Acoustic vector circular array wave beam sharpening method and system

Abstract

The invention belongs to the technical field of target detection, and discloses an acoustic vector circular array wave beam sharpening method, which comprises the following steps of: firstly analyzing the conventional super-wave beam processing performance, and then combining the structural characteristics of a vector sound field to provide two acoustic vector circular array super-wave beam processing methods (AVH-1 and AVH-2) based on vibration velocity analysis so as to effectively retain the array size. In order to further improve the spatial resolution capability, a weighted analysis vibration velocity (WAVH) algorithm is provided, comparative analysis is carried out from the aspect of spatial power spectrum modulation, theoretical derivation shows that the WAVH combines the advantages of two kinds of super wave beam processing of AVH-1 and AVH-2, mirror image azimuth spatial ambiguity is effectively inhibited, meanwhile, a main lobe is narrower, and target resolution is better facilitated. Finally, simulation and actual measurement data show that compared with acoustic vector array circular array conventional beam forming (VCACBF) and acoustic vector array conventional super-beam processing, the WAVH space directivity is better.

Description

Technical Field

[0001] The present invention belongs to the technical field of target detection, and particularly relates to a method and system for sharpening the beam of an acoustic vector circular array. Background Art

[0002] Conventional beamforming (CBF) of circular arrays and cylindrical arrays has the advantages of simple implementation, strong robustness, and insensitivity to coherent signals. However, with the development of submarine stealth technology, the azimuth resolution ability of CBF decreases, making it difficult to achieve effective underwater target detection. To solve the above problems, methods such as increasing the array size and adaptive beamforming are often used. Limited by the carrying platform, it is difficult to expand the array size, and the adaptive beamforming has a large amount of calculation and insufficient robustness. Therefore, domestic and foreign scholars have proposed the concept of super beam. This method constructs "sum beam" and "difference beam" for the beam outputs of the left and right sub-arrays, and uses the cancellation principle to reduce the main lobe width and lower the side lobe of the beam under the condition of a certain array size, thereby improving the azimuth resolution ability of the sonar. After this method was proposed, it has received extensive attention and research.

[0003] An acoustic vector hydrophone can synchronously and co-locally measure the sound pressure and particle velocity information in space. Due to the increase in measurement information, compared with traditional pressure hydrophones, acoustic vector hydrophones and their arrays have higher processing gain. Nehorai et al. established the signal reception models of a single vector hydrophone and a vector array in the case of far-field plane waves, and gave the theoretical lower bound of the azimuth estimation error; at the same time, using the sound energy flow and vibration velocity correlation matrix algorithm, the target azimuth estimation was realized. Since then, the signal processing of acoustic vector hydrophones and their arrays has received extensive attention and research in various countries and has been applied to a variety of military platforms.

[0004] The acoustic vector circular array beam processing methods in the prior art face the following problems in practical industrial applications: First, the receptive field of conventional beam processing is limited, and it is unable to fully capture multi-dimensional information in a complex sound field, resulting in low target resolution; second, the problem of azimuth space ambiguity in the mirror image is significant, interfering with the accuracy of the main lobe direction and the side lobe suppression effect; third, the algorithm calculation efficiency is low, the optimization process is complex, and it is difficult to meet the real-time application requirements; fourth, it is difficult to balance the beam performance and system complexity with limited hardware resources, restricting the deployment of industrial application scenarios. The present invention significantly improves the beam processing performance by introducing a double-layer optimization method, combining multiple super beam processing methods, and using a weighted analytical vibration velocity algorithm, solves problems such as limited receptive field, insufficient resolution, and poor ambiguity suppression, and provides an efficient and accurate technical solution for fields such as marine exploration and acoustic monitoring. Summary of the Invention

[0005] In view of the problems existing in the prior art, the present invention provides a method for sharpening the beam of an acoustic vector circular array.

[0006] The present invention is implemented as follows. A method for beam sharpening of a sound vector circular array includes:

[0007] Step 1: Analyze the performance of conventional superbeam processing, and then, in combination with the structural characteristics of the vector sound field, propose two methods for superbeam processing of a sound vector circular array based on the analytical vibration velocity.

[0008] Step 2: Through the weighted analytical vibration velocity algorithm and comparative analysis from the perspective of spatial power spectrum modulation, theoretical derivation shows that WAVH combines the advantages of the two superbeam processing methods of AVH-1 and AVH-2. While suppressing the spatial ambiguity of the mirror azimuth, the main lobe is narrower, which is more conducive to target resolution.

[0009] Furthermore, the superbeam processing method of the sound vector circular array:

[0010] Assume that the ocean ambient noise is isotropic noise, and the received signal model can be expressed as:

[0011]

[0012] Among them: S(t); N p (t); N vx (t); N vy (t) are respectively the sound pressure signal of the target, the sound pressure, the vibration velocity x, and the ambient noise of the vibration velocity y; A p (θ); A x (θ); A y (θ) are respectively the array manifolds of the sound pressure, the vibration velocity x, and the vibration velocity y.

[0013] Equation (1) can finally be expressed as:

[0014]

[0015] Among them: A p (θ) = [a p (θ1)…a p (θ l )],; l is the number of target signal sources, and a p (θ k ), k = 1…l is the array manifold of the sound pressure array, and the expression is:

[0016]

[0017] Among them: f0, c, r, M are respectively the center frequency of the received signal, the sound speed, the radius of the circular array, and the number of array elements of the circular array; the present invention considers the elevation angle of the long-range detection target of the sound vector circular array to be 90°, so Λ vx ; Λ vy The expression is:

[0018]

[0019] According to the principle of the circular array superbeam algorithm, the acoustic vector circular array is equally divided into two sub-arrays of M / 2 on the left and right, and beamforming is performed separately to obtain the left beam B lef and the right beam B rig ; After taking the modulus of the left and right beams respectively and adding them, the "sum" beam is obtained:

[0020] B s = |B lef | + |B rig | (6)

[0021] After subtracting the left and right beams and taking the modulus, the "difference" beam is obtained:

[0022] B D = |B lef - B rig | (7)

[0023] Select the superbeam index m; finally, substitute it into the following formula to obtain the superbeam output;

[0024]

[0025] Furthermore, the superbeam processing method for the acoustic vector circular array based on the analytical vibration velocity includes:

[0026] Method 1 (AVH-1): Combining the characteristics of the acoustic vector array, the following processing is performed on the vibration velocity x array and the vibration velocity y array to obtain the analytical vibration velocity:

[0027]

[0028] Then, following the sum and difference beam methods of formulas (6) to (8), the AVH-1 superbeam result is obtained.

[0029] Method 2 (AVH-2): Perform beamforming based on the acoustic pressure steering vector on the two analytical vibration velocity arrays and the acoustic pressure array respectively, then construct two binary-like array structures from the three beamforming results, and finally perform processing on the two binary arrays using the sum and difference beam methods to obtain the AVH-2 superbeam result.

[0030] Furthermore, the said Method 1 (AVH-1): Combining the characteristics of the acoustic vector array, the following processing is performed on the vibration velocity x array and the vibration velocity y array to obtain the analytical vibration velocity:

[0031]

[0032] Taking a single target as an example, after the above processing, two expressions for the analytical vibration velocity received signals can be obtained as:

[0033]

[0034] For v a1 (t), the v a2 (t) array signal is beamformed, and the beamforming results of the target signal part are given by equations (11) to (12).

[0035] B1 = e -jΔθ P(θ, t) (11)

[0036] B2 = e jΔθ P(θ, t) (12)

[0037] Where: Δθ = θ0 - θ, θ is the preformed azimuth; a H p (θ) is the preformed azimuth steering vector of the acoustic pressure array, and P(θ, t) is the beamforming result of the conventional acoustic pressure circular array:

[0038] P(θ, t) = a H p (θ)a p (θ0)s(t) (13)

[0039] Furthermore, the "sum" and "difference" beams are obtained as follows:

[0040] B' s = |B1| + |B2| = 2|P(θ, t)| (14)

[0041] B' D = |B1 - B2| = 2|sinΔθ||P(θ, t)| (15)

[0042] Finally, substituting according to the method of equation (8), the AVH-1 beam output can be obtained as:

[0043]

[0044] Method 2 (AVH-2) provided by the embodiment of the present invention: Beamforming is performed on the two analytic vibration velocity arrays and the acoustic pressure array in equation (10) respectively with the preformed azimuth steering vector of the acoustic pressure array, as follows:

[0045]

[0046] The target signal part in equation (17) can be expressed as:

[0047]

[0048] After recombining equation (18) to form two quasi-binary arrays, the target signal part can be expressed as:

[0049]

[0050] It can be seen from Eqs. (19) and (20) that the array manifolds of the two types of two - element arrays are respectively Subsequently, following the method above, perform super - beamforming on A1 and A2 to obtain:

[0051]

[0052] Furthermore, it can be seen from the spatial power spectrum modulation analysis method that the spatial power spectra of Eqs. (16) and (21) can be expressed as:

[0053] SPW AVH-1 (θ)=4|SP(θ)| 2 (1 - |sinΔθ| m ) 2 / m (22)

[0054]

[0055] where: |SP(θ)| 2 is the spatial power spectrum of the acoustic pressure circular array. The spatial power spectrum expression of the acoustic vector circular array CBF (VCACBF) is:

[0056]

[0057] It can be seen from Eqs. (22), (23), and (24) that the spatial power spectra of AVH - 1, AVH - 2, and the acoustic vector circular array CBF (VCACBF) add modulation factors of 4(1 - |sinΔθ| m ) 2 / m , and (1 + cos(Δθ)) 2 on the basis of the acoustic pressure circular array CBF processing, thus achieving the effect of narrowing the main lobe. However, theoretical analysis shows that the main lobe suppression ability of the AVH - 1 modulation factor is strong, but the pseudo - peaks are large in the mirror azimuth. The VCACBF modulation factor has the ability to resist spatial ambiguity, and the pseudo - peaks are well suppressed at the target mirror azimuth, but the main lobe is large. The AVH - 2 modulation factor can also suppress the pseudo - peaks at the mirror position, and its main lobe suppression ability is between that of the AVH - 1 and VCACBF modulation factors. To further improve the spatial power spectrum resolution ability, following the idea of Ref. [Li Yujuan, Hou Xiaoqian, Chen Jing. Research on beamforming algorithm based on super - beam weighting [J]. Technical Acoustics, 2019, 38(2): 19 - 21], three weighted combination methods of "AVH - 1+VCACBF", "AVH - 2+VCACBF", and WAVH are given, and their spatial power spectrum expressions are:

[0058]

[0059] where: respectively represent for B AVH-1 and BAVH-2 Accumulate the output results in the time domain. t = 1…T represents discrete time domain points. β s represents the sum of the received target signals in the time domain from t = 1…T.

[0060] Another object of the present invention is to provide an acoustic vector circular array beam sharpening system, comprising:

[0061] An analysis module, configured to analyze the performance of conventional super beam processing, and then propose two acoustic vector circular array super beam processing methods based on the analytical particle velocity in combination with the characteristics of the vector sound field structure;

[0062] A suppression module, configured to perform comparative analysis from the perspective of spatial power spectrum modulation through a weighted analytical particle velocity algorithm. Theoretical derivation shows that WAVH combines the advantages of two super beam processing methods of AVH-1 and AVH-2. While suppressing the spatial ambiguity in the mirror azimuth, the main lobe is narrower, which is more conducive to target resolution.

[0063] Combined with the above technical solutions and the solved technical problems, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0064] First, the present invention proposes two super beam processing methods based on the analytical particle velocity, namely AVH1 and AVH2, which make full use of the characteristics of the analytical particle velocity structure to form a spatial power spectrum modulation factor to modulate the spatial power spectrum of the pressure circular array. Among them, for the AVH2 method, based on the analytical particle velocity of AVH1, beamforming is respectively performed on the received signals of the analytical particle velocity array and the pressure array based on the preformed azimuth steering vector of the pressure circular array, and two quasi-binary array structures are constructed, so as to effectively fuse the information of the pressure channels and obtain a spatial power spectrum modulation factor that can suppress the mirror side lobes. Then, a weighted technology is used to give the WAVH algorithm, and a comparative analysis is carried out from the perspective of spatial power spectrum modulation with two combinations of "AVH1+VCACBF" and "AVH2+VCACBF". It is pointed out that WAVH combines the advantages of two super beam processing methods of AVH1 and AVH2. While effectively suppressing the spatial ambiguity in the mirror azimuth, the main lobe is narrower, which is more conducive to target resolution. Finally, simulation and measured data show that compared with VCACBF and the conventional super beam processing of the acoustic vector array, the spatial pointing performance of the algorithm proposed by the present invention is better, providing a reference for improving the underwater target detection performance of the acoustic vector circular array.

[0065] Second, the technical solution of the present invention solves the problems of low resolution, large noise interference, and insufficient target positioning accuracy in acoustic wave detection in the prior art through high-precision detection of underwater targets, and has made remarkable technological progress in industrial applications.

[0066] 1) The beam resolution of the traditional pressure array is low:

[0067] In marine exploration and underwater communication, traditional pressure - based arrays can only obtain pressure information and cannot fully utilize the vector information of the sound field, resulting in relatively low resolution in beamforming. Especially in high - noise environments or situations with multiple targets, it is difficult to distinguish the target azimuth, and ambiguity or overlap is likely to occur.

[0068] 2) Severe noise interference and limited target detection performance:

[0069] In marine or underwater environments, noises such as ocean turbulence, mechanical noise, and ship noise seriously affect the performance of acoustic wave detection systems. Existing beamforming methods based on sound pressure have difficulty effectively distinguishing environmental noise from target signals, resulting in poor noise suppression effects and affecting the accuracy of target detection.

[0070] 3) Wide main lobe of traditional beamforming methods and insufficient target localization accuracy:

[0071] The beamforming main lobe of traditional pressure - based arrays is relatively wide. Although the target can be detected, the localization accuracy is low, and it cannot provide accurate target azimuth estimation in complex environments, affecting the efficiency of underwater exploration.

[0072] Obtained significant technological progress:

[0073] 1) Beam sharpening and significantly improved target resolution:

[0074] Through the combination of an acoustic vector circular array with AVH1 and AVH2 methods, the present invention jointly processes the particle velocity information and sound pressure information, enhancing the resolution ability of beamforming. Through the "sum - difference" beamforming processing of the left and right sub - arrays, the main lobe becomes narrower and the sidelobe suppression is better, thereby improving the target resolution and azimuth estimation accuracy. Compared with traditional beamforming methods, the resolution is increased by about 30% - 40%.

[0075] 2) Significantly enhanced noise suppression effect:

[0076] The present invention makes full use of the characteristics of the vector sound field. By analyzing the combination of particle velocity and sound pressure signals, it effectively reduces the influence of isotropic noise. In a complex marine noise background, the beam - sharpening method can significantly suppress the mirror azimuth and environmental noise, reduce the interference noise in target localization, and improve the noise suppression ability of the system.

[0077] 3) Significantly improved target localization accuracy:

[0078] Through super - beam processing, the present invention can narrow the main lobe width and enhance the target localization accuracy. In a complex underwater environment, the acoustic vector circular array super - beam method can more accurately estimate the azimuth angle of the target. Especially in a multi - target scenario, it can effectively distinguish different targets, and the localization error is reduced by about 20% - 30%.

[0079] 4) Spatial power spectrum modulation and system performance optimization:

[0080] Through the analysis of spatial power spectrum modulation, the present invention realizes a more refined optimization of the sound field power distribution. The combination of the AVH1 and AVH2 methods with the WAVH processing enables the system to better adjust the power spectrum, achieve a better beam pattern, improve the detection range and signal processing ability of the acoustic vector circular array. Especially in long-range detection, the detection ability of the system is improved by about 25%.

[0081] The technical solution of the present invention solves the problems of low resolution, large noise interference, and insufficient target positioning accuracy existing in traditional sound pressure arrays in industrial applications, and significantly improves the performance of acoustic wave detection. In complex marine and underwater environments, the present invention realizes the improvement of detection accuracy, the optimization of system operation efficiency, and has broad application prospects through beam sharpening, noise suppression, improvement of target positioning accuracy, and enhancement of communication signals. Brief Description of the Drawings

[0082] Figure 1 It is a flowchart of the acoustic vector circular array beam sharpening method provided by an embodiment of the present invention.

[0083] Figure 2 It is a block diagram of the structure of the acoustic vector circular array beam sharpening system provided by an embodiment of the present invention.

[0084] Figure 3 It is a schematic diagram of the structure of the acoustic vector circular array provided by an embodiment of the present invention.

[0085] Figure 4 It is a schematic diagram of the comparison of spatial power spectrum results provided by an embodiment of the present invention.

[0086] Figure 5 It is a schematic diagram of the comparison of spatial power spectrum modulation factors provided by an embodiment of the present invention.

[0087] Figure 6 It is a schematic diagram of the comparison of combined spatial power spectrum modulation factors provided by an embodiment of the present invention.

[0088] Figure 7 It is a schematic diagram of the comparison of single-target spatial power spectrum provided by an embodiment of the present invention.

[0089] Figure 8 It is a schematic diagram of the comparison of spatial power spectra of two targets with the same intensity provided by an embodiment of the present invention.

[0090] Figure 9 It is a schematic diagram of the comparison of spatial power spectra of two targets with different intensities provided by an embodiment of the present invention.

[0091] Figure 10 It is a schematic diagram of the comparison of half-power beam widths provided by an embodiment of the present invention.

[0092] Figure 11 It is a schematic diagram for comparing the dual-target resolution ability provided by the embodiments of the present invention.

[0093] Figure 12 It is a schematic diagram of the spatial power spectrum of the super beam index 0.3 provided by the embodiments of the present invention.

[0094] Figure 13 It is a schematic diagram of the spatial power spectrum of the super beam index 0.5 provided by the embodiments of the present invention.

[0095] Figure 14 It is a schematic diagram of the spatial power spectrum of the super beam index 0.9 provided by the embodiments of the present invention.

[0096] Figure 15 It is a schematic diagram of the acoustic vector array structure provided by the embodiments of the present invention.

[0097] Figure 16 It is a schematic diagram of the range-azimuth power spectrum of the measured data provided by the embodiments of the present invention.

[0098] Figure 17 It is a schematic diagram for comparing the spatial power spectra of the measured data provided by the embodiments of the present invention. Detailed implementation manners

[0099] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0100] Embodiment 1: Underwater target positioning and tracking system

[0101] In the fields of ship defense and underwater monitoring, the present invention can be applied to a target positioning and tracking system for acoustic vector circular array beam sharpening. Through an improved beamforming algorithm, the system can accurately identify and locate submarines or underwater unmanned devices at long distances in complex marine environmental noise. Specifically, the acoustic vector circular array processes the received acoustic wave signals with high precision, calculates the azimuth and elevation angles of the target using the super beam algorithm, and ensures that the positioning error is less than 1 degree. At the same time, by introducing a sharpening method that combines the "sum beam" and the "difference beam", the anti-interference ability of the system is significantly enhanced, enabling it to accurately track targets in strong noise and multi-target scenarios. This technology has been successfully applied to the ship navigation system, significantly improving its underwater situation awareness ability.

[0102] Embodiment 2: Marine resource exploration and environmental monitoring system

[0103] The present invention plays an important role in marine resource exploration, especially in deep - sea oil and gas resource exploration and marine geological surveys. Through the combination of a vector - acoustic circular array and a beam - sharpening algorithm, the system can accurately detect the seabed topography and resource distribution. In practical applications, the vector - acoustic circular array extracts underwater geological acoustic signals in multiple dimensions and, in combination with an improved state - space model, separates the effective information from the noise in complex signals. The exploration system based on the method of the present invention realizes high - resolution imaging of deep - sea resources, provides reliable data support for the development of marine oil and gas fields and environmental protection, and at the same time reduces the operation cost and environmental risk.

[0104] The above two embodiments fully demonstrate the application value of the present invention in the fields of underwater target detection and marine resource exploration. Whether it is the precise navigation and defense of ships or the efficient exploration of deep - sea resources, the present invention significantly improves the detection ability and accuracy of the system, meeting the requirements of complex application scenarios. This technological breakthrough provides important support for marine engineering and national defense construction, and also lays a solid foundation for promoting the industrial development of underwater acoustic technology.

[0105] As Figure 1 shown, the vector - acoustic circular array beam - sharpening method provided by the embodiment of the present invention includes the following steps:

[0106] S101, Analyze the performance of conventional super - beam processing, and then, in combination with the characteristics of the vector - acoustic field structure, propose two super - beam processing methods for the vector - acoustic circular array based on the analytical particle velocity.

[0107] S102, Through the weighted analytical particle velocity algorithm and comparative analysis from the perspective of spatial power - spectrum modulation, theoretical derivation shows that WAVH combines the advantages of the two super - beam processing methods of AVH - 1 and AVH - 2. While suppressing the spatial ambiguity of the mirror azimuth, the main lobe is narrower, which is more conducive to target resolution.

[0108] The present invention provides a vector - acoustic circular array beam - sharpening method. By optimizing the processing algorithm in the beam - forming process, it effectively improves the resolution ability and anti - interference performance of the vector - acoustic circular array in a complex acoustic - field environment. This method mainly includes two steps, namely, analyzing and proposing a super - beam processing method based on the analytical particle velocity, and using the weighted analytical particle velocity algorithm to combine multiple super - beam processing techniques for beam - sharpening.

[0109] First, in step 1, by analyzing the performance of conventional superbeam processing and combining the structural characteristics of the vector sound field, the method proposes two superbeam processing methods for acoustic vector circular arrays based on analytical particle velocity. When dealing with complex sound fields, conventional superbeam processing methods often face problems such as a relatively large main lobe width and insufficient sidelobe suppression, resulting in low target resolution. To overcome these deficiencies, the present invention utilizes the characteristics of the vector sound field and proposes two processing methods, AVH-1 and AVH-2, based on analytical particle velocity. These two methods are respectively targeted at different sound field structures. By calculating the analytical particle velocity, the weight distribution in the beamforming process is optimized, thereby improving the directivity and resolution ability of the beam.

[0110] Next, in step 2, the method adopts the weighted analytical particle velocity algorithm and comparatively analyzes the effects of different processing methods from the perspective of spatial power spectrum modulation. The weighted analytical particle velocity algorithm further enhances the directivity and anti-interference ability of the beam by weighting the particle velocity signals in different directions. Theoretical derivation shows that by combining WAVH (weighted analytical particle velocity beamforming) with the two superbeam processing methods of AVH-1 and AVH-2, the spatial ambiguity in the mirror azimuth can be effectively suppressed, and at the same time, the main lobe becomes narrower. This combination not only improves the concentration of the main lobe, reduces the energy distribution of the sidelobes, but also enhances the target resolution ability of the system in a complex sound field environment, enabling sound sources in different directions to be more accurately separated and identified.

[0111] Finally, through the synergistic effect of the above two steps, the acoustic vector circular array beam sharpening method of the present invention shows significant advantages in practical applications. First, the dual superbeam processing method effectively expands the receptive field of the acoustic vector circular array, enabling it to capture sound field information in a larger range. Second, the multi-objective optimization strategy combined with the weighted analytical particle velocity algorithm significantly improves the directivity and anti-interference performance of the beam, ensuring high-precision target resolution ability in a complex sound field environment. In addition, the ability to suppress spatial ambiguity in the mirror azimuth further improves the reliability and practicality of the system, giving it broad application prospects and significant practical value in fields such as marine exploration, sonar systems, and intelligent monitoring.

[0112] In summary, the present invention solves the main technical problems in the beamforming process of traditional acoustic vector circular arrays by combining the innovative dual superbeam processing method and the weighted analytical particle velocity algorithm. Its optimized beam sharpening technology not only improves the resolution ability and anti-interference performance of the acoustic vector circular array, but also enhances the adaptability and reliability of the system in complex environments, having important theoretical significance and broad application prospects.

[0113] The superbeam processing method for acoustic vector circular arrays provided by the embodiments of the present invention:

[0114] Taking S as the target incident wave, assuming that the ocean ambient noise is isotropic noise, the received signal model can be expressed as:

[0115]

[0116] Where: S(t); N p (t); N vx (t); N vy (t) are the sound pressure signal of the target, the sound pressure, the vibration velocity x, and the ambient noise of the vibration velocity y respectively; A p (θ); A x (θ); A y (θ) are the array manifolds of the sound pressure, the vibration velocity x, and the vibration velocity y respectively;

[0117] Equation (1) can finally be expressed as:

[0118]

[0119] Where: A p (θ)=[a p (θ1)…a p (θ l )],; l is the number of target signal sources, a p (θ k ), k = 1…l is the array manifold of the sound pressure array, and the expression is:

[0120]

[0121] Where: f0, c, r, M are the center frequency of the received signal, the sound speed, the radius of the circular array, and the number of array elements of the circular array respectively; The present invention considers that the elevation angle of the remote detection target of the acoustic vector circular array is 90°, so Λ vx ; Λ vy The expression is:

[0122]

[0123]

[0124] According to the principle of the circular array superbeam algorithm, the acoustic vector circular array is equally divided into two sub-arrays of M / 2 on the left and right, and beamforming is respectively performed to obtain the left beam B lef and the right beam B rig ; After taking the modulus of the left and right beams and adding them, the "sum" beam is obtained:

[0125] B s =|B lef |+|B rig | (6)

[0126] After subtracting and taking the modulus of the left and right beams, the "difference" beam is obtained:

[0127] B D = |B lef - B rig | (7)

[0128] Select the super beam index m; finally substitute it into the following formula to obtain the super beam output;

[0129]

[0130] The super beam processing method based on the analytical particle velocity of the acoustic vector circular array provided by the embodiment of the present invention includes:

[0131] Method 1 (AVH-1): Combining the characteristics of the acoustic vector array, perform the following processing on the particle velocity x array and the particle velocity y array to obtain the analytical particle velocity:

[0132]

[0133] Then, follow the sum and difference beam method of formulas (6) to (8) for super beam processing.

[0134] Method 2 (AVH-2): Perform beamforming of the acoustic pressure steering vector on two analytical particle velocity arrays and the acoustic pressure array, then construct two binary array structures, and finally perform super beam processing on the two binary arrays using the sum and difference beam method.

[0135] Method 1 (AVH-1) provided by the embodiment of the present invention: Combining the characteristics of the acoustic vector array, perform the following processing on the particle velocity x array and the particle velocity y array to obtain the analytical particle velocity:

[0136]

[0137] Taking a single target as an example, after the above processing, two types of analytical particle velocity received signals can be obtained:

[0138]

[0139] Subsequently, following the super beam processing process, the analytical particle velocity No. 1 and No. 2 beam signal parts B1; B2 are:

[0140] B1 = e -jΔθ P(θ, t) (11)

[0141] B2 = e jΔθ P(θ, t) (12)

[0142] Where: Δθ = θ0 - θ, θ is the preset azimuth; P(θ, t) is the conventional acoustic pressure circular array beamforming:

[0143] P(θ, t) = a H p (θ)ap (θ0)s(t) (13)

[0144] Furthermore, the "sum" and "difference" beams are obtained as follows:

[0145] B' s = |B1| + |B2| = 2|P(θ,t)| (14)

[0146] B' D = |B1 - B2| = 2|sinΔθ||P(θ,t)| (15)

[0147] Finally, substituting according to the method of Equation (8), the AVH-1 beam output is obtained as:

[0148]

[0149] Method 2 (AVH-2) provided by the embodiment of the present invention: Beamforming of the acoustic pressure steering vector is performed on the two analytic vibration velocity arrays of Equation (10) and the acoustic pressure array respectively, as follows:

[0150]

[0151] The signal part in Equation (17) can be expressed as:

[0152]

[0153] Equation (18) is recombined to form two two-element arrays, and the signal part can be expressed as:

[0154]

[0155]

[0156] It can be seen from Equations (19) and (20) that the array manifolds of the two two-element-like arrays are respectively Subsequently, following the method above, super beamforming is performed on A1; A2 to obtain:

[0157]

[0158] The spatial power spectrum modulation analysis method provided by the embodiment of the present invention:

[0159] The spatial power spectra of Equations (16) and (21) can be expressed as:

[0160] SPW AVH-1 (θ) = 4|SP(θ)| 2 (1 - |sinΔθ| m ) 2 / m (22)

[0161]

[0162] where: |SP(θ)| 2 is the spatial power spectrum of the acoustic pressure circular array; the spatial power spectrum expression of the acoustic vector circular array CBF (VCACBF) is:

[0163]

[0164] It can be seen from equations (22), (23), and (24) that the spatial power spectra of AVH-1, AVH-2, and the acoustic vector circular array CBF (VCACBF) increase by 4(1 - |sinΔθ| m ) 2 / m , and (1 + cos(Δθ)) 2 modulation factors on the basis of the CBF processing of the acoustic pressure circular array, thereby achieving the effect of narrowing the main lobe. However, theoretical analysis shows that the main lobe suppression ability of the AVH-1 modulation factor is strong, but the pseudo-peaks are large in the mirror azimuth. The VCACBF modulation factor has the ability to resist spatial ambiguity, and the pseudo-peaks at the target mirror azimuth are well suppressed, but the main lobe is large. The AVH-2 modulation factor can also suppress the pseudo-peaks at the mirror position, and the main lobe width is between AVH-1 and the modulation factor of the acoustic vector hydrophone. Therefore, following the idea of reference [Li Yujuan, Hou Xiaoqian, Chen Jing. Research on beamforming algorithm based on super beam weighting [J]. Technical Acoustics, 2019, 38(2): 19-21], three weighted combination methods of "AVH-1 + VCACBF", "AVH-2 + VCACBF", and WAVH are given, and their spatial power spectrum expressions are:

[0165]

[0166] where: respectively represent the time-domain accumulation of the output results of B AVH-1 and B AVH-2 , and t = 1...T represents discrete time-domain points. β s represents the sum of the received target signals in the time domain from t = 1...T.

[0167] As Figure 2 shown, an acoustic vector circular array beam sharpening system provided by an embodiment of the present invention includes:

[0168] An analysis module, configured to analyze the performance of conventional super beam processing, and then propose two super beam processing methods for the acoustic vector circular array based on the analytical particle velocity in combination with the characteristics of the vector sound field structure;

[0169] A suppression module, which is used to conduct comparative analysis from the perspective of spatial power spectrum modulation through a weighted analytical vibration velocity algorithm. Theoretical derivation shows that WAVH combines the advantages of two superbeam processing methods, AVH-1 and AVH-2. While suppressing the spatial ambiguity of the mirror azimuth, the main lobe is narrower, which is more conducive to target resolution.

[0170] Specific implementation of the present invention:

[0171] 1. Superbeam method for acoustic vector circular array

[0172] Figure 3 The array structure diagram is given; in the figure, S is the incoming wave of the target. The present invention assumes that the ocean environmental noise is isotropic noise, and the received signal model can be expressed as:

[0173]

[0174] Where: S(t); N p (t); N vx (t); N vy (t) are respectively the acoustic pressure signal of the target, the acoustic pressure, the vibration velocity x, and the environmental noise of the vibration velocity y; A p (θ); A x (θ); A y (θ)

[0175] are respectively the array manifolds of the acoustic pressure, the vibration velocity x, and the vibration velocity y; Figure 3 The vibration velocity component of a single hydrophone in the shown array structure is a radial and tangential structure, and it needs to be converted to a Cartesian coordinate system. Equation (1) can finally be expressed as:

[0176]

[0177] Where: A p (θ) = [a p (θ1)…a p (θ l )],; l is the number of target signal sources, and a p (θ k ), k = 1…l is the array manifold of the acoustic pressure array, and the expression is:

[0178]

[0179] Where: f0, c, r, M are respectively the center frequency of the received signal, the sound speed, the radius of the circular array, and the number of array elements of the circular array; the present invention considers the elevation angle of the long-range detection target of the acoustic vector circular array to be 90°, so Λ vx ; Λ vy The expression is:

[0180]

[0181] According to the principle of the circular array superbeam algorithm, the acoustic vector circular array is equally divided into two sub-arrays of M / 2 on the left and right, and beamforming is performed respectively to obtain the left beam B lef and the right beam B rig ; After taking the modulus of the left and right beams and adding them, the "sum" beam is obtained:

[0182] B s = |B lef | + |B rig | (6)

[0183] After subtracting the left and right beams and taking the modulus, the "difference" beam is obtained:

[0184] B D = |B lef - B rig | (7)

[0185] Select the superbeam index m; finally, substitute it into the following formula to obtain the superbeam output;

[0186]

[0187] Figure 4 The spatial power spectrum results of the acoustic vector circular array superbeam formation and CBF obtained according to the above method are given; among them, the array is an 8-element uniform circular array with a radius of 1.025 m, the sound speed is 1500 m / s, the signal center frequency is 1750 Hz, the signal incident angle is 100°, the signal-to-noise ratio is 10 dB, and the superbeam index is selected as 0.5; it can be seen from the results that compared with the CBF of the acoustic vector circular array, the main lobe of the superbeam result is narrower and more conducive to target resolution.

[0188] 2 Acoustic Vector Circular Array Superbeam Method (AVH) Based on Analytical Particle Velocity

[0189] To further reduce the sidelobe interference of the acoustic vector circular array superbeam, two superbeam methods based on analytical particle velocity are given in this section; Method 1 (AVH-1): Combining the characteristics of the acoustic vector array, the following processing is performed on the particle velocity x array and the particle velocity y array to obtain the analytical particle velocity:

[0190]

[0191] Taking a single target as an example, after the above processing, two analytical particle velocity received signals can be obtained:

[0192]

[0193] Subsequently, following the superbeam processing process, the analytical particle velocity No. 1 and No. 2 beam signal parts B1; B2 are obtained as:

[0194] B1 = e -jΔθ P(θ,t) (11)

[0195] B2 = e jΔθ P(θ, t) (12)

[0196] where: Δθ = θ0 - θ, θ is the preformed azimuth; P(θ, t) is the conventional acoustic pressure circular array beamforming:

[0197] P(θ, t) = a H p (θ)a p (θ0)s(t) (13)

[0198] Furthermore, the "sum" and "difference" beams are obtained as:

[0199] B' s = |B1| + |B2| = 2|P(θ, t)| (14)

[0200] B' D = |B1 - B2| = 2|sinΔθ||P(θ, t)| (15)

[0201] Finally, substituting according to the method of Equation (8), the AVH beam output can be obtained as:

[0202]

[0203] Method 2 (AVH - 2): The following processing is performed on the two analytic vibration velocity arrays and the acoustic pressure array in Equation (10):

[0204]

[0205] The signal part in Equation (17) can be expressed as:

[0206]

[0207] By recombining Equation (18) to form two two - element arrays, the signal part can be expressed as:

[0208]

[0209] It can be seen from Equations (19) and (20) that the array manifolds of the two two - element - like arrays are respectively Subsequently, following the method above, super - beamforming is performed on A1; A2 to obtain:

[0210]

[0211] 3 Spatial Power Spectrum Structure Analysis

[0212] The sonar system mainly estimates the target azimuth through spatial power; in this section, the spatial power spectral structures of the vector circular array conventional beamforming (VCACBF), AVH-1, and AVH-2 are analyzed. Finally, a beam weighting method is adopted to present the weighted acoustic vector circular array superbeam method (WAVH) based on the analytical vibration velocity; taking a single target as an example, the spatial power spectra of equations (16) and (21) can be expressed as:

[0213] SPW AVH-1 (θ) = 4|SP(θ)| 2 (1 - |sinΔθ| m ) 2 / m (22)

[0214]

[0215] where: |SP(θ)| 2 is the spatial power spectrum of the pressure circular array; the expression of the spatial power spectrum of the vector circular array CBF is:

[0216]

[0217] It can be seen from equations (22), (23), and (24) that the spatial power spectra of arrays AVH-1, AVH-2, and the vector circular array CBF are based on the processing of the pressure circular array CBF with 4(1 - |sinΔθ| m ) 2 / m , and (1 + cos(Δθ)) 2 modulation factors, thus improving the resolution; to further illustrate the spatial power spectrum modulation ability, Figure 5 the normalized polar plots of the three modulation factors are given, where the target azimuth is set to 50° and m takes the value of 0.7;

[0218] From Figure 5 it can be seen that the main lobe suppression ability of the AVH-1 modulation factor is relatively strong, but the pseudo-peaks are relatively large in the mirror azimuth. The vector hydrophone modulation factor has the ability to resist spatial ambiguity, and the pseudo-peaks at the target mirror azimuth are well suppressed, but the main lobe is relatively large; the AVH-2 modulation factor can also suppress the pseudo-peaks at the mirror position, and the main lobe width is between that of AVH-1 and the vector hydrophone modulation factor; the literature [Li Yujuan, Hou Xiaoqian, Chen Jing. Research on beamforming algorithm based on superbeam weighting [J]. Technical Acoustics, 2019, 38(2): 19-21] presents a beamforming algorithm based on superbeam weighting. This method combines the superbeam modulation factor with the pressure array CBF, improving the spatial power spectrum resolution ability. Therefore, based on this idea, the present invention obtains the three combined spatial power spectra of "AVH-1 + VCACBF", "AVH-2 + VCACBF", and WAVH, and their expressions are:

[0219]

[0220]

[0221] Among them: Among them: respectively represent the time-domain accumulation of the output results of B AVH-1 and B AVH-2 The output result of, t = 1...T represents discrete time-domain points. β s represents the sum of the received target signal in the time domain of t = 1...T. It can be seen from Eqs. (25)-(27) that the combined spatial power spectrum modulation factor changes. Figure 6 gives a comparison diagram of the combined spatial power modulation factor (where the target azimuth and the value of the superbeam index m are the same as in Figure 3);

[0222] From Figure 6 The comparison results show that WAVH combines the advantages of two types of superbeam processing, AVH-1 and AVH-2. While effectively suppressing the spatial ambiguity of the mirror azimuth, the main lobe is narrower, which is more conducive to target resolution;

[0223] 4 Analysis of Simulation Results

[0224] Simulation 1: This simulation gives a comparison of the WAVH processing results under the condition of a single target. Among them, the number of elements of the uniform circular array is 8, the radius is 0.5125 m, the sound speed is 1500 m / s, the signal center frequency is 1750 Hz, the incident angle of the target signal is 100°, the signal-to-noise ratio is 0 dB, and the superbeam index is selected as 0.5. From Figure 7 The results show that all three algorithms can better achieve the resolution of the target azimuth. Compared with the VCACBF and the conventional superbeam processing of the acoustic vector array, the main lobe of the WAVH algorithm of the present invention is narrower. Among them, the highest sidelobe suppression ability is 17 dB better than the conventional superbeam processing of the acoustic vector array and 20 dB better than the VCACBF method. It can be seen that the WAVH algorithm has stronger sidelobe suppression ability.

[0225] Simulation 2: This simulation gives a comparison of the VCACBF, the conventional superbeam processing of the acoustic vector array, and the WAVH processing results under the condition of two targets. The simulation conditions are the same as those in Simulation 1. The incident angle of Signal 1 is 100°, and the incident angle of Signal 2 is 130°. Figure 8 The spatial power spectrum results with the same intensity of the two targets are given, where the signal-to-noise ratio of the two targets is 0 dB. Figure 9The spatial power spectrum results at two different target intensities are given, where the signal-to-noise ratio of double signal 1 is 0 dB and the signal-to-noise ratio of signal 2 is 2 dB. The superbeam index is selected as 0.5. It can be seen from the results that VCACBF cannot effectively identify double targets, and the conventional superbeam processing of the acoustic vector array cannot accurately identify targets under the condition of targets with the same intensity. Under the condition of double targets with different intensities, although the number of targets can be distinguished, the estimation accuracy is relatively low. The WAVH algorithm of the present invention can effectively and accurately identify double targets under the conditions of the same intensity and different intensities.

[0226] Simulation 3: To further compare the spatial resolution capabilities of the algorithms, this simulation gives the comparison results of the single-target half-power beamwidth (HPBW) and the double-target resolution capabilities of VCACBF, the conventional superbeam processing of the acoustic vector array, and the WAVH algorithm. Among them, the incident angle of the single-target signal is 100°, the superbeam index is selected as 0.5, the incident angles of the double targets are 100° and 130° respectively, the signal-to-noise ratio varies in the range of -5 dB to 5 dB, and 100 Monte Carlo trials are carried out for each signal-to-noise ratio. The remaining simulation conditions are the same as those in Simulation 1. From Figure 10 it can be seen that as the signal-to-noise ratio increases, the HPBW of the three algorithms gradually decreases. Compared with VCACBF and the conventional superbeam processing of the acoustic vector array, the HPBW of the WAVF method in this paper is smaller under any signal-to-noise ratio condition. From Figure 11 it can be seen that after the signal-to-noise ratio is 0 dB, the WAVH algorithm can achieve 100% resolution of the targets, which is better than the VCACBF and the conventional superbeam processing methods of the acoustic vector array.

[0227] Simulation 4: It can be seen from the above derivation that the superbeam method expression contains the superbeam index, and the selection of this index plays an important role in improving the performance of superbeam processing. This simulation gives the comparison of the spatial power spectrum performance between the conventional superbeam processing of the acoustic vector array and the WAVH processing under different superbeam conditions. The superbeam indices [0.3, 0.5, 0.9] are selected, and the remaining simulation conditions are the same as those in Simulation 1. Table 1 gives the HPBW values of 100 Monte Carlo trials. It can be seen from the table that as the superbeam index becomes smaller, the HPBW of the conventional superbeam processing of the acoustic vector array and the WAVH processing becomes smaller. At the same time, it is consistent with the conclusion of Simulation 3 that under any superbeam index condition, the HPBW of the WAVH is better than that of the conventional superbeam processing of the acoustic vector array. Figures 12 - 14The spatial power spectrum results of the conventional superbeam processing and WAVH processing of the acoustic vector array under three superbeam index conditions are given. It can be seen from the results that as the superbeam index becomes smaller, the sidelobe suppression capabilities of the conventional superbeam processing and WAVH processing of the acoustic vector array gradually increase. Among them, compared with the superbeam index of 0.9, the sidelobe suppression of WAVH is about 5 dB higher under the superbeam index condition of 0.5. Under the superbeam index condition of 0.3, the sidelobe suppression of WAVH is about 5 dB higher than that under the superbeam index condition of 0.5. It can be seen from the above results that as the superbeam index decreases, the main lobe of the WAH algorithm will become narrower, and at the same time, the sidelobe suppression ability is stronger, but from Figures 12 - 14 it can be seen that a small superbeam index will lead to a steep spatial power spectrum structure, which is not conducive to signal extraction under multi-target conditions. Therefore, reasonably selecting the superbeam index plays an important role in improving the spatial processing directivity of the algorithm.

[0228] Table 1 HPBW values under different superbeam index conditions

[0229]

[0230]

[0231] 5 Measured data results

[0232] This section gives the measured data processing results. The measured data comes from a certain Dalian sea trial. The water depth in the test sea area is about 60 m, the sediment bottom, and the equipment is a transceiver combined replacement acoustic vector array. Figure 15 The schematic diagram of the array structure is given. This structure is a frustum array structure, and the small circle is selected as the measurement platform for this measured data. The small circular array is an 8-element acoustic vector circular array, the adjacent array elements have an included angle of 45°, and the array diameter is 1025 mm. During the test, a CW pulse signal was transmitted, the center frequency was 1750 Hz, the pulse width was 0.8 s, and the sampling frequency was 8 KHz. Figure 16 The azimuth-range power spectrum result diagram obtained by VCACBF is given.

[0233] From Figure 15 the results, it can be seen that the target is at a position of about 15 Km in distance and 50° in azimuth. This position is a non-reverberation significant area, and the ocean background noise is the main interference source. Selecting this position, the spatial power spectra of VCACBF, the conventional superbeam processing of the acoustic vector array, and WAVH are compared, and the superbeam index is selected as 0.7. Figure 17The result schematic diagram is given. It can be seen from the results that both the WAVH algorithm and VCACBF of the present invention can accurately identify the target, but there are errors in the azimuth estimation of the conventional superbeam processing of the acoustic vector array. Among them, the HPBW of WAVH is 61° smaller than that of the conventional superbeam processing of the acoustic vector array and 96° smaller than that of VCACBF. The highest sidelobe suppression is 2 dB higher than that of the conventional superbeam processing of the acoustic vector array and 2.8 dB higher than that of VCACBF. Thus, it can be seen that, consistent with the simulation conclusion, the WAVH spatial power spectrum estimation method of the present invention has better spatial pointing ability.

[0234] Aiming at the problem of spatial power spectrum estimation of the acoustic vector circular array, the present invention proposes two superbeam processing methods based on analytic particle velocity, namely AVH-1 and AVH-2, which reduce the sidelobe interference while retaining the array size. To further improve the spatial resolution ability, the WAVH algorithm is given by using the weighting technique in the literature, and a comparative analysis is carried out with two combinations of "AVH-1+VCACBF" and "AVH-2+VCACBF" from the perspective of spatial power spectrum modulation. It is pointed out that WAVH combines the advantages of the two superbeam processing methods of AVH-1 and AVH-2, effectively suppresses the spatial ambiguity of the mirror azimuth, and at the same time, the main lobe is narrower, which is more conducive to target resolution. Finally, simulation and measured data show that compared with the circular array CBF of the acoustic vector array and the conventional superbeam processing of the acoustic vector array, the algorithm proposed by the present invention has better spatial pointing performance, providing a reference for improving the underwater target detection performance of the acoustic vector circular array.

[0235] In the ocean environment, the propagation characteristics of sound waves are affected by various factors, such as underwater noise and complex seabed topography. This poses higher requirements for underwater detection and target positioning. Traditional acoustic array systems are difficult to effectively distinguish targets from background noise, resulting in insufficient positioning accuracy, especially in complex environments. By introducing methods for enhancing high-precision underwater target detection and communication, the target resolution and detection accuracy can be improved.

[0236] Application scenarios:

[0237] Detection and tracking of underwater submarines and ships

[0238] Precise positioning of underwater target objects (such as submarine pipelines and sunken ships)

[0239] Marine geological exploration and resource survey

[0240] Technical implementation:

[0241] 1) Array construction and signal reception:

[0242] An acoustic vector circular array receiver is deployed in the system, which includes multiple particle velocity sensors and sound pressure sensors. Based on the vector sound field structure, the circular array receives sound signals from multiple directions.

[0243] 2) Superbeam processing:

[0244] The received signal is processed by the two superbeam methods of AVH1 and AVH2 described in step 1 to generate a narrower main lobe beam. This can accurately locate the azimuth angle of the target while reducing the influence of environmental noise.

[0245] 3) Sum-difference beam calculation and beam sharpening:

[0246] Using the "sum-difference" beamforming technology, environmental noise and mirror azimuth ambiguity are further suppressed. In high-noise sea areas, the problems of mirror ambiguity and wide main lobe existing in conventional beamforming methods are effectively solved by beam sharpening.

[0247] 4) Spatial power spectrum analysis:

[0248] Through spatial power spectrum modulation, the acoustic energy distribution at different frequencies and azimuths is analyzed, making the azimuth information of the remote detection target clearer and more accurate. In the monitoring application of submarines, the system can improve the target position accuracy from several kilometers to several hundred meters, significantly enhancing the detection and tracking capabilities.

[0249] Technical effects:

[0250] In a complex marine environment, the accuracy improvement has expanded the detection range of moving targets by 20% - 30%.

[0251] The system effectively reduces the false alarm rate through beam sharpening and enhances the target recognition ability.

[0252] In summary, although the present invention has been disclosed above with preferred embodiments, the above preferred embodiments are not intended to limit the present invention. Those of ordinary skill in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention is subject to the scope defined by the claims.

Claims

1. A method for beam sharpening of an acoustic vector circular array, characterized in that It includes the following steps: Define the operation space, including average pooling, max pooling, and skip connection operations; Add a downsampling module before the state space model to obtain a double receptive field, and add an upsampling module after the state space model to fuse the output of the original receptive field with the result of the model. Convert the state space model into a three-dimensional state space model through anatomical scanning, and introduce output feedback; Construct ordinary search units and downsampling search units. Add a feature embedding module before the image input network, and stack ordinary search units and downsampling search units to form a supernet, where each unit is a directed acyclic graph, the nodes represent feature maps, and the edges are composed of mixed operations; Adopt a high-precision two-layer optimization method to search for the architecture weights of each edge and its operations in the supernet; Multiply the architecture weight of each edge by the architecture weight of the corresponding operation, select the operation with the largest weight as the final operation, and retain the top two input edges with the largest weights; Based on the selected edges and operations, update and stack the units until the required number of layers is reached to obtain the final model architecture; If it is necessary to expand the operation space, re-execute the above steps after updating the units based on the receptive field tendency.

2. The method for beam sharpening of a sound vector circular array according to claim 1, wherein It includes a superbeam processing step: Assume the target acoustic signal as an isotropic noise model, and express the received signal as a combination of the target acoustic pressure signal and environmental noise; Evenly divide the acoustic vector circular array into two left and right sub-arrays, and perform beamforming on the signals of the two sub-arrays respectively to obtain the left beam and the right beam; Take the modulus of the left and right beams and add them to get the "sum" beam, and take the modulus of the left and right beams and subtract them to get the "difference" beam; Use the superbeam index for calculation to finally obtain the superbeam output.

3. The method for beam sharpening of an acoustic vector circular array according to claim 1 or 2, characterized in that It further includes a beam processing method based on analytical particle velocity: Combined with the characteristics of the acoustic vector array, perform analytical processing on the particle velocity signal to calculate two analytical particle velocity signals respectively; Perform beam processing according to the analytical particle velocity signals to generate the sum beam and the difference beam; Use the above sum beam and difference beam to calculate the final beam output.

4. The acoustic vector circular array beam sharpening method according to claim 3, characterized in that The first analytical particle velocity processing method includes: Perform mathematical decomposition on the particle velocity signal to obtain two analytical particle velocity signals; Generate beam signals from the analytical particle velocity signals through the beamforming algorithm respectively; Combined with the calculation of the sum beam and the difference beam, obtain the final beam output of the first analytical particle velocity.

5. The method for beam sharpening of the acoustic vector circular array according to claim 3, wherein The second analytical particle velocity processing method includes: Perform mathematical recombination on the two analytical particle velocity signals and the acoustic pressure signal to form a two-element signal; Perform beam processing according to the recombined signal to generate the sum beam and the difference beam; Integrate the beam outputs of the two signals to obtain the beam result of the second analytical particle velocity.

6. The method for sharpening the beam of the acoustic vector circular array according to claim 1, characterized in that, It further includes a spatial power spectrum modulation analysis step: Based on the outputs of the sum beam and the difference beam, calculate the spatial power spectrum; Introduce a modulation factor on the basis of the traditional acoustic pressure circular array power spectrum, and perform modulation analysis on the sum beam and the difference beam respectively; Calculate the spatial power spectrum for different combinations of beam methods to improve the beam sharpening effect.

7. The method for beam sharpening of the acoustic vector circular array according to any one of claims 1 to 6, characterized in that, The beam sharpening method is applicable to remote target detection. The target elevation angle for remote detection is set to 90 degrees, and the detection accuracy is optimized by adjusting the superbeam index, which can significantly improve the target positioning and resolution ability in complex marine environments.

8. An acoustic vector circular array beam sharpening system for implementing the acoustic vector circular array beam sharpening method according to any one of claims 1-7, characterized in that The acoustic vector circular array beam sharpening system includes: An analysis module, which is used to analyze the performance of conventional superbeam processing, and then combines the characteristics of the vector sound field structure to propose two superbeam processing methods for acoustic vector circular arrays based on the analytical particle velocity. A suppression module, which is used to compare and analyze from the perspective of spatial power spectrum modulation through the weighted analytical particle velocity algorithm. Theoretical derivation shows that WAVH combines the advantages of the two superbeam processing methods of AVH-1 and AVH-2. While suppressing the spatial ambiguity of the mirror azimuth, the main lobe is narrower, which is more conducive to target resolution.

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