Non-rigid target acoustic scattering micro-Doppler feature prediction method and system

Abstract

The present invention provides a method and system for predicting the acoustic scattering micro-Doppler characteristics of non-rigid targets, including the following steps: Step S1: Obtain the scattering sound field of the non-rigid target; Step S2: Predict the acoustic scattering micro-Doppler characteristics of the non-rigid target according to the scattering sound field. The present invention is applicable to the acoustic scattering simulation of non-rigid moving targets, enabling physical acoustics methods to be used for analyzing the micro-motion characteristics of non-rigid moving target acoustic scattering; compared with traditional methods, the present invention can accurately simulate the micro-Doppler characteristics generated during the movement of non-rigid targets, thereby providing an effective method for analyzing the characteristics of non-rigid moving targets; applying the present invention can better analyze the micro-motion characteristics, especially the micro-Doppler characteristics, caused during the movement of non-rigid targets than traditional methods, thus providing support for the detection and identification of non-rigid targets by active sonar.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater target characteristic simulation, and in particular, to a method and system for predicting the micro-Doppler characteristics of acoustic scattering of non-rigid targets. Background Art

[0002] As a key technology in the field of underwater detection, the core of underwater acoustic target recognition technology is the analysis and extraction of target acoustic scattering characteristics. The main methods for studying target acoustic scattering characteristic extraction are numerical simulation and experiments. Compared with experiments, numerical simulation has low cost, good repeatability, and the prediction accuracy depends on the prediction method and the accuracy of the numerical model. In recent years, numerical simulation technology has become a widely used method in many engineering fields.

[0003] For the high-frequency acoustic scattering prediction direction of underwater complex targets, due to the limitations of computing efficiency and storage space, numerical methods such as finite element and finite difference time domain are powerless. The Kirchhoff approximation based on physical acoustics is currently the most common method in the engineering field to solve the high-frequency acoustic scattering problem of complex targets (for example, reference [4]). This method approximately calculates the surface acoustic pressure with surface admittance or reflection coefficient, avoids directly solving the surface Helmholtz integral equation, greatly improves the calculation speed, and is suitable for rapid calculations with a grid number of up to hundreds of thousands or even millions.

[0004] For underwater targets such as submarines and UUVs (Unmanned Underwater Vehicles) that rely on propeller structures for propulsion, their external shapes basically do not change during navigation, belonging to rigid targets, and there is no need to consider the influence of shape changes on the scattering sound field. The English full name of UUV is Unmanned underwater vehicle, and the Chinese translation is unmanned submersible.

[0005] Reference: [1] Fan Jun, Tang Weilin. Plate element method for sonar target strength (TS) calculation [C] / / Proceedings of the 1999 Youth Academic Conference of the Chinese Acoustical Society [CYCA'99]. 1999.

[0006] [2] Wang Xilong, Zhang Linlin. Plate element method for predicting sonar target echo characteristics [J]. Science and Technology Outlook, 2016, 26(13).

[0007] [3] K. Lee and W. Seong. Time-domain Kirchhoff model for acoustic scattering from an impedance polygon facet [J]. J. Acoust. Soc. Am. 2009, 126(1): EL14-EL21.

[0008] [4] A.T. Abawi. Kirchhoff scattering from non - penetrable targets modeled as an assembly of triangular facets[J]. J. Acoust. Soc. Am. 2016, 140(3): 1878 - 1886.

[0009] The Chinese invention patent document with the publication number CN113359137A discloses an underwater target acoustic identification method based on the acoustic scattering resonance characteristics of a periodic structure. A periodic distribution structure is designed, and a short - pulse linear frequency - modulated signal is used to excite the periodic structure. The echo signal and the reference signal are subjected to convolution envelope processing to obtain the acoustic target strength. According to the Bragg scattering principle, the azimuth coordinate axis is transformed to obtain an inverted trapezoidal color map of the acoustic target strength, making the geometric scattering phase interference fringes presented vertically. The resonance peaks are extracted by energy integration in the frequency domain direction, and the corresponding relationship between the resonance peak positions and binary symbols is established to form an acoustic barcode, completing the acoustic identification, and the structural period is decoded according to the Bragg scattering principle.

[0010] Regarding the above - mentioned related technologies, the inventor believes that targets such as frogmen and aquatic organisms that move forward by body swinging belong to non - rigid targets. During the movement of such targets, each part mainly moves non - uniformly, and the shape changes regularly with time. For non - rigid targets, traditional acoustic scattering characteristic analysis methods are no longer sufficient to describe the micro - Doppler characteristics contained in the scattering sound field during target movement. Summary of the Invention

[0011] Aiming at the defects in the prior art, the purpose of the present invention is to provide a method and system for predicting the acoustic scattering micro - Doppler characteristics of non - rigid targets.

[0012] According to a method for predicting the acoustic scattering micro - Doppler characteristics of non - rigid targets provided by the present invention, the following steps are included:

[0013] Step S1: Obtain the scattering sound field of the non - rigid target;

[0014] Step S2: Predict the acoustic scattering micro - Doppler characteristics of the non - rigid target according to the scattering sound field.

[0015] Preferably, the step S1 includes the following steps:

[0016] Information acquisition step: Establish a moving target model according to the shape and movement law of the non - rigid target, obtain the receiving and transmitting position information from the relative position between the transceiver and the target, perform grid meshing on the moving target model and extract the dynamic grid, and obtain the grid information and velocity vector of each part of the non - rigid target.

[0017] Steps for obtaining the incident wave frequency response function: According to the velocity vector and the receiving and transmitting position information in the information acquisition step, transform the incident signal in the stationary space to obtain the incident signal in the moving space, and transform the incident signal in the moving space to obtain the incident wave frequency response function in the moving space;

[0018] Steps for obtaining the scattered sound field frequency response function: According to the grid information in the information acquisition step, obtain the impulse response function of the scattered sound field for each grid in the moving space, and obtain the scattered sound field frequency response function in the moving space based on the impulse response function of the scattered sound field in the moving space;

[0019] Steps for obtaining the time-domain echo of the scattered sound field: Obtain the echo spectrum of the scattered sound field in the moving space from the incident wave frequency response function in the moving space and the scattered sound field frequency response function in the moving space, and transform the echo spectrum of the scattered sound field in the moving space to obtain the time-domain echo of the scattered sound field in the moving space;

[0020] Steps for obtaining the total scattered sound field: Transform the time-domain echo of the scattered sound field in the moving space to obtain the scattered sound field in the stationary space, and accumulate the scattered sound fields of each grid in the moving space and the stationary space to obtain the total scattered sound field.

[0021] Preferably, in the step of obtaining the incident wave frequency response function, the incident signal s(t) in the stationary space, where t is the time quantity in the stationary space; use the Lorentz transformation to obtain the incident signal s′(t′) in the moving space, where t′ is the time quantity in the moving space; use the Fourier transform on the incident signal s′(t′) in the moving space to obtain the incident wave frequency response function S′(f′) in the moving space, where f′ is the frequency quantity in the moving space.

[0022] Preferably, in the step of obtaining the incident wave frequency response function, the relationship between t′ in the moving space and t in the stationary space is:

[0023]

[0024] where v represents the product of the grid movement velocity vector and the unit vector from the grid center point to the receiving and transmitting, and c represents the sound speed in water.

[0025] Preferably, in the step of obtaining the scattered sound field frequency response function, use the Fourier transform on the impulse response function h′(τ′) of the scattered sound field for each grid in the moving space to obtain the scattered sound field frequency response function H′(f′) in the moving space, where τ′ represents the time variable in the system impulse response function;

[0026] The relationship between the impulse response function h′(τ′) of the scattered sound field for each grid in the moving space and the scattered sound field frequency response function H′(f′) in the moving space is:

[0027]

[0028] Among them, e represents the natural exponent, and i represents the imaginary number.

[0029] Preferably, in the step of obtaining the time-domain echo of the scattered sound field, the echo spectrum number Y′(f′) of the scattered sound field in the motion space is obtained by inverse Fourier transform to obtain the time-domain echo y′(t′) of the scattered sound field in the motion space;

[0030] The calculation of the echo spectrum number Y′(f′) of the scattered sound field in the motion space and the time-domain echo y′(t′) of the scattered sound field in the motion space is as follows:

[0031] Y′(f′) = H′(f′)·S′(f′)

[0032]

[0033] According to a non-rigid target acoustic scattering micro-Doppler feature prediction system provided by the present invention, it includes the following modules:

[0034] Module M1: Obtain the scattered sound field of the non-rigid target;

[0035] Module M2: Predict the non-rigid target acoustic scattering micro-Doppler feature according to the scattered sound field.

[0036] Preferably, the module M1 includes the following modules:

[0037] Information acquisition module: Establish a moving target model according to the shape and motion law of the non-rigid target, obtain the receiving and transmitting position information from the relative position between the transceiver and the target, perform grid meshing on the moving target model and extract the moving grid to obtain the grid information and velocity vector of each part of the non-rigid target;

[0038] Incident wave frequency response function acquisition module: According to the velocity vector and receiving and transmitting position information in the information acquisition module, transform the incident signal in the static space to obtain the incident signal in the motion space, and transform the incident signal in the motion space to obtain the incident wave frequency response function in the motion space;

[0039] Scattered sound field frequency response function acquisition module: According to the grid information in the information acquisition module, obtain the impulse response function of the scattered sound field of each grid in the motion space, and obtain the frequency response function of the scattered sound field in the motion space according to the impulse response function of the scattered sound field in the motion space;

[0040] Scattered sound field time-domain echo acquisition module: Obtain the echo spectrum number of the scattered sound field in the moving space from the incident wave frequency response function in the moving space and the scattered sound field frequency response function in the moving space, and transform the echo spectrum number of the scattered sound field in the moving space to obtain the scattered sound field time-domain echo in the moving space;

[0041] Total scattered sound field acquisition module: Transform the scattered sound field time-domain echo in the moving space to obtain the scattered sound field in the static space, and accumulate the scattered sound fields of each grid in the moving space and the static space to obtain the total scattered sound field.

[0042] Preferably, in the incident wave frequency response function acquisition module, the incident signal s(t) in the static space, where t is the time quantity in the static space; use the Lorentz transformation to obtain the incident signal s′(t′) in the moving space, where t′ is the time quantity in the moving space; perform Fourier transform on the incident signal s′(t′) in the moving space to obtain the incident wave frequency response function S′(f′) in the moving space, where f′ is the frequency quantity in the moving space.

[0043] Preferably, in the incident wave frequency response function acquisition module, the relationship between t′ in the moving space and t in the static space is:

[0044]

[0045] where v represents the product of the grid movement velocity vector and the unit vector from the grid center point to the receiving and transmitting unit, and c represents the sound speed in water.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. The present invention is applicable to the acoustic scattering simulation of non-rigid moving targets, enabling physical acoustics methods to be used to analyze the micro-motion characteristics of non-rigid moving target acoustic scattering;

[0048] 2. Compared with traditional methods, the present invention can accurately simulate the micro-Doppler characteristics generated during the movement of non-rigid targets, thus providing an effective method for analyzing the characteristics of non-rigid moving targets;

[0049] 3. Applying the present invention can analyze the micro-motion characteristics, especially the micro-Doppler characteristics, caused during the movement of non-rigid targets better than traditional methods, thus providing support for the detection and recognition of non-rigid targets by active sonar;

[0050] 4. For non-rigid moving targets such as frogmen and aquatic organisms, based on traditional methods, dynamic mesh subdivision and Lorentz transformation are used to simulate the micro-Doppler characteristics of the scattered sound fields of moving frogmen and underwater acoustic organisms. Therefore, applying the present invention can carry out more comprehensive and detailed target characteristic analysis on underwater targets with micro-motion characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Other features, objects, and advantages of the present invention will become more apparent by reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0052] Figure 1 It is a model diagram of a moving frogman of the present invention;

[0053] Figure 2 It is a mesh model subdivision diagram of a moving frogman of the present invention;

[0054] Figure 3 It is a process flow diagram of the prediction of the present invention;

[0055] Figure 4 It is a time-domain echo diagram of the sound scattering of a moving frogman of the present invention;

[0056] Figure 5 It is a sound scattering frequency spectrum diagram of a moving frogman of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those of ordinary skill in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0058] An embodiment of the present invention discloses a method for predicting the micro-Doppler characteristics of sound scattering of non-rigid targets, as Figure 1 and Figure 2 shown, including the following steps: Step S1: Obtain the scattered sound field of the non-rigid target. Step S1 includes the following steps: Information acquisition step: Establish a moving target model according to the shape and movement law of the non-rigid target, obtain the received and transmitted position information from the relative position between the transceiver device and the target, perform mesh subdivision on the moving target model and extract the dynamic mesh, and obtain the mesh information and velocity vector of each part of the non-rigid target.

[0059] According to the shape and movement law of the frogman, use MAYA to establish a three-dimensional moving frogman model and set the movement laws of each part of the model, as Figure 1 shown. MAYA represents Maya software, which is three-dimensional modeling and animation software.

[0060] First, establish a moving frogman model according to the shape and movement law of the frogman. Use a script program to segment the movement process of the frogman and ensure that the time interval is small enough. The minimum time interval can be determined according to the minimum frequency resolution of the incident signal. Further, carry out grid meshing and extract the dynamic grid to obtain the grid information and movement speed vector of each part of the frogman. Because the shape structure of the model changes continuously during the movement process, ordinary grid meshing will divide different shapes into different grids, and the total number and size of the grids will change. The dynamic grid specifically refers to the situation where although the shape structure changes, the total number of grids remains unchanged and the change in grid size is very small. This is a professional term in the industry.

[0061] Perform grid meshing on the model in regions, discretize the surface of the frogman into triangular grids of similar size, and the dynamic grid includes triangular grids. Since the modeling is to model the frogman's limbs separately and add movement methods. Therefore, after grid meshing, all grids at different times can correspond one by one, reflecting the local displacement during the movement process of the frogman, such as Figure 2 shown.

[0062] Export the grids at different times in the format of the model standard file.obj by writing a MAYA script program. According to the reading method of the.obj format, the displacement vector of the same triangular grid at different times can be calculated, and the speed vector of each triangular grid can be obtained by substituting the interval time.

[0063] Steps to obtain the incident wave frequency response function: According to the speed vector and the receiving and transmitting position information in the information acquisition step, transform the incident signal in the static space to obtain the incident signal in the moving space, and then transform the incident signal in the moving space to obtain the incident wave frequency response function in the moving space. The incident signal s(t) in the static space, where t is the time quantity in the static space; use the Lorentz transformation to obtain the incident signal s′(t′) in the moving space, where t′ is the time quantity in the moving space; use the Fourier transformation on the incident signal s′(t′) in the moving space to obtain the incident wave frequency response function S′(f′) in the moving space, where f′ is the frequency quantity in the moving space.

[0064] The relationship between t′ in the moving space and t in the static space is:

[0065]

[0066] where v represents the product of the grid movement speed vector and the unit vector from the grid center point to the receiving and transmitting point, and c represents the sound speed in water.

[0067] According to the speed vector of the grid in the information acquisition step And receive the transmitting and receiving position information, and use Lorentz transformation on the incident signal s(t) in the stationary space to obtain the incident signal s′(t′) in the moving space. Among them v is the relative velocity of the grid with respect to the transmitting and receiving. Further, use Fourier transform on s′(t′) to obtain the frequency response function S′(f′) of the incident wave in the moving space, that is, the incident signal spectrum S′(f′) in the moving space. The moving space is relative to the stationary space.

[0068] Steps for obtaining the frequency response function of the scattered sound field: According to the grid information in the information acquisition step, obtain the impulse response function of the scattered sound field of each grid in the moving space, and obtain the frequency response function of the scattered sound field in the moving space based on the impulse response function of the scattered sound field in the moving space.

[0069] Use Fourier transform on the impulse response function h′(τ′) of the scattered sound field of each grid in the moving space to obtain the frequency response function H′(f′) of the scattered sound field in the moving space. τ′ represents the time variable in the system impulse response function; that is, the quantity representing time in the system impulse response function, also known as the process time.

[0070] The relationship between the impulse response function h′(τ′) of the scattered sound field of each grid in the moving space and the frequency response function H′(f′) of the scattered sound field in the moving space is:

[0071]

[0072] Among them, e represents the natural exponent, and i represents the imaginary number.

[0073] According to the grid information in the information acquisition step, use the physical acoustics method to obtain the impulse response function h′(τ′) of the scattered sound field of each grid in the moving space, and use the method of Fourier transform to obtain the frequency response function H′(f′) of the scattered sound field.

[0074] Steps for obtaining the time-domain echo of the scattered sound field: Obtain the echo spectrum number of the scattered sound field in the moving space from the incident wave frequency response function and the frequency response function of the scattered sound field in the moving space, and transform the echo spectrum number of the scattered sound field in the moving space to obtain the time-domain echo of the scattered sound field in the moving space.

[0075] Use inverse Fourier transform on the echo spectrum number Y′(f′) of the scattered sound field in the moving space to obtain the time-domain echo y′(t′) of the scattered sound field in the moving space. The calculation of the echo spectrum number Y′(f′) of the scattered sound field in the moving space and the time-domain echo y′(t′) of the scattered sound field in the moving space is:

[0076] Y′(f′) = H′(f′)·S′(f′)

[0077]

[0078] Multiply the incident wave frequency response function S′(f′) in the moving space in the step of obtaining the frequency response function of the scattered sound field by the scattered sound field frequency response function H′(f′) in the moving space in step (3) to obtain the echo spectrum number Y′(f′) of the scattered sound field in the moving space, and further use the inverse Fourier transform to obtain the time-domain echo y′(t′) of the scattered sound field in the moving space.

[0079] Step of obtaining the total scattered sound field: Transform the time-domain echo of the scattered sound field in the moving space to obtain the scattered sound field in the stationary space, and accumulate the scattered sound fields of each grid in the moving space and the stationary space to obtain the total scattered sound field.

[0080] First, give the incident signal s(t) in the stationary space, and according to the velocity vector of each grid relative to the transceiver Use the Lorentz transformation on s(t) to obtain the incident signal s′(t′) in the moving space, and then calculate the impulse response function h′(τ′) of each grid in the moving space based on the physical acoustics method. Furthermore, obtain the time-domain scattered echo signal y′(t′) in the moving space through time-frequency transformation, and use the Lorentz transformation again to obtain the time-domain scattered echo signal y(t) in the stationary space. Finally, add up the scattered echoes of all grids to obtain the total scattered echo that fully contains the micro-motion characteristics of the diver's limbs. As Figure 3 shown, y′(t′) represents the time-domain scattered echo signal in the moving space, that is, the time-domain echo of the scattered sound field in the moving space; y(t) represents the time-domain scattered echo signal in the stationary space, that is, the scattered sound field in the stationary space; the total scattered echo is the total scattered sound field.

[0081] Use the Lorentz transformation on y′(t′) in the step of obtaining the time-domain echo of the scattered sound field to obtain the scattered sound field y(t) in the stationary space. Finally, accumulate the scattered sound fields of each grid to obtain the total scattered sound field.

[0082] Step S2: Predict the micro-Doppler characteristics of non-rigid target acoustic scattering according to the scattered sound field.

[0083] By comparing with the traditional underwater target acoustic scattering simulation method, the effects achieved by the method of the present invention are illustrated. Use a sinusoidal frequency-modulated signal as the incident wave. In order to obtain sufficient frequency resolution, a transmit signal with a center frequency of 1.2 MHz and a pulse width of 4.2 ms is used. According to Figure 3 the process, use the method of the present invention and the traditional underwater target acoustic scattering simulation method to calculate the acoustic scattering echoes of divers in different postures respectively. There are 399 pulses in one leg-swing cycle of the diver. The calculation results are as Figure 4 shown. Figure 4 The abscissa is the number of pulses, that is, the echo obtained from one pulse. In this example, the diver completes one thigh cycle and a total of 399 echoes are obtained. Figure 4Indicates the time-domain echo of the scattered sound of a moving frog's voice, Figure 4 On the left side of (a) in [figure] is the calculation result of the present invention, Figure 4 and on the right side of (b) is the calculation result of the traditional simulation method. Fourier transform is performed on the Figure 4 result to obtain the spectrogram of the time-domain echo, as shown in Figure 5 [figure], Figure 5 which is the spectrogram of the scattered sound frequency of the moving frog's voice. Figure 5 On the left side of (a) in [figure] is the calculation result of the present invention, Figure 5 and on the right side of (b) in [figure] is the calculation result of the traditional simulation method. By comparison, it can be seen that Figure 5 (a) has obvious micro-Doppler characteristics.

[0084] The embodiment of the present invention also discloses a non-rigid target acoustic scattering micro-Doppler feature prediction system, which includes the following modules: Module M1: Obtain the scattering sound field of the non-rigid target. Module M1 includes the following modules: Information acquisition module: Establish a moving target model according to the shape and motion law of the non-rigid target, obtain the receiving and transmitting position information from the relative position between the transceiver and the target, perform grid division on the moving target model and extract the dynamic grid to obtain the grid information and velocity vector of each part of the non-rigid target.

[0085] Incident wave frequency response function acquisition module: According to the velocity vector and receiving and transmitting position information in the information acquisition module, transform the incident signal in the static space to obtain the incident signal in the moving space, and transform the incident signal in the moving space to obtain the incident wave frequency response function in the moving space. The incident signal s(t) in the static space, where t is the time quantity in the static space; use the Lorentz transformation to obtain the incident signal s′(t′) in the moving space, where t′ is the time quantity in the moving space; perform Fourier transform on the incident signal s′(t′) in the moving space to obtain the incident wave frequency response function S′(f′) in the moving space, where f′ is the frequency quantity in the moving space.

[0086] The relationship between t′ in the moving space and t in the static space is:

[0087]

[0088] where v represents the product of the grid movement velocity vector and the unit vector from the grid center point to the receiving and transmitting unit, and c represents the sound speed in water.

[0089] Scattering sound field frequency response function acquisition module: According to the grid information in the information acquisition module, obtain the impulse response function of the scattering sound field of each grid in the moving space, and obtain the frequency response function of the scattering sound field in the moving space according to the impulse response function of the scattering sound field in the moving space.

[0090] Scattering sound field time-domain echo acquisition module: Obtain the echo spectrum number of the scattering sound field in the motion space from the incident wave frequency response function in the motion space and the scattering sound field frequency response function in the motion space, and transform the echo spectrum number of the scattering sound field in the motion space to obtain the time-domain echo of the scattering sound field in the motion space.

[0091] Total scattering sound field acquisition module: Transform the time-domain echo of the scattering sound field in the motion space to obtain the scattering sound field in the static space, and accumulate the scattering sound fields of each grid in the motion space and the static space to obtain the total scattering sound field.

[0092] Module M2: Predict the acoustic scattering micro-Doppler characteristics of non-rigid targets based on the scattering sound field.

[0093] In order to make up for the defects of the current underwater target characteristic prediction method in predicting the acoustic scattering of the motion characteristics of non-rigid targets, the present invention introduces a dynamic grid meshing method and Lorentz transformation on the basis of traditional physical acoustics, and can reflect the acoustic scattering simulation of the micro-Doppler effect caused by the motion of non-rigid targets. The present invention is applicable to the analysis of the acoustic scattering target characteristics of underwater non-rigid targets. The present invention first gives a dynamic grid meshing method applicable to underwater complex targets, combines physical acoustics and Lorentz transformation to obtain the acoustic scattering simulation of underwater micro-motion targets, and can accurately simulate the micro-motion characteristics of underwater non-rigid targets, especially the micro-Doppler characteristics. Moreover, the method of the present invention has a fast calculation speed and is easy to implement, and is expected to be widely applied to the research field of the acoustic scattering target characteristics of underwater frogmen and underwater acoustic organisms. The present invention provides help for the theoretical analysis of the characteristics of underwater non-rigid targets and is a basic scientific research achievement in data. The present invention is particularly aimed at targets whose geometric shapes will change significantly during the motion process, such as frogmen and aquatic organisms. Taking frogmen as an example, through the dynamic modeling and dynamic grid meshing of moving frogmen, the velocity vectors of each part of the frogmen can be accurately obtained. Based on physical acoustics and Lorentz transformation, the scattering sound fields of each moving grid are calculated separately and summed to obtain the total scattering sound field. The present invention is applicable to the field of analysis of the acoustic scattering target characteristics of underwater moving targets with micro-motion characteristics.

[0094] The present invention aims at an acoustic scattering simulation method applicable to non-rigid moving targets, enabling the physical acoustics method to be used to analyze the micro-motion characteristics of the acoustic scattering of non-rigid moving targets. Compared with the traditional method, the present invention can accurately simulate the micro-Doppler characteristics generated during the motion of non-rigid targets, thus providing an effective method for the analysis of the characteristics of non-rigid moving targets. Therefore, applying the method of the present invention can better analyze the micro-motion characteristics, especially the micro-Doppler characteristics, caused by the motion of non-rigid targets than the traditional method, thus providing support for the detection and identification of non-rigid targets by active sonar.

[0095] Those skilled in the art know that, in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc., to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a kind of hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or structures within the hardware component.

[0096] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for predicting the micro-Doppler characteristics of acoustic scattering from non-rigid targets, characterized in that, It includes the following steps: Step S1: Obtain the scattered sound field of the non-rigid target; Step S2: Predict the acoustic scattering micro-Doppler characteristics of the non-rigid target according to the scattered sound field; The said Step S1 includes the following steps: Information acquisition step: Establish a moving target model according to the shape and motion law of the non-rigid target, obtain the receiving and transmitting position information from the relative position between the transceiver and the target, perform grid division on the moving target model and extract the dynamic grid to obtain the grid information and velocity vector of each part of the non-rigid target; Incident wave frequency response function acquisition step: According to the velocity vector and receiving and transmitting position information in the information acquisition step, transform the incident signal in the stationary space to obtain the incident signal in the moving space, and transform the incident signal in the moving space to obtain the incident wave frequency response function in the moving space; Scattered sound field frequency response function acquisition step: According to the grid information in the information acquisition step, obtain the impulse response function of the scattered sound field of each grid in the moving space, and obtain the scattered sound field frequency response function in the moving space according to the impulse response function of the scattered sound field in the moving space; Scattered sound field time-domain echo acquisition step: Obtain the echo spectrum number of the scattered sound field in the moving space by using the incident wave frequency response function in the moving space and the scattered sound field frequency response function in the moving space, and transform the echo spectrum number of the scattered sound field in the moving space to obtain the scattered sound field time-domain echo in the moving space; Total scattered sound field acquisition step: Transform the scattered sound field time-domain echo in the moving space to obtain the scattered sound field in the stationary space, and accumulate the scattered sound fields of each grid in the moving space and the stationary space to obtain the total scattered sound field; In the said incident wave frequency response function acquisition step, the incident signal s(t) in the stationary space, where t is the time quantity in the stationary space; use the Lorentz transformation to obtain the incident signal s′(t′) in the moving space, where t′ is the time quantity in the moving space; use the Fourier transformation on the incident signal s′(t′) in the moving space to obtain the incident wave frequency response function S′(f′) in the moving space, where f′ is the frequency quantity in the moving space; In the said incident wave frequency response function acquisition step, the relationship between t′ in the moving space and t in the stationary space is: where v represents the grid motion velocity vector multiplied by the unit vector from the grid center point to the transceiver, and c represents the sound speed in water.

2. The method for predicting the micro-Doppler characteristics of acoustic scattering from non-rigid targets according to claim 1, characterized in that, In the said scattered sound field frequency response function acquisition step, use the Fourier transformation on the impulse response function h′(τ′) of the scattered sound field of each grid in the moving space to obtain the scattered sound field frequency response function H′(f′) in the moving space, where τ′ represents the time variable in the system impulse response function; The relationship between the impulse response function h′(τ′) of the scattered sound field of each grid in the moving space and the scattered sound field frequency response function H′(f′) in the moving space is: where, e represents the natural exponent, and i represents the imaginary number.

3. The method for predicting the micro-Doppler characteristics of acoustic scattering from non-rigid targets according to claim 1, characterized in that, In the said scattered sound field time-domain echo acquisition step, use the inverse Fourier transformation on the echo spectrum number Y′(f′) of the scattered sound field in the moving space to obtain the scattered sound field time-domain echo y′(t′) in the moving space; The calculation of the echo spectrum number Y′(f′) of the scattered sound field in the moving space and the scattered sound field time-domain echo y′(t′) in the moving space is: Y′(f′) = H′(f′)·S′(f′) 4. A system for predicting the micro-Doppler characteristics of acoustic scattering from non-rigid targets, characterized in that, It includes the following modules: Module M1: Obtain the scattered sound field of a non-rigid target; Module M2: Predict the acoustic scattering micro-Doppler characteristics of a non-rigid target based on the scattered sound field; The said Module M1 includes the following modules: Information acquisition module: Establish a moving target model according to the shape and motion law of the non-rigid target, obtain the receiving and transmitting position information from the relative position between the transceiver and the target, perform grid meshing on the moving target model and extract the moving grid to obtain the grid information and velocity vector of each part of the non-rigid target; Incident wave frequency response function acquisition module: According to the velocity vector and receiving and transmitting position information in the information acquisition module, transform the incident signal in the static space to obtain the incident signal in the moving space, and transform the incident signal in the moving space to obtain the incident wave frequency response function in the moving space; Scattered sound field frequency response function acquisition module: According to the grid information in the information acquisition module, obtain the impulse response function of the scattered sound field of each grid in the moving space, and obtain the scattered sound field frequency response function in the moving space based on the impulse response function of the scattered sound field in the moving space; Scattered sound field time-domain echo acquisition module: Obtain the echo spectrum number of the scattered sound field in the moving space from the incident wave frequency response function and the scattered sound field frequency response function in the moving space, and transform the echo spectrum number of the scattered sound field in the moving space to obtain the scattered sound field time-domain echo in the moving space; Total scattered sound field acquisition module: Transform the scattered sound field time-domain echo in the moving space to obtain the scattered sound field in the static space, and accumulate the scattered sound fields of each grid in the moving space and the static space to obtain the total scattered sound field; In the said incident wave frequency response function acquisition module, the incident signal s(t) in the static space, where t is the time quantity in the static space; use the Lorentz transformation to obtain the incident signal s′(t′) in the moving space, where t′ is the time quantity in the moving space; use the Fourier transformation on the incident signal s′(t′) in the moving space to obtain the incident wave frequency response function S′(f′) in the moving space, where f′ is the frequency quantity in the moving space; In the said incident wave frequency response function acquisition module, the relationship between t′ in the moving space and t in the static space is: where v represents the grid movement velocity vector multiplied by the unit vector from the grid center point to the transceiver, and c represents the sound speed in water

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