, a static target test point is set at every 10 degrees, ranging from 10 degrees to 170 degrees, for a total of 17 azimuth angles. (Refer to...) Figure 6 The results show that the error curve before correction exhibits a U-shaped distribution with the 90-degree lateral direction as the axis of symmetry: the original direction-finding error is close to zero near the lateral direction; as the target shifts towards the end-firing direction, the projection deviation increases sharply, reaching a peak of 14 degrees near 20 degrees and 160 degrees. After introducing the correction method, the absolute direction-finding error is significantly reduced and stabilized between 0.5 degrees and 3 degrees over a wide azimuth range of 30 degrees to 150 degrees. The average absolute error across the entire azimuth range decreases from 7.47 degrees before correction to 1.70 degrees after correction.

[0050] like Figure 7 and 8 As shown, in the range applicability verification, the depth configuration of the detection platform and the target remained unchanged, the target azimuth angle was fixed at 60 degrees, and the detection range was scanned from 10 kilometers to 50 kilometers, with a total of 12 range points set. (Refer to...) Figure 8 The correction method showed significant gains in the 10 to 40 km range, reducing the error to between 0.5 and 1.5 degrees, and lowering the mean absolute error from 4.13 degrees to 1.12 degrees. The correction effect was particularly pronounced in the short-range segment of 10 to 20 km, with error reductions of 5 to 7 degrees.

[0051] In the quantitative evaluation of the working range, eight distance points were set at 10, 15, 20, 25, 30, 40, 50, and 60 kilometers, and 15 azimuth angles were set at 10-degree intervals, ranging from 20 to 160 degrees. The combination of distance and azimuth angles constituted 120 test points. Within the working range (distance 10 to 40 kilometers, azimuth angle 30 to 150 degrees) where the correction gain was significant, the average absolute error before correction was 4.98 degrees, which decreased to 1.06 degrees after correction, resulting in an overall improvement of 78.8% in direction finding accuracy. The maximum residual error after correction was 1.89 degrees. The error correction effects at various detection distances within the working range are shown in Table 1.

[0052] Table 1. Error correction effect at various detection distances

[0053] Distance (km) Mean error before correction (°) Corrected mean error (°) Error reduction (°) Reduction ratio (%) 10 10.11 1.45 8.65 85.6 15 7.00 1.28 5.72 81.8 20 4.88 1.24 3.64 74.6 25 3.52 0.99 2.53 71.8 30 2.65 0.80 1.85 69.9 40 1.75 0.58 1.18 67.2

[0054] This invention applies to the detection range after the disappearance of the direct sound ray. In the near-range where the direct sound ray still exists, the direct wave carries the majority of the energy and its incident elevation angle is relatively small; the azimuth angle output by conventional beamforming is already quite accurate. If, in this range, the lower limit of the elevation angle of the non-direct wave is used as a priori value for correction, the originally correct observation results will be pulled away from the true value, leading to an increase in error. In the long-range range outside the deep-sea acoustic channel convergence zone, the error curves before and after correction gradually converge, and the gain of the correction method decreases. In practical applications, it is necessary to determine whether the current detection range falls within the working range of the correction method, and correction should only be performed in the detection range from the disappearance of the direct sound ray to the arrival of the convergence zone.

[0055] To verify the applicability of the method framework to different transmission and reception depth configurations, while keeping the marine environmental parameters and array parameters constant, the target depths were set to 100m, 200m, 300m, 500m, and 800m, corresponding to the detection platform depths of 200m, 300m, 400m, 600m, and 900m, respectively. The above-mentioned prior curve construction process was repeated within a distance range of 3 to 100km. The results show that, under the five depth configurations, the lower limit of the non-direct wave elevation angle exhibits a consistent trend of monotonically decreasing with increasing detection distance within the working range (approximately 10 to 40km). The lower limit of the elevation angle gradually decreases from 43° to 46° at close range to 3° to 13° at the far end of the working range. In the far-range segment above 50km, the curves at each depth show differentiated fluctuations due to the deep-sea acoustic channel convergence zone effect, but this range is outside the working range of the method. The above results show that the decreasing characteristic of the prior experience curve is stable and holds true for different transmit and receive depth configurations within the working range of the method. The method flow does not need to be changed, and the prior experience curve under the corresponding depth configuration can be reconstructed to adapt it. The method framework has universality for different transmit and receive depth configurations in the thermocline layer.

[0056] Example 2

[0057] like Figure 4 As shown, in this embodiment, a priori empirical curve of multipath delay difference as a function of detection distance is constructed using the same simulation data. Specifically, the non-direct wave multipath delay difference value corresponding to each detection distance is extracted from the effective sound ray set to obtain discrete data points of multipath delay difference as a function of detection distance; then, a conformal piecewise cubic interpolation algorithm is used to perform nonlinear smooth fitting on the discrete data points to construct a priori empirical curve of multipath delay difference as a function of detection distance.

[0058] Simulation results show that, under thermocline conditions, the multipath delay difference decreases significantly with increasing detection distance and gradually converges. Specifically, in the short-range segment (approximately 10-40 km), it decreases from about 11 seconds to about 5 seconds. In the medium-to-long-range region, the attenuation gradually flattens, eventually stabilizing at 3-4 seconds. The constructed prior empirical curve of the multipath delay difference reflects the mapping relationship between the multipath delay difference and the detection distance, providing prior data support for subsequent applications that utilize mature signal correlation analysis techniques to estimate the multipath delay difference from the received signal and then infer the current detection distance.

[0059] Example 3

[0060] like Figure 9 As shown, Figure 9 A horizontal linear array direction finding error correction system provided in this application embodiment includes:

[0061] The prior mapping curve construction module 11 is used to simulate the multipath sound field of the deep-sea environment using the ray acoustic model, extract discrete data points of the lower limit of the non-direct wave elevation angle as a function of the detection distance, and use a conformal piecewise cubic interpolation algorithm to perform nonlinear smooth fitting on the discrete data points to generate a prior empirical curve of the lower limit of the non-direct wave elevation angle as a function of the detection distance.

[0062] The pitch angle dynamic query module 12 is used to obtain the current detection distance, query the prior experience curve based on the current detection distance, and obtain the estimated lower limit value of the pitch angle of the dominant sound ray at the corresponding detection distance.

[0063] The observation azimuth inverse compensation module 13 is used to inversely compensate the observation azimuth of the conventional beamforming output using the estimated lower limit of the elevation angle, so as to obtain the corrected azimuth estimate.

[0064] Example 4

[0065] like Figure 10 As shown, Figure 10 This is a schematic diagram of an electronic device provided in an embodiment of this application. The electronic device includes: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the horizontal linear array direction-finding error correction method disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment can specifically be an electronic computer.

[0066] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0067] The processor 21 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 21 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 21 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0068] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0069] The operating system 221 manages and controls the various hardware devices and computer programs 222 on the electronic device 20 to enable the processor 21 to perform calculations and processing on the massive amounts of data 223 in the memory 22. It can be Windows Server, Netware, Unix, Linux, etc. The computer program 222, in addition to including a computer program capable of performing the data routing method for the flight ad hoc network disclosed in any of the foregoing embodiments, may further include computer programs capable of performing other specific tasks. The data 223 may include data received by the electronic device from external devices, as well as data collected by its own input / output interface 25.

[0070] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded over a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods shown in the above embodiments are implemented.

Claims

1. A method for correcting the direction-finding error of a horizontal linear array, characterized in that: Includes the following steps: Constructing a priori mapping curve: Using a ray acoustic model, multipath sound field simulation of the deep-sea environment is performed, and discrete data points of the lower limit of the non-direct wave elevation angle as a function of the detection distance are extracted. A nonlinear smooth fitting is performed on the discrete data points using a conformal piecewise cubic interpolation algorithm to generate a priori empirical curve of the lower limit of the non-direct wave elevation angle as a function of the detection distance. Pitch angle dynamic query: Obtain the current detection distance, query the prior experience curve based on the current detection distance, and obtain the estimated lower limit of the pitch angle of the dominant sound ray at the corresponding detection distance; Inverse compensation of observation azimuth angle: The observation azimuth angle output by conventional beamforming is inversely compensated using the estimated lower limit of elevation angle to obtain a corrected azimuth angle estimate. The inverse compensation calculation process is as follows: the cosine value of the observation azimuth angle is divided by the cosine value of the estimated lower limit of elevation angle, and the inverse cosine of the quotient is taken.

2. The horizontal linear array direction finding error correction method according to claim 1, characterized in that: The observed azimuth angle is the azimuth angle output by conventional beamforming under the assumption that all incoming waves are located on the horizontal plane; The estimated pitch angle lower limit is the dominant vocal pitch angle lower limit obtained by querying the prior experience curve. The observed azimuth angle and the target's true azimuth angle satisfy a projection relationship; The cosine of the observed azimuth angle is equal to the cosine of the true azimuth angle multiplied by the cosine of the incident elevation angle.

3. The horizontal linear array direction finding error correction method according to claim 1, characterized in that: The ray acoustic model is the Bellhop ray model, and the discrete data points showing the variation of the lower limit of the non-direct wave elevation angle with the detection distance are obtained in the following way: The intrinsic sound lines output by the Bellhop ray model are arranged in descending order of energy. Starting from the intrinsic sound line with the highest energy, they are added sequentially. All intrinsic sound lines included when the cumulative energy percentage reaches a preset cumulative energy percentage threshold constitute the effective sound line set. Intrinsic sound lines outside the preset cumulative energy percentage threshold are not included in the effective sound line set. For each detection distance, it is determined whether there is a direct sound ray in the effective sound ray set that is not reflected by the sea surface or the seabed. At the detection distance where there is no direct sound ray, the minimum absolute value of the pitch angle in the effective sound ray set is taken as the lower limit value of the non-direct wave pitch angle corresponding to that detection distance.

4. The horizontal linear array direction finding error correction method according to claim 1, characterized in that: It also includes constructing a priori empirical curve for multipath delay difference, which includes the following steps: The deep-sea environment was simulated using the ray acoustic model. The non-direct wave multipath delay difference was extracted for each detection distance, and discrete data points of the multipath delay difference as a function of the detection distance were obtained. A conformal piecewise cubic interpolation algorithm is used to perform nonlinear smooth fitting on the discrete data points of the multipath delay difference as the detection distance changes, generating a priori empirical curve of the multipath delay difference as the detection distance changes. The priori empirical curve of the multipath delay difference as the detection distance changes is used to map the multipath delay difference to the corresponding detection distance estimate.

5. The horizontal linear array direction finding error correction method according to claim 1, characterized in that: The method is applicable to thermocline detection scenarios, where the detection platform and the target are both located within the negative gradient region of the thermocline, and the current transceiver configuration does not contain direct sound rays that are not reflected by the sea surface or the seabed, as determined by the X-ray acoustic model simulation.

6. The horizontal linear array direction finding error correction method according to claim 1, characterized in that: The working range of the method is defined as the near-mid range of detection distance from the disappearance of the direct sound ray to the arrival of the deep-sea acoustic channel convergence zone. Within the working range, the lower limit of the non-direct wave elevation angle decreases monotonically with the increase of the detection distance.

7. The horizontal linear array direction finding error correction method according to claim 1, characterized in that: The horizontal linear array is a uniform horizontal linear array, and the conventional beamforming is a process of enhancing the sound source signal in a specified direction based on the weighted compensation and summation of the received signals of the array elements.

8. A horizontal linear array direction-finding error correction system, characterized in that, The system includes: The prior mapping curve construction module is used to simulate the multipath sound field of the deep-sea environment using the ray acoustic model, extract discrete data points of the lower limit of the non-direct wave elevation angle as a function of the detection distance, and use the conformal piecewise cubic interpolation algorithm to perform nonlinear smooth fitting on the discrete data points to generate a prior empirical curve of the lower limit of the non-direct wave elevation angle as a function of the detection distance. The pitch angle dynamic query module is used to obtain the current detection distance, query the prior experience curve based on the current detection distance, and obtain the estimated lower limit value of the pitch angle of the dominant sound ray at the corresponding detection distance; The observation azimuth angle inverse compensation module is used to inversely compensate the observation azimuth angle output by conventional beamforming using the estimated lower limit value of the elevation angle, so as to obtain the corrected azimuth angle estimate.

9. The horizontal linear array direction finding error correction system based on prior features of deep-sea acoustic field according to claim 8, characterized in that, The system also includes a multipath delay difference prior empirical curve construction module, which is used to simulate the multipath sound field of the deep-sea environment using the ray acoustic model, extract the non-direct wave multipath delay difference value corresponding to each detection distance, and obtain discrete data points of multipath delay difference as a function of detection distance; and use a conformal piecewise cubic interpolation algorithm to perform nonlinear smooth fitting on the discrete data points of multipath delay difference as a function of detection distance to generate a prior empirical curve of multipath delay difference as a function of detection distance. The prior empirical curve of multipath delay difference as a function of detection distance is used to map the multipath delay difference to the corresponding detection distance estimate.

10. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the horizontal linear array direction finding error correction method according to any one of claims 1 to 7.

11. A computer-readable storage medium, wherein when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the horizontal linear array direction finding error correction method as described in any one of claims 1 to 7.

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