A high-fidelity and high-efficiency calculation method, system, device and medium for laser scattering characteristics of sea surface and targets under high sea conditions

Abstract

A high-fidelity and high-efficiency calculation method, system, device and medium for laser scattering characteristics of sea surface and target under high sea conditions, the method comprises the following steps: decomposing the high sea condition sea surface into a composite structure of a nonlinear rough sea surface layer and a white wave foam layer, and constructing a high sea condition sea surface geometric model; constructing the optical characteristics of the high sea condition sea surface geometric model: constructing a traditional circular symmetric Gaussian beam model and an ultra-Gaussian fan beam model based on a Powell prism shaping; based on the high sea condition sea surface geometric model and the optical characteristics of the high sea condition sea surface geometric model, combining a laser radar equation, using a laser pulse Gaussian time domain waveform, introducing a ray tracing method to determine a three-dimensional shielding relationship, establishing a composite discrete time domain integral model, and obtaining a target and sea clutter composite time domain waveform through time and space solving and energy superposition; the system, device and medium are used for realizing the method; the method has the advantages of high sea surface geometric modeling precision, fast scattering calculation speed, strong detection system adaptability, outstanding engineering application value and the like.

Description

Technical Field

[0001] This invention belongs to the field of lidar technology, and specifically relates to a high-fidelity and efficient calculation method, system, device and medium for the laser scattering characteristics of the sea surface and the target under high sea conditions. Background Technology

[0002] Laser detection systems (such as lidar and laser fuses) have been widely used in maritime surveillance, low-altitude air defense, and missile defense due to their high precision and strong anti-interference capabilities. However, in complex marine environments, high sea states (high wind speeds) can cause violent wave fluctuations and generate large areas of whitecaps and foam layers. The foam layer, composed of numerous tiny bubbles, is a polydisperse medium that exhibits a strong volumetric diffuse reflection (Mie scattering) effect on lasers, drastically increasing the background power of sea clutter. To evaluate and improve the anti-interference performance of laser detection equipment under harsh sea conditions, high-fidelity and high-efficiency simulations of the composite laser scattering echoes from "high-sea-state foamy sea surfaces and sea-skimming targets" must be conducted during the equipment development phase.

[0003] Currently, the mainstream technical solutions for simulating laser scattering characteristics and calculating sea clutter at high sea states mainly include the following steps and methods: In the area of ​​geometric extraction of sea surface foam: Li Dongfang (Li Dongfang. Research on Electromagnetic Scattering Characteristics of Nonlinear Sea Surfaces [D]. University of Electronic Science and Technology of China, 2021.) established a sea surface model for studying the electromagnetic scattering characteristics of nonlinear sea surfaces, using a surface slope threshold criterion to distinguish between wave crest foam and static foam, and determining the breakage location based on the slope order. Zou Junfeng (Zou Junfeng. Research on Real-time Infrared Simulation of Large-Scale Marine Scenes [D]. Xi'an University of Electronic Science and Technology, 2022.) used sea surface vertices as the discrimination unit in modeling and simulating marine scenes, and identified all vertices with heights greater than a certain value H and normal angles exceeding a set threshold as the determination location for sea surface foam generation. Existing technologies typically use fixed geometric thresholds (such as fixed wave height thresholds or fixed surface slope thresholds) to directly extract rough sea surfaces, directly marking areas exceeding this fixed threshold as foam-covered areas.

[0004] In the calculation of optical scattering in foam layers: Hou Yonghua (Hou Yonghua. Study on scattering characteristics of 905nm laser on sea surface [D]. Nanjing University of Science and Technology, 2025.) calculated the optical transmission parameters of two foam layers using Mie scattering theory and foam particle scale distribution in the calculation of laser scattering on sea surface, simulated the scattering process of 905nm laser on foam layer, and calculated the bidirectional reflection distribution function under different incident angles. Zhou Qian (Zhou Qian et al. Calculation and analysis of radiation scattering direction-spectral characteristics of typical multi-scale sea surface structures [J]. Journal of Harbin Institute of Technology, 2024) also relied on Mie scattering theory and foam particle scale distribution to construct a calculation model of sea surface spectral characteristics and analyzed the influencing factors of radiation scattering direction-spectral characteristics of structures. Existing technology usually directly adopts Monte Carlo photon tracking algorithm. That is, in system-level scene simulation, a large number of photons are emitted, and the multiple random walks, collisions, absorption and scattering processes of each photon in millions of foam particles are calculated in real time, and finally the energy of the emitted photons is statistically analyzed.

[0005] In summary, existing simulation schemes for the laser scattering characteristics of the sea surface and targets under high sea states have shortcomings in both foam geometry extraction and optical scattering solution, making it difficult to balance the fidelity of sea surface modeling with the computational efficiency of large-scale simulations. Specifically: Defect 1: Low accuracy of geometric modeling of high sea state sea surface, unable to adapt to dynamic sea conditions, resulting in distorted environmental simulation.

[0006] Current technologies use a fixed threshold to extract foam, while the whitecaps and foam coverage in the real ocean vary with conditions such as wind speed. A fixed threshold cannot adapt to dynamically evolving sea conditions, leading to excessive accumulation or severe loss of foam areas, violating macroscopic statistical laws, and consequently distorting the generated simulated sea surface environment.

[0007] Defect 2: Ray tracing has extremely high computational complexity, making it difficult to meet the real-time requirements of large-scale scene and system-level simulation.

[0008] Due to the extremely thick optical thickness of the foam layer in high sea states, photons undergo intense multi-volume scattering within it. Current techniques perform real-time microscopic Monte Carlo photon calculations during system-level ray tracing. This results in exponentially increasing computational overhead and memory usage, leading to extremely slow simulation response times and rendering it unsuitable for simulating complex, large-scale scenes and long-term processes. Summary of the Invention

[0009] To overcome the shortcomings of the prior art, the present invention aims to provide a high-fidelity and efficient calculation method, system, device, and medium for the laser scattering characteristics of the sea surface and target under high sea states. First, by introducing a sea spectrum model and nonlinear transformation, combined with Jacobian matrix and slope determination, foam distribution region division is achieved, solving the problem of foam extraction distortion and realizing accurate foam distribution matching, effectively improving the fidelity of composite sea surface modeling. Second, a reduced-dimensional foam bidirectional reflectance distribution function (BRDF) lookup table based on Monte Carlo pre-calculation is established, replacing real-time microscopic spectral tracking calculation with hybrid interpolation calls during ray tracing, overcoming the slow speed of traditional simulation calculations, significantly reducing computational overhead, and improving the efficiency of large-scale scene simulation. Finally, by combining different Gaussian light fields and ray tracing algorithms, the composite interaction process between sea-skimming targets and high sea states is solved, generating high-fidelity target and sea clutter composite time-domain waveforms, providing solid simulation data support for performance evaluation, anti-interference algorithm verification, and system parameter optimization of sea-based electro-optical detection equipment such as lidar and laser fuses.

[0010] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A high-fidelity and efficient method for calculating the laser scattering characteristics of the sea surface and the target under high sea states includes the following steps: Step 1: Decompose the high sea level sea surface into a composite structure of a nonlinear rough sea surface layer and a white wave foam layer, and construct a geometric model of the high sea level sea surface. Step 2: Constructing the optical properties of a high-sea-state sea surface geometry model: Scattering models were developed for the nonlinear rough sea surface layer and the white wave foam layer. The nonlinear rough sea surface layer adopted a specular scattering model based on Fresnel reflection theory. For the white wave foam layer, a physical model was first constructed and the volume scattering parameters were calculated. Then, the four-dimensional bidirectional reflection distribution function tensor of the foam was obtained through Monte Carlo simulation. The dimensionality was reduced by combining the isotropic characteristics of the azimuth angle and a BRDF lookup table was constructed. Finally, a hybrid interpolation algorithm was used to obtain the foam BRDF value at any detection angle. Step 3: Construct a traditional circularly symmetric Gaussian beam model and a super-Gaussian fan-shaped beam model based on Powell prism shaping; based on the optical characteristics of the high-sea-state surface geometry model constructed in Step 1 and Step 2, and combined with the lidar equation, use the Gaussian time-domain waveform of the laser pulse, introduce the ray tracing method to determine the three-dimensional occlusion relationship, establish a composite discretized time-domain integral model, and obtain the composite time-domain waveform of the target and sea clutter through spatiotemporal solution and energy superposition.

[0011] The specific method of step 1 includes: (1) Constructing a nonlinear rough sea surface layer The Fourier expansion of the sea surface height field is: (32) in, for The Fourier complex amplitude of the sea surface height field at time t. The initial spatial coordinates of the sea surface. It is a two-dimensional wavenumber vector. The imaginary unit; The Elfouhaily spectrum is subjected to a Choppy nonlinear transform; firstly, the horizontal displacement field is calculated in the frequency domain, and then the sea surface horizontal displacement field is transformed into the spatial domain through an inverse fast Fourier transform. (33) Initial spatial coordinates After displacement field perturbation, a new nonlinear horizontal coordinate is obtained. The expression is: (34) in, This is the chopping factor, used to control the degree of nonlinear compression of waves. and These are the displacement components in the x and y directions, respectively; (2) Based on the Monahan foam coverage model, construct the geometric model of the white wave foam layer; The coverage of sea surface foam is determined by the wind speed at a height of 10m above the sea surface. Temperature difference with sea temperature It was jointly decided to divide the foam on the sea surface into two categories: Phase A, peak wave foam, and Phase B, static foam, with a total foam coverage rate of [missing information]. Phase A peak wave foam coverage and Phase B static foam coverage They respectively satisfy the following empirical relations: (35) (36) (37) By normalizing the weight allocation, the target area that the peak wave foam of stage A and the static foam of stage B should occupy in the nonlinear rough sea surface layer under the current sea state is calculated. and : (38) in, The area of ​​the nonlinear rough sea surface layer; The local deformation rate of the nonlinear rough sea surface layer is measured to determine the location distribution of stage A peak wave foam on the nonlinear rough sea surface layer: (39) The smaller the value of the Jacobian determinant, the more severe the compression of the water body; the threshold for determining peak wave foam in stage A is set as follows. Then the set of surface mask elements for the peak wave foam in stage A. satisfy: (40) The location distribution of residual stage B static foam on the nonlinear rough sea surface layer is determined by using the macroscopic geometric slope S(x, y): (41) in, The height of the nonlinear rough sea surface layer after Choppy transformation; Set the static foam threshold for stage B as follows: Its surface mask set satisfy: (42) Based on the positional distribution of peak wave foam in stage A and static foam in stage B on the nonlinear rough sea surface layer, a two-dimensional Gaussian kernel function is used to smooth the displacement field and height field to obtain a geometric model of the high sea state sea surface.

[0012] Step 2, the specific method for scattering modeling of the nonlinear rough sea surface layer, includes: The sea surface is discretized into several micro-surface elements, where the scattering behavior of a single micro-surface element can be equivalent to a local planar specular reflection process and satisfies Fresnel's law of reflection. Assuming the incident light is isotropic, according to Fresnel's reflection theory, the ratio of the scattered field intensity to the incident field intensity of the micro-surface element is characterized by the Fresnel reflection coefficient: (43) in, The laser incident angle, The laser emission angle is... , is the polarization amplitude reflection coefficient.

[0013] Step 2, which involves constructing a physical model of the white foam layer and calculating the volume scattering parameters, includes the following specific methods: The Reul empirical model was used to determine the thickness of the wind-driven macroscopic white wave foam layer, and the white wave foam layer was simplified into a three-layer parallel flat plate structure with uniform thickness and linear porosity with depth. Treating a single foam particle as a double-layered hollow sphere, the single-shot optical scattering parameters are solved based on Mie theory. The single-particle scattering characteristics are then integrated over the entire log-normal particle size distribution using a ensemble average to obtain macroscopic volume scattering parameters, including the extinction coefficient. Scattering coefficient absorption coefficient and asymmetric factors ; (44) (45) (46) (47) (48) (49) in: (50) (51) (52) in: These are parameters related to the size of the foam particles. Let be the order of the Mie scattering expansion. , The Mie scattering coefficient is... , , In order, they are single-particle extinction, scattering, and absorption efficiency factors. The asymmetry factor of the foam particles. The single-scattering albedo of the foam particles, Where is the radius of the foam particles. The volume fraction of the foam layer medium. Let be the particle size distribution function of the foam particles. The concentration of foam particles, Let be the particle size distribution function of the foam particles. Minimum and maximum radii of the foam particle size distribution. Let be the geometric mean radius of the foam particles. This represents the geometric standard deviation of the foam particle size distribution.

[0014] In step 2, the four-dimensional bidirectional reflectance distribution function (BRDF) tensor of the white wave foam layer is obtained through Monte Carlo simulation. Dimensionality reduction is achieved by combining azimuth isotropy, and a BRDF lookup table is constructed. A hybrid interpolation algorithm is used to obtain the foam BRDF value at any detection angle. Specifically, the method includes: using Monte Carlo simulation to model the multipath random walk of the beam within the white wave foam layer, the air-sea interface interaction, and self-occlusion correction based on the annihilation factor of the error function. Finally, the photons escaping from the upper surface of the white wave foam layer and captured by the receiving solid angle are statistically analyzed. The four-dimensional bidirectional reflectance distribution function (BRDF) tensor of the white wave foam layer is calculated as follows: (53) in, From The total number of photons incident on the foam surface in the direction of incidence. In solid angle The number of photons received reduces the four-dimensional bidirectional reflectance distribution function (BRDF) tensor of the white foam layer to three dimensions: (twenty three) in, ; ; By traversing all incident direction meshes and performing extensive photon tracing, a complete 3D tensor lookup table is obtained. A hybrid interpolation algorithm is used to obtain the foam BRDF value at any detection angle.

[0015] The process of obtaining the foam BRDF value at any detection angle using a hybrid interpolation algorithm is as follows: First, calculate the incident zenith angle of the incident ray in the local tangent space of the current white wave foam layer element. With azimuth And determine the zenith angle of the launch direction based on the detection requirements. relative azimuth ; In a three-dimensional tensor lookup table In the middle, find the angle of incidence that matches the current query. Discrete grid node with the smallest absolute error As a matching layer, The index m is determined by the following formula: (54) in, For 3D tensor lookup tables The number of discrete grids at the incident zenith angle. Let be the incident zenith angle value corresponding to the k-th grid node; reduce the 3D spatial interpolation problem to a fixed incident zenith angle. Two-dimensional data slices In progress; At the matching angle of incidence At the level of querying the launch direction Using bilinear interpolation, the four adjacent nodes surrounding the exit direction in the two-dimensional grid are located. Falling in the range , Falling in the range ; Calculate the normalized weighting factor based on angular distance: (55) The final BRDF value to be determined for the foam It is an exact approximation by the weighted sum of the four surrounding discrete BRDF values: (56) in, Equivalent to elements in a 3D tensor lookup table .

[0016] The specific method for step 3 includes: Two spatial illuminance distribution models were constructed: a traditional circularly symmetric Gaussian beam model and a super-Gaussian fan-shaped beam model based on Powell prism shaping, to accurately characterize the energy distribution of the laser beam across its cross-section. : (1) Constructing a traditional circularly symmetric Gaussian beam model For traditional narrow-beam spot illumination systems, the laser energy in space follows an ideal Gaussian decay law of the fundamental mode. Let the effective beam radius be... Its spatial illuminance distribution is as follows: (57) in, Spatial coordinates The peak power of the laser pulse. is the Gaussian beam radius (beam waist radius) at a distance z from the emitting end; (2) Constructing a super-Gaussian fan-shaped beam model based on Powell prism shaping By introducing a super-Gaussian function to fit the true flat-top distribution, assuming the laser undergoes shaping along the Y-axis and maintains its fundamental mode along the X-axis, the corrected mixed-space illuminance distribution is as follows: (58) In the formula, Let z be the peak light intensity at a propagation distance z. It is a super-Gaussian order. and These are the beam length and minor axis widths corresponding to the depth. The dynamic peak light intensity is derived from the conservation of total emitted power: (59) in, It is a gamma function; Meanwhile, let the Gaussian time-domain waveform of the pulse emitted by the laser be... It usually follows a Gaussian distribution: (60) in, The moment of laser pulse emission. This refers to the laser pulse width parameter; Based on the lidar equation, the power of the laser backscattered echo collected by the receiving system is jointly determined by the environmental parameters of the high-sea-state sea surface geometric model, the optical characteristics of the high-sea-state sea surface geometric model, and the geometric relationship of the detector. A ray tracing method is introduced to determine the complex three-dimensional occlusion relationship between the undulating sea surface and the sea-skimming target. The composite discretized time-domain integral model collected by the receiving system at time t can be expressed as: (61) in, Let be the straight-line distance from the i-th surface element to the radar. The speed of light in a vacuum. To achieve the effective receiving area of ​​the receiving antenna, Atmospheric transport attenuation, For the incident projection of the surface element, Let i be the area of ​​the i-th face element. Based on the radar system of the specific simulation scenario, one of the two spatial illumination distribution models mentioned above is substituted into the model. By performing spatiotemporal calculation and superposition of the visible surface echo energy within each range gate in the time domain, the composite time domain waveform of the target and sea clutter can be obtained.

[0017] This invention also provides a high-fidelity and high-efficiency calculation system for the laser scattering characteristics of the sea surface and the target under high sea states, comprising: The high sea level sea surface geometry model construction module is used to decompose the high sea level sea surface into a composite structure of a nonlinear rough sea surface layer and a white wave foam layer, and construct a high sea level sea surface geometry model. The optical property construction module of the high-sea-state sea surface geometry model is used to perform scattering modeling for the nonlinear rough sea surface layer and the white wave foam layer respectively. The nonlinear rough sea surface layer adopts a specular scattering model based on Fresnel reflection theory. For the white wave foam layer, its physical model is first constructed and the volume scattering parameters are calculated. Then, the four-dimensional bidirectional reflection distribution function tensor of the foam is obtained through Monte Carlo simulation. The dimensionality is reduced by combining the isotropic characteristics of the azimuth angle and a BRDF lookup table is constructed. Finally, a hybrid interpolation algorithm is used to obtain the foam BRDF value at any detection angle. The target and sea clutter composite time-domain waveform acquisition module is used to construct a traditional circularly symmetric Gaussian beam model and a super-Gaussian fan-shaped beam model based on Powell prism shaping. Based on the high-sea-state surface geometry model and its optical characteristics, combined with the lidar equation, the module uses the laser pulse Gaussian time-domain waveform, introduces the ray tracing method to determine the three-dimensional occlusion relationship, establishes a composite discretized time-domain integral model, and obtains the target and sea clutter composite time-domain waveform through spatiotemporal calculation and energy superposition.

[0018] This invention also provides a high-fidelity and high-efficiency computing device for the laser scattering characteristics of the sea surface and the target under high sea states, comprising: Memory: A computer program that stores the above-mentioned high-fidelity and high-efficiency calculation method for the laser scattering characteristics of the sea surface and the target under high sea conditions, and is a computer-readable device; Processor: Used to implement the high-fidelity and high-efficiency calculation method for the laser scattering characteristics of the sea surface and the target under high sea state when executing the computer program.

[0019] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the implementation of a high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea conditions.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention achieves accurate matching of foam distribution on high-sea-state sea surfaces through foam extraction technology based on the Jacobian matrix and slope criterion, combined with the Monahan foam coverage model, significantly improving the fidelity of geometric modeling of high-sea-state sea surfaces. Addressing the problem of regional over-accumulation or severe missing areas caused by existing technologies using fixed geometric thresholds for foam extraction, this invention divides sea surface foam into two categories: A-stage peak wave foam and B-stage static foam. The Jacobian determinant is used to measure the degree of local water compression to determine the generation location of peak wave foam, and the macroscopic geometric slope is used to determine the distribution range of residual static foam after breakup. Furthermore, the Monahan foam coverage model is used to dynamically match the theoretical foam coverage rate under the current sea state, solving the problem that fixed thresholds cannot adapt to dynamic sea conditions in high-sea-state environments.

[0021] 2. This invention utilizes Monte Carlo computation combined with a dimension-reduced BRDF lookup table technique, replacing real-time microscopic photon tracking calculations with hybrid interpolation, thereby improving simulation efficiency while maintaining scattering calculation accuracy. Addressing the computational overhead and memory consumption issues caused by real-time microscopic foam photon tracking in existing technologies, this invention employs the Monte Carlo method to simulate the multiple scattering process of photons within the foam layer, calculating the four-dimensional BRDF tensor of the foam. Leveraging the isotropic physical property of ocean foam azimuth angles, it reduces and compresses the tensor to three-dimensional space and constructs an efficient BRDF lookup table. During simulation, a hybrid algorithm combining incident angle matching and bilinear interpolation is used to quickly obtain the foam BRDF value at any detection angle, significantly reducing computational overhead during simulation and making large-scale, long-term high-ocean-state laser scattering simulations feasible for engineering applications.

[0022] 3. This invention achieves accurate calculation of composite scattering echoes from the sea surface and sea-skimming targets under various laser detection systems by combining multi-beam model adaptation with composite discretized time-domain integration technology and introducing a three-dimensional occlusion ray tracing algorithm. To adapt to the simulation requirements of different detection systems, this invention simultaneously constructs a traditional circularly symmetric Gaussian beam model and a super-Gaussian fan-shaped beam model based on Powell prism shaping, which can flexibly adapt to different application scenarios such as narrow-beam lidar and wide-angle laser fuses. The ray tracing method is introduced to accurately determine the complex three-dimensional occlusion relationship between the undulating sea surface and sea-skimming targets, and a composite discretized time-domain integration model is established. By performing spatiotemporal calculation and superposition of the visible surface element echo energy within each range gate in the time domain, a composite time-domain waveform of the target and sea clutter that conforms to physical reality can be generated, providing high-fidelity simulation data support for the anti-interference performance evaluation and algorithm verification of laser detection equipment.

[0023] In summary, this invention solves the problems of "low modeling fidelity" and "poor computational efficiency" in traditional high-sea-state laser scattering simulation by using an adaptive two-stage foam geometry extraction, pre-calculated dimensionality-reduced BRDF lookup table, and multi-beam composite time-domain integration technology. It has significant advantages such as high accuracy of sea surface geometry modeling, fast scattering calculation speed, strong adaptability to detection systems, and outstanding engineering application value. It can provide reliable simulation support for the performance evaluation and anti-interference algorithm development of sea-based photoelectric detection equipment such as lidar and laser fuses. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the nonlinear rough sea surface geometry modeling of the present invention.

[0025] Figure 2 This is a schematic diagram of the geometric modeling of the high sea surface of the present invention.

[0026] Figure 3 This is a schematic diagram of the cross-sectional structure of the foam layer of the present invention.

[0027] Figure 4 This is a schematic diagram of BRDF detection on the upper surface of the foam structure of the present invention.

[0028] Figure 5 This is a schematic diagram of a laser detection scenario using a circularly symmetric Gaussian beam model according to the present invention.

[0029] Figure 6(a) is a laser pulse echo diagram of the non-foam-containing sea surface at x=0 of the scanning platform of the present invention.

[0030] Figure 6(b) is a laser pulse echo diagram of the foamy sea surface at x=0 of the scanning platform of the present invention.

[0031] Figure 7(a) is a single-pulse cross-sectional array diagram of a foam-free sea surface when the scanning platform of the present invention moves along the x-axis.

[0032] Figure 7(b) is a single-pulse cross-sectional array diagram of the foamy sea surface when the scanning platform of the present invention moves along the x-axis.

[0033] Figure 8(a) is a pulse peak diagram of the sea surface without foam when the scanning platform of the present invention moves along the x-axis.

[0034] Figure 8(b) is a pulse peak diagram of the foamy sea surface when the scanning platform of the present invention moves along the x-axis.

[0035] Figure 9 This is a schematic diagram of a laser detection scenario using the super-Gaussian fan-shaped beam model of the present invention.

[0036] Figure 10(a) is a pulse peak diagram of a missile when the scanning platform of the present invention moves along the x-axis.

[0037] Figure 10(b) is a cross-sectional array diagram of a missile single pulse when the scanning platform of the present invention moves along the x-axis.

[0038] Figure 11(a) is a peak pulse diagram of a missile and a sea surface without foam when the scanning platform of the present invention moves along the x-axis.

[0039] Figure 11(b) is a cross-sectional array diagram of a missile and a sea surface without foam when the scanning platform of the present invention moves along the x-axis.

[0040] Figure 12(a) is a peak pulse diagram of a missile and a foamy sea surface when the scanning platform of the present invention moves along the x-axis.

[0041] Figure 12(b) is a cross-sectional array diagram of a missile and a single pulse containing foam when the scanning platform of the present invention moves along the x-axis. Detailed Implementation

[0042] The technical solution adopted by the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0043] A high-fidelity and efficient method for calculating the laser scattering characteristics of the sea surface and the target under high sea states includes the following steps: Step 1: Sea surface modeling often uses the sea surface spectrum method, which decomposes the high-sea-state sea surface into a composite structure of a nonlinear rough sea surface layer and a white wave foam layer to achieve its refined geometric representation. Construct a geometric model of the high-sea-state sea surface; The specific method of step 1 includes: (1) Constructing a nonlinear rough sea surface layer The basic modeling is based on the full wave number spectrum (including the composite structure of deep-water gravity waves and surface tension waves) proposed by Elfouhaily et al., and the Fourier expansion of the sea surface height field is as follows: (62) in, for The Fourier complex amplitude of the sea surface height field at time t. The initial spatial coordinates of the sea surface. It is a two-dimensional wavenumber vector. The imaginary unit; To represent the sharpening of wave crests and the smoothing of wave troughs in real gravity waves, a Choppy nonlinear transform is introduced into the Elfouhaily spectrum. First, the horizontal displacement field is calculated in the frequency domain, and then the sea surface horizontal displacement field is transformed into the spatial domain using an inverse fast Fourier transform (IFFT). (63) Initial spatial coordinates After displacement field perturbation, a new nonlinear horizontal coordinate is obtained. The expression is: (64) in, This is the chopping factor, used to control the degree of nonlinear compression of waves. and These are the displacement components in the x and y directions, respectively. The nonlinear rough sea surface geometry model established in this invention is as follows: Figure 1 As shown.

[0044] (2) Based on the Monahan foam coverage model, construct the geometric model of the white wave foam layer; The coverage of sea surface foam is determined by the wind speed at a height of 10m above the sea surface. Temperature difference with sea temperature It was jointly decided to divide the foam on the sea surface into two categories: Phase A, active foam (dynamic foam generated when waves break) and Phase B, static foam (stable foam remaining after waves break), with a total foam coverage rate of [missing information]. Phase A Peak Wave Foam Coverage and Phase B static foam coverage They respectively satisfy the following empirical relations: (65) (66) (67) By normalizing the weight allocation, the theoretical target area that the peak wave foam of stage A and the static foam of stage B should occupy in the nonlinear rough sea surface layer under the current sea state is calculated. and : (68) in, The area of ​​the nonlinear rough sea surface layer; The core hydrodynamic characteristic of wave crests being so sharp that water particle velocities exceed phase velocities leads to wave breakup, characterized by extreme horizontal compression of the water body. The Jacobian matrix is ​​used to measure the local deformation rate of the nonlinear rough sea surface layer to determine the location distribution of stage A wave crest foam on the nonlinear rough sea surface layer. (69) The smaller the value of the Jacobian determinant, the more severe the compression of the water body; the threshold for determining peak wave foam in stage A is set as follows. Then the set of surface masks for the peak wave foam in stage A. satisfy: (70) After foam is formed, it slides down the steep windward or leeward side of the waves, forming long foam streaks under the tearing force of strong winds. This part is strongly correlated with the maximum value of the sea surface slope. The macroscopic geometric slope S(x, y) is used to determine the location distribution of the residual B-stage static foam on the nonlinear rough sea surface layer: (71) in, The height of the nonlinear rough sea surface layer after Choppy transformation; To ensure physical exclusivity and prevent the overlap between the static foam region in stage B and the peak wave foam region in stage A, the static foam threshold in stage B is set as follows: Its surface mask set satisfy: (72) Based on the positional distribution of stage A peak wave foam and stage B static foam on the nonlinear rough sea surface layer, and by eliminating the interference of high-frequency capillary waves on the derivative operator and separating the shock wave and steady-state wave scales, a two-dimensional Gaussian kernel function is used to smooth the displacement and height fields, resulting in a high-sea-state sea surface geometric model. The figure shows a schematic diagram of the smoothed high-sea-state sea surface geometric model, where the red area represents stage A peak wave foam and the green area represents stage B static foam.

[0045] Step 2: Constructing the optical properties of a high-sea-state sea surface geometry model: Scattering models were developed for the nonlinear rough sea surface layer and the white wave foam layer. The nonlinear rough sea surface layer adopted a specular scattering model based on Fresnel reflection theory. For the white wave foam layer, a physical model was first constructed and the volume scattering parameters were calculated. Then, the four-dimensional bidirectional reflection distribution function (BRDF) tensor of the foam was obtained through Monte Carlo simulation. The dimensionality was reduced by combining the isotropic characteristics of the azimuth angle and a BRDF lookup table was constructed. Finally, a hybrid interpolation algorithm was used to quickly obtain the foam BRDF value at any detection angle. Step 2, the specific method for scattering modeling of the nonlinear rough sea surface layer, includes: The sea surface is discretized into several micro-surface elements, where the scattering behavior of a single micro-surface element is equivalent to a local planar specular reflection process and satisfies Fresnel's law of reflection. Assuming the incident light is isotropic, according to Fresnel's reflection theory, the ratio of the scattered field intensity to the incident field intensity of the micro-surface element is characterized by the Fresnel reflection coefficient: (73) in, The laser incident angle, The laser emission angle is... , is the polarization amplitude reflection coefficient.

[0046] Step 2, which involves constructing a physical model of the white foam layer and calculating the volume scattering parameters, includes the following specific methods: The sea surface foam layer exhibits microscopic characteristics as a highly dispersed, multi-scattering medium. The Reul empirical model was used to determine the thickness of the wind-driven macroscopic white wave foam layer, which was then simplified into a three-layer parallel flat plate structure with uniform thickness and linearly varying porosity with depth (e.g., Figure 3 (As shown). The foam particle size distribution follows a log-normal distribution (minimum radius 50 μm, maximum 1 mm).

[0047] Treating a single foam particle as a double-layered hollow sphere, the single-shot optical scattering parameters are solved based on Mie scattering theory. Due to the extremely large optical thickness of the foam layer, photon transmission exhibits intense volume scattering. The single-particle scattering characteristics are integrated over the entire log-normal particle size distribution using a ensemble average to obtain macroscopic volume scattering parameters, including the extinction coefficient. Scattering coefficient absorption coefficient and asymmetric factors ; (74) (75) (76) (77) (78) (79) in: (80) (81) (82) in: These are parameters related to the size of the foam particles. Let be the order of the Mie scattering expansion. , The Mie scattering coefficient is... , , In order, they are single-particle extinction, scattering, and absorption efficiency factors. The asymmetry factor of the foam particles. The single-scattering albedo of the foam particles, Where is the radius of the foam particles. The volume fraction of the foam layer medium. Let be the particle size distribution function of the foam particles. The concentration of foam particles, Let be the particle size distribution function of the foam particles. Minimum and maximum radii of the foam particle size distribution. Let be the geometric mean radius of the foam particles. This represents the geometric standard deviation of the foam particle size distribution. Step 2 involves obtaining the four-dimensional bidirectional reflectance distribution function (BRDF) tensor of the white foam layer through Monte Carlo simulation, performing dimensionality reduction by combining azimuth isotropy, constructing a BRDF lookup table, and using a hybrid interpolation algorithm to quickly obtain the foam BRDF value at any detection angle. Specific methods include: After obtaining the volume scattering parameters, the Monte Carlo method was used to simulate the multipath random walk of the beam inside the white foam layer, the air-sea interface interaction (combined with the Cox-Munk model), and the self-occlusion correction based on the annihilation factor of the error function. Finally, the photons escaping from the upper surface of the white foam layer and captured by the receiving solid angle (such as...) were statistically analyzed. Figure 4 As shown in the figure, the four-dimensional bidirectional reflection distribution function (BRDF) tensor of the white foam layer is calculated as follows: (83) in, From The total number of photons incident on the foam surface in the direction of incidence. In solid angle The number of photons received depends on the fact that sea foam in nature typically exhibits azimuth isotropy on a macroscopic scale; that is, the reflectivity of foam does not depend on the absolute incident and reflection azimuth angles, but only on the relative azimuth difference between them. The four-dimensional bidirectional reflection distribution function (BRDF) tensor of the white foam layer can be reduced to three dimensions: (twenty three) in, ; By traversing all incident direction grids and performing a large number of photon tracing operations, a complete three-dimensional tensor lookup table can be obtained. ; In subsequent calculations of the foam's optical properties, a hybrid interpolation algorithm is used to quickly obtain the foam's BRDF value at any detection angle; the specific process is as follows: First, calculate the incident zenith angle of the incident ray in the local tangent space of the current white wave foam layer element. With azimuth And determine the zenith angle of the launch direction based on the detection requirements. relative azimuth ; To significantly reduce the computational cost of multidimensional interpolation, a three-dimensional tensor lookup table is used. In the middle, find the angle of incidence that matches the current query. Discrete grid node with the smallest absolute error As a matching layer, The index m is determined by the following formula: (84) in, For 3D tensor lookup tables The number of discrete grids at the incident zenith angle. Let be the incident zenith angle value corresponding to the k-th grid node; through this step, the three-dimensional interpolation problem is reduced to a fixed incident zenith angle. Two-dimensional data slices In progress; To avoid the spatial discontinuity of reflected energy distribution caused by discrete grids, at a matched incident angle At the level of querying the launch direction Using bilinear interpolation, the four adjacent nodes surrounding the exit direction in the two-dimensional grid are located. Falling in the range , Falling in the range ; Calculate the normalized weighting factor based on angular distance: (85) The final BRDF value to be determined for the foam It can be precisely approximated by the weighted sum of the four surrounding discrete BRDF values: (86) in, Equivalent to elements in a 3D tensor lookup table .

[0048] Step 3: Construct a traditional circularly symmetric Gaussian beam model and a super-Gaussian fan-shaped beam model based on Powell prism shaping; based on the optical characteristics of the high-sea-state surface geometry model constructed in Step 1 and Step 2, and combined with the lidar equation, use the Gaussian time-domain waveform of the laser pulse, introduce the ray tracing method to determine the three-dimensional occlusion relationship, establish a composite discretized time-domain integral model, and obtain the composite time-domain waveform of the target and sea clutter through spatiotemporal solution and energy superposition.

[0049] The specific method for step 3 includes: To meet the simulation requirements of different detection systems (such as traditional circular beam radar and wide-angle laser fuzes), this invention constructs two spatial illumination distribution models: a traditional circularly symmetric Gaussian beam model and a super-Gaussian fan-shaped beam model based on Powell prism shaping, to accurately characterize the energy distribution of the laser beam on the cross-section. (unit: ): (1) Constructing a traditional circularly symmetric Gaussian beam model For traditional narrow-beam spot illumination systems, the laser energy in space follows an ideal Gaussian decay law of the fundamental mode. Let the effective beam radius be... Its spatial illuminance distribution is as follows: (87) in, Spatial coordinates The peak power of the laser pulse. is the Gaussian beam radius (beam waist radius) at a distance z from the emitting end; (2) Constructing a super-Gaussian fan-shaped beam model based on Powell prism shaping In practical fuse detection engineering (such as typical (Sector-shaped field of view) To avoid missing targets at the edge of the sector, the transmitting end often uses a Powell prism for light field equalization. Due to the edge roll-off effect in actual devices, this invention introduces a super-Gaussian function to fit the real flat-top distribution. Assuming that the laser undergoes shaping on the Y-axis and maintains the fundamental mode on the X-axis, the corrected mixed spatial illuminance distribution is: (88) In the formula, Let z be the peak light intensity at a propagation distance z. It is the super-Gaussian order (usually between 8 and 20, depending on the prism manufacturing precision). and These are the beam length and minor axis widths corresponding to the depth. The dynamic peak light intensity is derived from the conservation of total emitted power: (89) in, It is a gamma function; Meanwhile, let the Gaussian time-domain waveform of the pulse emitted by the laser be... It usually follows a Gaussian distribution: (90) in, The moment of laser pulse emission. This refers to the laser pulse width parameter.

[0050] Based on the lidar equation, the power of the laser backscattered echo collected by the receiving system can be jointly determined by the environmental parameters of the high-sea-state sea surface geometric model, the optical characteristics of the high-sea-state sea surface geometric model, and the geometric relationship of the detector. This invention introduces the ray tracing method to accurately determine the complex three-dimensional occlusion relationship between the large-undulation sea surface and the sea-skimming target. The composite discretized time-domain integral model collected by the receiving system at time t can be expressed as: (91) The parameters in the formula are defined as described above, where, Let be the straight-line distance from the i-th surface element to the radar. The speed of light in a vacuum. To achieve the effective receiving area of ​​the receiving antenna, Atmospheric transport attenuation, For the incident projection of the surface element, Let i be the area of ​​the i-th face element. Depending on the radar system of the specific simulation scenario, one of the two spatial illumination distribution models mentioned above can be flexibly substituted. By performing spatiotemporal calculation and superposition of the visible surface echo energy within each range gate in the time domain, a complete and physically realistic composite time-domain waveform of the target and sea clutter can be obtained.

[0051] Simulation Analysis of High-Sea-Level Sea Surface Backscattering Characteristics like Figure 5 The diagram shows a circularly symmetric Gaussian beam laser detection scenario, where XOY is the coordinate system, Tx / Rx represents transmission and reception, and V represents the velocity direction of the scanning platform. The initial position of the scanning platform is (-100, 0, 100), the scanning distance is 200m, the peak pulse power is 140W, the pulse frequency is 1000Hz, the pulse width is 0.5ns, the sampling frequency is 2e9, and the laser wavelength is 1.06μm.

[0052] When the laser is incident perpendicularly to the sea surface, i.e., the scanning direction is (0,0,-1), the scattered echoes from foam-containing and foam-free sea surfaces under continuous pulse irradiation are shown in Figures 6(a), 6(b), 7(a), 7(b), 8(a), and 8(b). Figures 6(a) and 6(b) show the laser pulse echoes from the scanning platform at x=0 to the foam-free and foam-containing sea surfaces, respectively. Figures 7(a) and 7(b) show the single-pulse profile arrays of the scanning platform moving along the x-axis to the foam-free and foam-containing sea surfaces, respectively. Figures 8(a) and 8(b) show the pulse peak values ​​of the scanning platform moving along the x-axis to the foam-free and foam-containing sea surfaces, respectively. When the laser is incident perpendicularly to the sea surface, the scattered echo characteristics from foam-containing and foam-free sea surfaces under continuous pulse irradiation show significant differences.

[0053] Comparing the single-pulse echoes in Figures 6(a) and 6(b), it can be seen that the power base of the sea surface echo increases by orders of magnitude after the introduction of the foam layer, regardless of whether it is a single echo or multiple echoes. From a physical mechanism perspective, the backscattering of a foam-free sea surface is highly dependent on the strict mirror alignment of the wave micro-surface element normals; while the foam layer covering the wave crests disrupts the continuity of the air-sea interface, and its strong volume scattering characteristics transform the originally highly directional specular reflection into diffuse reflection from a rougher surface with a more uniform spatial distribution. As shown in Figures 7(a) and 7(b), the sea surface echo considering the influence of foam exhibits a significant asymmetric broadening effect on the time axis. This is mainly due to the dramatic increase in sea surface roughness under high sea states, which causes the laser to undergo more frequent geometrical multiple ejections between the undulating sea surface and the foam layer. This spatial time delay accumulated by the multipath propagation of rays ultimately manifests macroscopically as an extension of the pulse width. Figures 8(a) and 8(b) further demonstrate that during continuous pulse scanning, the strong diffuse reflection characteristics of the foam-covered area effectively fill the "echo void" caused by the lack of specular reflection, resulting in a significant increase in the peak value of the continuous pulse when the scanning platform moves along the x-axis, and a more continuous overall envelope.

[0054] Simulation Analysis of Typical Low-Altitude Target Engagement Cases In this embodiment, the transmitter employs a super-Gaussian fan-shaped beam model based on Powell prism shaping. The beam field of view is set to... SuperGaussian order .like Figure 9 The diagram shows a laser detection scenario using a super-Gaussian fan-beam model. XOY represents the coordinate system, Tx / Rx represents the transmission and reception, the low-reflectivity (0.05) sea-skimming cruise missile is shown (at an altitude of 4m), and V represents the velocity direction of the scanning platform. The initial position of the scanning platform is (-15, 0, 10), the scanning distance is 30m, the peak pulse power is 140W, the pulse frequency is 1000Hz, the pulse width is 5ns, the sampling frequency is 2e9, and the laser wavelength is 1.06μm.

[0055] When the laser is incident perpendicularly to the sea surface, i.e., the scanning direction is (0,0,-1), the composite scattered echoes of the target from the foamy sea surface and the non-foamy sea surface under continuous pulse irradiation are shown in Figures 10(a), 10(b), 11(a), 11(b), and 12(a) and 12(b). When the scanning platform moves along the x-axis, Figures 10(a) and 10(b) are the pulse peak and single pulse profile array of a missile, respectively; Figures 11(a) and 11(b) are the pulse peak and single pulse profile array of a missile and a non-foamy sea surface, respectively; and Figures 12(a) and 12(b) are the pulse peak and single pulse profile array of a missile and a foamy sea surface, respectively.

[0056] As shown in Figures 10(a) and 10(b), the single-pulse profile array of the target clearly reflects its geometric topological features. Due to the strong backscattering capability of large cross-section components such as the target's tail and wings, obvious echo extrema appear at the scanning positions of -3 m and 0 m. Comparing the received waveforms of the composite scene in Figures 11(a) and 11(b) and Figures 12(a) and 12(b), it can be seen that after introducing the high-precision foam model, under the influence of the wide-field-of-view ultra-Gaussian beam illumination, the massive diffuse reflection energy generated by the high-sea-state foam layer is integrated on the detector target surface, forming an extremely high background echo signal. As a result, the weak target echo is completely masked by strong foam clutter on the pulse peak curve. However, in the time dimension of the single-pulse profile array, thanks to the extremely narrow pulse width and the physical height difference between the target and the sea surface, the target echo and the delayed sea surface echo are effectively physically separated on the time axis. Furthermore, a local depression in the sea surface echo energy can be clearly observed directly below the scanning platform where the target pulse exists. This is due to the three-dimensional geometric occlusion effect of the target on the lower sea surface.

[0057] Therefore, this invention can reproduce the effects of power enhancement, pulse broadening, and echo continuity enhancement of backscattering from the sea surface by the foam layer under high sea conditions. At the same time, it can present the composite scattering characteristics, time separation characteristics, and three-dimensional occlusion effect of sea-skimming targets and high sea surface. It provides a high-fidelity simulation verification method for the performance evaluation, anti-interference algorithm design, and system parameter optimization of sea-penetrating photoelectric detection equipment such as lidar and laser fuse under harsh sea conditions.

[0058] This invention can accurately reproduce the echo base rise, pulse asymmetric broadening, and severe target "energy inversion masking" phenomenon caused by high sea state foam, providing a reliable data model and theoretical basis for the anti-interference design and adaptive threshold calibration of complex laser detection systems.

[0059] This invention also provides a high-fidelity and high-efficiency calculation system for the laser scattering characteristics of the sea surface and the target under high sea states, comprising: The high sea level sea surface geometric model construction module is used to realize the decomposition of the high sea level sea surface into a composite structure of nonlinear rough sea surface layer and white wave foam layer in step 1, and to construct the high sea level sea surface geometric model. The optical property construction module of the high-sea-state sea surface geometry model is used to realize the scattering modeling of the nonlinear rough sea surface layer and the white wave foam layer in step 2. The nonlinear rough sea surface layer adopts the specular scattering model based on Fresnel reflection theory. For the white wave foam layer, its physical model is first constructed and the volume scattering parameters are calculated. Then, the foam four-dimensional bidirectional reflection distribution function tensor is obtained through Monte Carlo simulation. The dimensionality is reduced by combining the isotropic characteristics of the azimuth angle and a BRDF lookup table is constructed. Finally, the foam BRDF value at any detection angle is obtained by using a hybrid interpolation algorithm. The target and sea clutter composite time-domain waveform acquisition module is used to realize the construction of the traditional circular symmetric Gaussian beam model and the super-Gaussian fan-shaped beam model based on Powell prism shaping in step 3; based on the optical characteristics of the high sea state surface geometry model constructed in step 1 and step 2, combined with the lidar equation, using the laser pulse Gaussian time-domain waveform, introducing the ray tracing method to determine the three-dimensional occlusion relationship, establishing a composite discretized time-domain integral model, and obtaining the target and sea clutter composite time-domain waveform through spatiotemporal calculation and energy superposition.

[0060] This invention also provides a high-fidelity and high-efficiency computing device for the laser scattering characteristics of the sea surface and the target under high sea states, comprising: Memory: A computer program that stores the above-mentioned high-fidelity and high-efficiency calculation method for the laser scattering characteristics of the sea surface and the target under high sea conditions, and is a computer-readable device; Processor: Used to implement the high-fidelity and high-efficiency calculation method for the laser scattering characteristics of the sea surface and the target under high sea state when executing the computer program.

[0061] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the implementation of a high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea conditions.

Claims

1. A high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea states, characterized in that, Includes the following steps: Step 1: Decompose the high sea level sea surface into a composite structure of a nonlinear rough sea surface layer and a white wave foam layer, and construct a geometric model of the high sea level sea surface. Step 2: Constructing the optical properties of a high-sea-state sea surface geometry model: Scattering models were developed for the nonlinear rough sea surface layer and the white wave foam layer. The nonlinear rough sea surface layer adopted a specular scattering model based on Fresnel reflection theory. For the white wave foam layer, a physical model was first constructed and the volume scattering parameters were calculated. Then, the four-dimensional bidirectional reflection distribution function tensor of the foam was obtained through Monte Carlo simulation. The dimensionality was reduced by combining the isotropic characteristics of the azimuth angle and a BRDF lookup table was constructed. Finally, a hybrid interpolation algorithm was used to obtain the foam BRDF value at any detection angle. Step 3: Construct a traditional circularly symmetric Gaussian beam model and a super-Gaussian fan-shaped beam model based on Powell prism shaping; based on the optical characteristics of the high-sea-state surface geometry model constructed in Step 1 and Step 2, and combined with the lidar equation, use the Gaussian time-domain waveform of the laser pulse, introduce the ray tracing method to determine the three-dimensional occlusion relationship, establish a composite discretized time-domain integral model, and obtain the composite time-domain waveform of the target and sea clutter through spatiotemporal solution and energy superposition.

2. The high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea state conditions, as described in claim 1, is characterized in that... The specific method of step 1 includes: (1) Constructing a nonlinear rough sea surface layer The Fourier expansion of the sea surface height field is: (1) in, for The Fourier complex amplitude of the sea surface height field at time t. The initial spatial coordinates of the sea surface. It is a two-dimensional wavenumber vector. The imaginary unit; The Elfouhaily spectrum is subjected to a Choppy nonlinear transform; firstly, the horizontal displacement field is calculated in the frequency domain, and then the sea surface horizontal displacement field is transformed into the spatial domain through an inverse fast Fourier transform. (2) Initial spatial coordinates After displacement field perturbation, a new nonlinear horizontal coordinate is obtained. The expression is: (3) in, This is the chopping factor, used to control the degree of nonlinear compression of waves. and These are the displacement components in the x and y directions, respectively; (2) Based on the Monahan foam coverage model, construct the geometric model of the white wave foam layer; The coverage of sea surface foam is determined by the wind speed at a height of 10m above the sea surface. Temperature difference with sea temperature It was jointly decided to divide the foam on the sea surface into two categories: Phase A, peak wave foam, and Phase B, static foam, with a total foam coverage rate of [missing information]. Phase A peak wave foam coverage and Phase B static foam coverage They respectively satisfy the following empirical relations: (4) (5) (6) By normalizing the weight allocation, the target area that the peak wave foam of stage A and the static foam of stage B should occupy in the nonlinear rough sea surface layer under the current sea state is calculated. and : (7) in, The area of ​​the nonlinear rough sea surface layer; The local deformation rate of the nonlinear rough sea surface layer is measured to determine the location distribution of stage A peak wave foam on the nonlinear rough sea surface layer: (8) The smaller the value of the Jacobian determinant, the more severe the compression of the water body; the threshold for determining peak wave foam in stage A is set as follows. Then the set of surface mask elements for the peak wave foam in stage A. satisfy: (9) The location distribution of residual stage B static foam on the nonlinear rough sea surface layer is determined by using the macroscopic geometric slope S(x, y): (10) in, The height of the nonlinear rough sea surface layer after Choppy transformation; Set the static foam threshold for stage B as follows: Its surface mask set satisfy: (11) Based on the positional distribution of peak wave foam in stage A and static foam in stage B on the nonlinear rough sea surface layer, a two-dimensional Gaussian kernel function is used to smooth the displacement field and height field to obtain a geometric model of the high sea state sea surface.

3. The high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea state conditions, as described in claim 1, is characterized in that... Step 2, the specific method for scattering modeling of the nonlinear rough sea surface layer, includes: The sea surface is discretized into several micro-surface elements, where the scattering behavior of a single micro-surface element is equivalent to a local planar specular reflection process and satisfies Fresnel's law of reflection. Assuming the incident light is isotropic, according to Fresnel's reflection theory, the ratio of the scattered field intensity to the incident field intensity of the micro-surface element is characterized by the Fresnel reflection coefficient: (12) in, The laser incident angle, The laser emission angle is... , is the polarization amplitude reflection coefficient.

4. The high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea state conditions, as described in claim 3, is characterized in that... Step 2, which involves constructing a physical model of the white foam layer and calculating the volume scattering parameters, includes the following specific methods: The Reul empirical model was used to determine the thickness of the wind-driven macroscopic white wave foam layer, and the white wave foam layer was simplified into a three-layer parallel flat plate structure with uniform thickness and linear porosity with depth. Treating a single foam particle as a double-layered hollow sphere, the single-shot optical scattering parameters are solved based on Mie theory. The single-particle scattering characteristics are then integrated over the entire log-normal particle size distribution using a ensemble average to obtain macroscopic volume scattering parameters, including the extinction coefficient. Scattering coefficient absorption coefficient and asymmetric factors ; (13) (14) (15) (16) (17) (18) in: (19) (20) (21) in: These are parameters related to the size of the foam particles. Let be the order of the Mie scattering expansion. , The Mie scattering coefficient is... , , In order, they are single-particle extinction, scattering, and absorption efficiency factors. The asymmetry factor of the foam particles. The single-scattering albedo of the foam particles, Where is the radius of the foam particles. The volume fraction of the foam layer medium. Let be the particle size distribution function of the foam particles. The concentration of foam particles, Let be the particle size distribution function of the foam particles. Minimum and maximum radii of the foam particle size distribution. Let be the geometric mean radius of the foam particles. This represents the geometric standard deviation of the foam particle size distribution.

5. The high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea state conditions, as described in claim 4, is characterized in that... In step 2, the four-dimensional bidirectional reflectance distribution function (BRDF) tensor of the white wave foam layer is obtained through Monte Carlo simulation. Dimensionality reduction is achieved by combining azimuth isotropy, and a BRDF lookup table is constructed. A hybrid interpolation algorithm is used to obtain the foam BRDF value at any detection angle. Specifically, the method includes: using Monte Carlo simulation to model the multipath random walk of the beam within the white wave foam layer, the air-sea interface interaction, and self-occlusion correction based on the annihilation factor of the error function. Finally, the photons escaping from the upper surface of the white wave foam layer and captured by the receiving solid angle are statistically analyzed. The four-dimensional bidirectional reflectance distribution function (BRDF) tensor of the white wave foam layer is calculated as follows: (22) in, From The total number of photons incident on the foam surface in the direction of incidence. In solid angle The number of photons received internally; reducing the four-dimensional bidirectional reflectance distribution function (BRDF) tensor of the white foam layer to three dimensions: (23) in, ; By traversing all incident direction meshes and performing extensive photon tracing, a complete 3D tensor lookup table is obtained. A hybrid interpolation algorithm is used to obtain the foam BRDF value at any detection angle.

6. The high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea state conditions, as described in claim 5, is characterized in that... The process of obtaining the foam BRDF value at any detection angle using a hybrid interpolation algorithm is as follows: First, calculate the incident zenith angle of the incident ray in the local tangent space of the current white wave foam layer element. With azimuth And determine the zenith angle of the launch direction based on the detection requirements. relative azimuth ; In a three-dimensional tensor lookup table In the middle, find the angle of incidence that matches the current query. Discrete grid node with the smallest absolute error As a matching layer, The index m is determined by the following formula: (24) in, For 3D tensor lookup tables The number of discrete grids at the incident zenith angle. Let be the incident zenith angle value corresponding to the k-th grid node; reduce the 3D spatial interpolation problem to a fixed incident zenith angle. Two-dimensional data slices In progress; At the matching angle of incidence At the level of querying the launch direction Using bilinear interpolation, the four adjacent nodes surrounding the exit direction in the two-dimensional grid are located. Falling in the range , Falling in the range ; Calculate the normalized weighting factor based on angular distance: (25) The final BRDF value to be determined for the foam It is an exact approximation by the weighted sum of the four surrounding discrete BRDF values: (26) in, Equivalent to elements in a 3D tensor lookup table .

7. The high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea state conditions, as described in claim 1, is characterized in that... The specific method for step 3 includes: Two spatial illuminance distribution models were constructed: a traditional circularly symmetric Gaussian beam model and a super-Gaussian fan-shaped beam model based on Powell prism shaping, to accurately characterize the energy distribution of the laser beam across its cross-section. : (1) Constructing a traditional circularly symmetric Gaussian beam model For traditional narrow-beam spot illumination systems, the laser energy in space follows an ideal Gaussian decay law of the fundamental mode. Let the effective beam radius be... Its spatial illuminance distribution is as follows: (27) in, Spatial coordinates The peak power of the laser pulse. is the Gaussian beam radius (beam waist radius) at a distance z from the emitting end; (2) Constructing a super-Gaussian fan-shaped beam model based on Powell prism shaping By introducing a super-Gaussian function to fit the true flat-top distribution, assuming the laser undergoes shaping along the Y-axis and maintains its fundamental mode along the X-axis, the corrected mixed-space illuminance distribution is as follows: (28) In the formula, Let z be the peak light intensity at a propagation distance z. It is a super-Gaussian order. and These are the beam length and minor axis widths corresponding to the depth. The dynamic peak light intensity is derived from the conservation of total emitted power: (29) in, It is a gamma function; Meanwhile, let the Gaussian time-domain waveform of the pulse emitted by the laser be... It usually follows a Gaussian distribution: (30) in, The moment of laser pulse emission. This refers to the laser pulse width parameter; Based on the lidar equation, the power of the laser backscattered echo collected by the receiving system is jointly determined by the environmental parameters of the high-sea-state sea surface geometric model, the optical characteristics of the high-sea-state sea surface geometric model, and the geometric relationship of the detector. A ray tracing method is introduced to determine the complex three-dimensional occlusion relationship between the undulating sea surface and the sea-skimming target. The composite discretized time-domain integral model collected by the receiving system at time t can be expressed as: (31) in, Let be the straight-line distance from the i-th surface element to the radar. The speed of light in a vacuum. To achieve the effective receiving area of ​​the receiving antenna, Atmospheric transport attenuation, For the incident projection of the surface element, Let i be the area of ​​the i-th face element. Based on the radar system of the specific simulation scenario, one of the two spatial illumination distribution models mentioned above is substituted into the model. By performing spatiotemporal calculation and superposition of the visible surface echo energy within each range gate in the time domain, the composite time domain waveform of the target and sea clutter can be obtained.

8. A high-fidelity and high-efficiency computing system for calculating the laser scattering characteristics of the sea surface and a target under high sea states, characterized in that, To implement the method of claim 1, the method comprises: The high sea level sea surface geometry model construction module is used to decompose the high sea level sea surface into a composite structure of a nonlinear rough sea surface layer and a white wave foam layer, and construct a high sea level sea surface geometry model. The optical property construction module of the high-sea-state sea surface geometry model is used to perform scattering modeling for the nonlinear rough sea surface layer and the white wave foam layer respectively. The nonlinear rough sea surface layer adopts a specular scattering model based on Fresnel reflection theory. For the white wave foam layer, its physical model is first constructed and the volume scattering parameters are calculated. Then, the four-dimensional bidirectional reflection distribution function tensor of the foam is obtained through Monte Carlo simulation. The dimensionality is reduced by combining the isotropic characteristics of the azimuth angle and a BRDF lookup table is constructed. Finally, a hybrid interpolation algorithm is used to obtain the foam BRDF value at any detection angle. The target and sea clutter composite time-domain waveform acquisition module is used to construct a traditional circularly symmetric Gaussian beam model and a super-Gaussian fan-shaped beam model based on Powell prism shaping. Based on the high-sea-state surface geometry model and its optical characteristics, combined with the lidar equation, the module uses the laser pulse Gaussian time-domain waveform, introduces the ray tracing method to determine the three-dimensional occlusion relationship, establishes a composite discretized time-domain integral model, and obtains the target and sea clutter composite time-domain waveform through spatiotemporal calculation and energy superposition.

9. A high-fidelity and high-efficiency computing device for the laser scattering characteristics of the sea surface and a target under high sea states, characterized in that, include: Memory: A computer program for calculating the high-fidelity and high-efficiency laser scattering characteristics of the sea surface and the target under high sea conditions, as described in any one of claims 1-7, is a computer-readable device; Processor: Used to execute the computer program to implement the high-fidelity and high-efficiency calculation method for the laser scattering characteristics of the sea surface and the target under high sea state as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, enables the implementation of a high-fidelity and efficient calculation method for the laser scattering characteristics of the sea surface and the target under high sea conditions, as described in any one of claims 1-7.

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