Statistical scattering method for clutter particles in the environment in radar detection

Abstract

This invention belongs to the field of radar signal processing and target detection technology, specifically relating to a statistical scattering method for clutter particles in radar detection. The method includes: acquiring single scattering parameters and simulation control parameters of the clutter particles; dynamically determining the simulation space length based on the single extinction coefficient and asymmetry factor; initializing a quasi-Monte Carlo low-discrepancy sequence; after initializing each photon packet, randomly generating a propagation step size and updating the cumulative propagation step size; when the photon packet does not exceed the boundary, determining whether scattering has occurred based on the single extinction coefficient and cumulative propagation step size; if scattering has occurred, updating the scattering direction based on the Henyey-Greenstein phase function and attenuating the energy weight; employing an adaptive dynamic threshold roulette wheel mechanism to dynamically adjust the survival probability based on scattering efficiency, photon position, and propagation direction, and maintaining statistical unbiasedness through energy weight compensation; after traversing all photon packets, calculating the total transmitted energy and total reflected energy, and calculating the equivalent extinction coefficient and radar cross section. This invention significantly improves simulation efficiency while ensuring statistical accuracy through physically guided importance sampling and a quasi-Monte Carlo low-discrepancy sequence, providing reliable support for radar anti-environmental clutter interference design.

Description

Technical Field

[0001] This invention belongs to the field of radar signal processing and target detection technology, specifically relating to a statistical scattering method for clutter particles in the environment during radar detection. Background Technology

[0002] This application relates to the field of radar detection technology, specifically to a statistical scattering method for environmental clutter particles in radar detection. During radar detection, environmental clutter particles such as rain, snow, fog, and dust scatter and attenuate radar electromagnetic waves, creating strong background interference. This directly leads to a decrease in the probability of detecting weak targets and an increase in the false alarm rate. Therefore, accurately simulating the multiple scattering and energy transfer process of radar waves by clutter particles is an important prerequisite for improving radar anti-jamming capabilities, optimizing detection algorithms, and achieving accurate detection in complex environments.

[0003] In existing technologies, analytical models based on single-scattering approximations (such as Mie theory) are mainly used to establish clutter scattering models. These models are computationally simple, but they completely ignore the contribution of multiple scattering, which can introduce systematic errors in scenarios with large optical thickness, such as dense clouds and heavy precipitation. Deterministic numerical solutions to the radiative transfer equation (such as the discrete coordinate method and the spherical harmonic function method) can consider multiple scattering, but they face challenges of high computational complexity and poor adaptability when dealing with complex three-dimensional non-uniform media, strongly anisotropic scattering phase functions, and calculating higher-order statistical moments of echo signals. Monte Carlo methods, as statistical simulation techniques based on random sampling, can naturally handle complex geometry and scattering phase functions. However, traditional Monte Carlo simulations require tracking a massive number of photon samples to achieve convergence, resulting in extremely high computational costs, which is difficult to meet the engineering application requirements of rapid parameter scanning or real-time system performance evaluation.

[0004] Therefore, how to effectively reduce the computational overhead of the Monte Carlo method while ensuring simulation accuracy, so that clutter scattering simulation can achieve both high accuracy and high efficiency, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] To address the problems existing in the background art, one aspect of the present invention provides a statistical scattering method for radar detection of clutter particles in the environment, comprising:

[0006] S1: Obtain the single scattering parameters and simulation control parameters of the clutter particles. The single scattering parameters include the asymmetry factor, single extinction coefficient, and scattering efficiency. The simulation control parameters include the total number of photon packets and the roulette wheel betting threshold.

[0007] S2: Dynamically determine the simulation space length based on the single extinction coefficient and asymmetry factor, and initialize the quasi-Monte Carlo low-difference sequence for random sampling;

[0008] S3: Perform initialization for each photon packet, setting the initial position, initial propagation direction, and normalized energy weights;

[0009] S4: Randomly generate the propagation step size, control the photon packet to propagate along the propagation direction in the simulation space, and update the current cumulative propagation step size of the photon packet;

[0010] S5: Determine if the photon packet exceeds the simulation space boundary; if it does, record the transmitted or reflected energy and terminate the current photon packet; if it does not exceed the boundary, determine whether the photon packet is scattering based on the single extinction coefficient of the photon packet and the current cumulative propagation step size.

[0011] If no scattering occurs, keep the propagation direction of the photon packet unchanged and return to step S4;

[0012] If scattering occurs, the scattering direction of the photon packet is updated based on the Henyey Greenstein phase function of the quasi-Monte Carlo low-difference sequence, the propagation direction of the photon packet is updated to the scattering direction, the energy weight of the photon packet is attenuated, and the current cumulative propagation step size of the photon packet is cleared to 0.

[0013] S6: Calculate the dynamic threshold based on the roulette wheel betting base threshold, the current photon packet number, and the total number of photon packets; take a random sample value from the quasi-Monte Carlo low-difference sequence. If the survival probability of the photon packet is greater than the random sample value, the photon packet is determined to be alive, the energy weight of the photon packet is increased, and the process returns to step S4; if the survival probability of the photon packet is less than or equal to the random sample value, the photon packet is determined to be dead, and the current photon packet is terminated.

[0014] S7: After traversing all photon packets, the total transmitted energy and total reflected energy of all photon packets are counted, and the equivalent extinction coefficient and radar cross section are calculated.

[0015] Another aspect of the present invention provides a statistical scattering system for radar detection of clutter particles in the environment, the system comprising a memory and a processor; the memory for storing an application program; and the processor for running the application program to execute the statistical scattering method for radar detection of clutter particles in the environment.

[0016] Another aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the statistical scattering method for detecting clutter particles in the environment in radar detection.

[0017] The present invention has at least the following beneficial effects

[0018] This application employs an adaptive dynamic threshold roulette wheel mechanism to dynamically adjust the photon survival probability based on the simulation progress, photon position, and scattering angle. This intelligently focuses computational resources on photon paths that contribute significantly to transmission and reflection. Simultaneously, it introduces quasi-Monte Carlo low-difference sequences (such as Sobol sequences) to replace the traditional pseudo-random number generator, ensuring uniform filling of photon samples in the state space and significantly accelerating statistical convergence. Furthermore, it combines physical-guided importance sampling based on actual particle scattering theory, greatly improving simulation efficiency and accuracy while maintaining statistical unbiasedness. This effectively overcomes the technical shortcomings of existing Monte Carlo methods, such as high computational cost and difficulty in balancing high accuracy and efficiency, providing reliable and efficient simulation support for the anti-interference design of radar systems in complex environments. Attached Figure Description

[0019] Figure 1 A schematic diagram of the method flow of this invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figure 1 One aspect of the present invention provides a statistical scattering method for radar detection of clutter particles in the environment, comprising:

[0022] S1: Obtain the single scattering parameters and simulation control parameters of the clutter particles. The single scattering parameters include the asymmetry factor, single extinction coefficient, and scattering efficiency. The simulation control parameters include the total number of photon packets and the roulette wheel betting threshold.

[0023] In this embodiment, radar environmental clutter simulation under heavy rainfall is used as an example. First, the simulation scenario is determined to be a rainstorm environment with a rainfall intensity of 15 mm / h. Based on the Marshall-Palmer raindrop size distribution model, the droplet size distribution range (diameter from 0.1 mm to 5 mm) is calculated. Then, combined with the complex permittivity of water at 20°C, the average single-scattering parameters of the raindrop swarm are calculated based on Mie scattering theory. Specifically, the asymmetry factor of the clutter particles is obtained through weighted averaging. Characterizes the tendency of raindrops to scatter radar waves forward; calculates the single extinction coefficient. This reflects the energy attenuation of electromagnetic waves per unit distance due to scattering and absorption; the scattering efficiency is calculated. This indicates that the scattered energy accounts for a relatively high proportion of the total extinction energy in the raindrop swarm, while the absorption is relatively weak. Secondly, simulation control parameters are set. To ensure statistical convergence accuracy, the total number of photon packets is set. Based on previous experimental experience, a basic threshold for roulette wheel betting was set. This serves as the base value for subsequent dynamic threshold calculations. Simultaneously, to accommodate future parallel computing needs, a parallel computing mode is enabled, and a quad-core processor is configured to execute the photon packet tracking task in parallel.

[0024] S2: Dynamically determine the simulation space length based on the single extinction coefficient and asymmetry factor, and initialize the quasi-Monte Carlo low-difference sequence for random sampling;

[0025] Preferably, the length of the simulation space includes:

[0026]

[0027]

[0028] in, Indicates the length of the simulation space; This represents the dynamic adjustment factor; K represents the single extinction coefficient of clutter particles. This represents a preset empirical constant, typically ranging from 1.3 to 1.5. The asymmetry factor representing clutter particles.

[0029] Preferably, the quasi-Monte Carlo low-difference sequence is Sobol sequences of intervals.

[0030] In this embodiment, based on the obtained single scattering parameters: asymmetry factor Single extinction coefficient Calculate the length of the simulation space, thereby determining its length along the z-axis. This length satisfies the following conditions: for a raindrop swarm with strong forward scattering, a sufficiently large simulation space is needed to adequately simulate the backscattering path, while simultaneously ensuring that particles undergo a sufficient number of scattering events within the space. L represents the degree of freedom of the particle;

[0031] To replace traditional pseudo-random number generators and improve the convergence speed of Monte Carlo simulations, this embodiment uses Sobol sequences as quasi-Monte Carlo low-discrepancy sequences; the initialization process is as follows:

[0032] The Sobol sequence is set to 1024 dimensions to ensure that all random number requests throughout the simulation can be sequentially drawn from this sequence. The number of jump points is set to 1000 to eliminate the influence of initial correlations. Sobol sequence objects are generated using MATLAB's built-in functions. In subsequent simulations, a global counter is maintained, and random numbers are drawn sequentially from the next dimension of the sequence each time they are needed. When all dimensions are exhausted, the loop restarts from the first dimension, increasing the number of jump points to ensure the independence of random numbers between different photon packets. For example, for the first scattering of the first photon packet, the first and second dimensions of the Sobol sequence are used as the propagation step random numbers. And scattering to determine random numbers Take the third dimension as the random number for sampling the scattering direction. The fourth dimension is used as the random number for the roulette wheel scattering; subsequent scattering uses the fifth dimension and subsequent dimensions. This method ensures that all random samples originate from low-discrepancy sequences, uniformly filling the state space with photon samples, thus achieving lower statistical variance for the same number of photon packets and accelerating convergence.

[0033] By dynamically determining the simulation space length based on the single extinction coefficient and asymmetry factor, the simulation space adaptively matches the scattering characteristics of clutter particles, ensuring sufficient occurrence of multiple scatterings while avoiding computational waste caused by excessive space. At the same time, a quasi-Monte Carlo low-difference sequence (Sobol sequence) is introduced to replace the traditional pseudo-random number generator, so that photon samples are uniformly filled in the state space, significantly accelerating the statistical convergence speed. This results in lower statistical variance with the same number of photon packets, laying the spatial and sampling foundation for subsequent efficient and high-precision scattering simulations.

[0034] S3: Perform initialization for each photon packet, setting the initial position, initial propagation direction, and normalized energy weights;

[0035] In this embodiment, the total number of photon packets is determined according to the set simulation control parameters. This embodiment employs a parallel computing mode, which will... The 250,000 photon packets are evenly distributed across 4 processor cores, with each core independently processing 250,000 photon packets. Within this parallel computing framework, each core maintains an independent Sobol sequence pointer, ensuring that random number sampling between different cores is independent.

[0036] For each photon packet, perform the following initialization operation:

[0037] For all photon packets, the initial position of the photon packet is set to the origin of the three-dimensional coordinate system. .in, The axial direction is the incident direction of the radar wave. and The axis forms a cross section perpendicular to the direction of propagation.

[0038] Set the initial propagation direction of the photon packet to a unit vector. Incident along the positive z-axis In this application, the x and y directions are not considered; therefore, the initial propagation direction can be simplified to... Set the energy weight of the photon packet After each photon packet is initialized, its state information is stored in memory as a structure. In parallel computing mode, each core pushes the initialized photon packet state into its respective processing queue in sequence, waiting for the propagation loop to process. The cumulative propagation step size of all photon packets is initialized to 0.

[0039] S4: Randomly generate the propagation step size, control the photon packet to propagate along the propagation direction in the simulation space, and update the current cumulative propagation step size of the photon packet;

[0040] Preferably, the random generation propagation step size includes:

[0041]

[0042] Where s represents the randomly generated propagation step size; denoted as a random number taken from a quasi-Monte Carlo low-difference sequence, and K represents the single extinction coefficient of clutter particles.

[0043] In this embodiment, each photon packet needs to generate a propagation step size multiple times during its propagation cycle. The system maintains a global Sobol sequence pointer (in parallel computing mode, each core maintains an independent pointer). When a step size needs to be generated, a one-dimensional random number is sequentially taken from the Sobol sequence. ; Calculate the random propagation step size, which represents the distance the photon packet moves in one continuous movement in the current propagation direction.

[0044] Update current cumulative propagation step size , The cumulative propagation step size represents the total distance that the photon packet has continuously traveled since the last scattering (or from the initial state). It is continuously accumulated when no scattering occurs and reset to zero after scattering occurs.

[0045] S5: Determine if the photon packet exceeds the simulation space boundary; if it does, record the transmitted or reflected energy and terminate the current photon packet; if it does not exceed the boundary, determine whether the photon packet is scattering based on the single extinction coefficient of the photon packet and the current cumulative propagation step size.

[0046] Preferably, determining whether photon packets are scattered includes:

[0047] The scattering probability is calculated based on the single extinction coefficient of the photon packet and the current cumulative propagation step size:

[0048]

[0049] in, This represents the scattering probability of a photon packet; Represents an exponential function; Indicates the single extinction coefficient of clutter particles; This indicates the current cumulative propagation step size of the photon packet;

[0050] Random numbers are drawn from the quasi-Monte Carlo low-dispersion sequence. If random number Less than the scattering probability If the random number is 0, then it is determined that the photon packet has been scattered. Greater than or equal to scattering probability If the photon packet is not scattered, then it is determined that no scattering has occurred.

[0051] If no scattering occurs, keep the propagation direction of the photon packet unchanged and return to step S4;

[0052] If scattering occurs, the scattering direction of the photon packet is updated based on the Henyey Greenstein phase function of the quasi-Monte Carlo low-difference sequence, the propagation direction of the photon packet is updated to the scattering direction, the energy weight of the photon packet is attenuated, and the current cumulative propagation step size of the photon packet is cleared to 0.

[0053] Preferably, updating the scattering direction of the photon packet based on the Henyey Greenstein phase function of the quasi-Monte Carlo low-difference sequence includes:

[0054] S51: Take random numbers from a quasi-Monte Carlo low-dispersion sequence ;

[0055] S52: Based on the asymmetry factor of clutter particles With random numbers Calculate the cosine of the photon packet scattering angle using the Henyey-Greenstein phase function:

[0056]

[0057]

[0058] in, The cosine of the photon packet scattering angle; Represents the intermediate calculation variables of the Henyey Greenstein phase function; The angle between the scattering direction of the photon packet and the initial propagation direction of the photon packet; The asymmetry factor representing clutter particles;

[0059] S53: Calculate the scattering angle of the photon packet based on the cosine of the scattering angle of the photon packet, and then obtain the scattering direction of the photon packet.

[0060] Preferably, the attenuation of the energy weight of the photon packet includes:

[0061]

[0062] in, Indicates the energy weight of the photon packet; Represents an exponential function; This indicates the current cumulative propagation step size of the photon packet; Indicates the single extinction coefficient of clutter particles;

[0063] Preferably, the calculation of the dynamic threshold includes:

[0064]

[0065] in, Indicates a dynamic threshold; This represents the base threshold for roulette; and Indicates preset parameters; Indicates the total number of photon packets; This indicates the current photon packet number.

[0066] In this embodiment, the current position of the photon packet is obtained, and it is determined whether it exceeds the simulation space boundary: if the position (z coordinate) of the photon packet in the initial propagation direction (Z-axis) exceeds the simulation space boundary (… If the photon packet is not received, its reflected energy is recorded. ; Indicates the current direction of propagation Component; if the position (z coordinate) of the photon packet in the initial propagation direction (Z-axis) exceeds the boundary of the simulation space ( If the photon packet is terminated, its transmission energy is recorded. ; Indicates the current direction of propagation The photon packet remains within the simulation space, and subsequent scattering judgments continue.

[0067] The scattering probability is calculated based on the single extinction coefficient of the photon packet and the current cumulative propagation step size. Take a random number from the quasi-Monte Carlo low-difference sequence. If random number Less than the scattering probability If the random number is 0, then it is determined that the photon packet has been scattered. Greater than or equal to scattering probability If so, it is determined that the photon packet has not been scattered;

[0068] Processing for cases where no scattering occurs: Keep the propagation direction of the photon packet unchanged, do not change the energy weight, do not clear the accumulated propagation step size, return to step S4, generate a new propagation step size and continue propagation;

[0069] Handling scattering: Take random numbers from the Sobol sequence According to the asymmetry factor of clutter particles With random numbers Calculate the cosine of the photon packet scattering angle using the Henyey-Greenstein phase function. ; Thus, the scattering direction angle is obtained. , This represents the inverse cosine function; the propagation direction is only considered in the Z-axis direction, while the x and y axes are not considered.

[0070] After scattering occurs, the current energy weight is decayed; the current cumulative propagation step size of the photon packet is then reduced. Reset to 0 for distance accumulation before the next scattering.

[0071] By calculating the scattering probability based on the cumulative propagation step size, a physically accurate determination of whether a photon packet is scattering is achieved. At the same time, by using the Henyey Greenstein phase function combined with the quasi-Monte Carlo low-difference sequence sampling scattering direction, the anisotropic scattering characteristics of clutter particles are accurately simulated, and the energy weight is exponentially decayed after scattering, which truly reflects the energy loss of electromagnetic waves during propagation. In addition, the completeness of statistical data is ensured by accurately judging the boundary of the simulation space and recording the transmitted / reflected energy.

[0072] S6: Calculate the dynamic threshold based on the roulette wheel betting base threshold, the current photon packet number, and the total number of photon packets; take a random sample value from the quasi-Monte Carlo low-difference sequence. If the survival probability of the photon packet is greater than the random sample value, the photon packet is determined to be alive, the energy weight of the photon packet is increased, and the process returns to step S4; if the survival probability of the photon packet is less than or equal to the random sample value, the photon packet is determined to be dead, and the current photon packet is terminated.

[0073] Preferably, the survival probability of the photon packet includes:

[0074]

[0075] in, This indicates the survival probability of the photon packet; Indicates the scattering efficiency of clutter particles; , These are preset parameters; H represents the coordinates of the photon packet in the initial propagation direction; H is the length of the simulation space in the initial propagation direction of the photon packet. This represents the component of the photon packet in the initial propagation direction; Represents an exponential function;

[0076] The energy weights of the amplified photon packet include:

[0077]

[0078] in, Indicates the energy weight of the photon packet; This represents the survival probability of the photon packet.

[0079] In this embodiment, it is assumed that the currently processed photon packet has completed several scatterings, and its energy weight has decayed to below the dynamic threshold calculated based on the current photon packet number and the basic threshold of the roulette wheel betting mechanism. Therefore, it enters the roulette wheel betting mechanism. The dynamic threshold is calculated based on the basic threshold of the roulette wheel betting mechanism, the current photon packet number, and the total number of photon packets. This threshold adaptively changes with the simulation progress, making it easier for later photon packets to enter the roulette wheel betting mechanism. Based on the current position and propagation direction cosine of the photon packet, combined with the scattering efficiency of clutter particles and preset boundary enhancement parameters, the survival probability of the photon packet is calculated. If the photon packet is located in the middle of the simulation space, the survival probability is directly taken as the scattering efficiency; if the photon packet is close to the incident or exit boundary, the survival probability is adjusted exponentially according to the direction cosine and position coordinates, so that photons that contribute more to backscattering or forward scattering have a higher chance of survival.

[0080] Then, a random sample value is sequentially taken from the quasi-Monte Carlo low-difference sequence (Sobol sequence) and compared with the survival probability. If the random sample value is less than the survival probability, the photon packet is determined to be alive, its energy weight is divided by the survival probability for amplification compensation, and then the process returns to step S4 to continue propagation; if the random sample value is greater than or equal to the survival probability, the photon packet is determined to be not alive, the photon packet is terminated directly, and it is no longer tracked.

[0081] Through an adaptive dynamic threshold roulette wheel mechanism, the threshold for entering the roulette wheel is dynamically adjusted based on the photon packet sequence number, making subsequent photons easier to process efficiently. Simultaneously, by combining photon position and propagation direction, the survival probability of critical backward or forward photons near the boundary is increased, achieving physically guided importance sampling and focusing computational resources on paths that significantly contribute to transmission and reflection energy. Crucially, when a photon packet survives, an energy weight amplification formula is used... The weights of surviving photons are precisely compensated so that the total expected energy carried by the remaining photons remains unchanged after terminating some photons, thus strictly guaranteeing statistical unbiasedness. When photons are not surviving, low-contribution photons are terminated in a timely manner to save computational costs. This step significantly reduces computational costs while maintaining simulation accuracy, effectively overcoming the shortcomings of traditional fixed-threshold roulette wheel betting, which suffers from unreasonable resource allocation and lacks strict unbiasedness guarantees, and significantly improving overall simulation efficiency and statistical reliability.

[0082] S7: After traversing all photon packets, the total transmitted energy and total reflected energy of all photon packets are counted, and the equivalent extinction coefficient and radar cross section are calculated.

[0083] Preferably, the calculated equivalent extinction coefficient and radar cross section include:

[0084]

[0085]

[0086] in, The equivalent extinction coefficient is... Radar cross section, This is the total transmitted energy (i.e., the sum of the transmitted energies of all photon packets). This is the total reflected energy (i.e., the sum of the reflected energies of all photon packets). The total number of photon packets. This represents the length of the simulated space.

[0087] In this embodiment, by statistically analyzing the total transmitted and reflected energy of all photon packets, the microscopic Monte Carlo scattering simulation results are transformed into the equivalent extinction coefficient (EXT) and radar cross section (RCS) that can be directly applied to the radar system, achieving a precise mapping from particle scattering physics to engineering parameters. Based on the law of large numbers, as the total number of photon packets increases, the statistical results asymptotically converge to the true values, ensuring the high accuracy and stability of the simulation output and providing a reliable quantitative evaluation basis for radar anti-clutter interference design.

[0088] Another aspect of the present invention provides a statistical scattering system for radar detection of clutter particles in the environment, the system comprising a memory and a processor; the memory for storing an application program; and the processor for running the application program to execute the statistical scattering method for radar detection of clutter particles in the environment.

[0089] Another aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the statistical scattering method for detecting clutter particles in the environment in radar detection.

[0090] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0091] In summary, this invention achieves physically guided importance sampling through an adaptive dynamic threshold roulette wheel mechanism. It dynamically adjusts the survival probability based on photon position and propagation direction, combined with energy weight compensation, focusing computational resources on key scattering paths while maintaining statistical unbiasedness, thus significantly improving simulation efficiency. Simultaneously, it introduces quasi-Monte Carlo low-discrepancy sequences to replace traditional pseudo-random numbers, ensuring uniform photon sample filling in the state space and significantly accelerating statistical convergence. Combining single-scattering parameter input based on actual particle scattering theories (Mie, TMatrix, etc.) with Henyey-Greenstein phase functions to accurately simulate anisotropic multiple scattering ensures the theoretical rigor and data accuracy of the model. Furthermore, the adaptive matching of simulation space length to clutter characteristics, support for parallel computing and multi-platform portability enable this scheme to efficiently and accurately simulate radar clutter scattering characteristics under complex environments such as rain, snow, and dust storms, providing reliable and universal simulation support for radar anti-jamming design, target detection algorithm optimization, and system performance evaluation.

[0092] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A statistical scattering method for clutter particles in an environment in radar detection, characterized by, include: S1: Obtain the single scattering parameters and simulation control parameters of the clutter particles. The single scattering parameters include the asymmetry factor, single extinction coefficient, and scattering efficiency. The simulation control parameters include the total number of photon packets and the roulette wheel betting threshold. S2: Dynamically determine the simulation space length based on the single extinction coefficient and asymmetry factor, and initialize the quasi-Monte Carlo low-difference sequence for random sampling; S3: Perform initialization for each photon packet, setting the initial position, initial propagation direction, and normalized energy weights; S4: Randomly generate the propagation step size, control the photon packet to propagate along the propagation direction in the simulation space, and update the current cumulative propagation step size of the photon packet; S5: Determine if the photon packet exceeds the simulation space boundary; if it does, record the transmitted or reflected energy and terminate the current photon packet; if it does not exceed the boundary, determine whether the photon packet is scattering based on the single extinction coefficient of the photon packet and the current cumulative propagation step size. If no scattering occurs, keep the propagation direction of the photon packet unchanged and return to step S4; If scattering occurs, the scattering direction of the photon packet is updated based on the Henyey Greenstein phase function of the quasi-Monte Carlo low-difference sequence, the propagation direction of the photon packet is updated to the scattering direction, the energy weight of the photon packet is attenuated, and the current cumulative propagation step size of the photon packet is cleared to 0. S6: Calculate the dynamic threshold based on the roulette wheel betting base threshold, the current photon packet number, and the total number of photon packets; take a random sample value from the quasi-Monte Carlo low-difference sequence. If the survival probability of the photon packet is greater than the random sample value, the photon packet is determined to be alive, the energy weight of the photon packet is increased, and the process returns to step S4; if the survival probability of the photon packet is less than or equal to the random sample value, the photon packet is determined to be dead, and the current photon packet is terminated. S7: After traversing all photon packets, the total transmitted energy and total reflected energy of all photon packets are counted, and the equivalent extinction coefficient and radar cross section are calculated.

2. A statistical scattering method for clutter particles in the environment in radar detection according to claim 1, characterized in that, The randomly generated propagation step size includes: Where s represents the randomly generated propagation step size; denoted as a random number taken from a quasi-Monte Carlo low-difference sequence, and K represents the single extinction coefficient of clutter particles.

3. The statistical scattering method for detecting clutter particles in the environment in radar detection according to claim 1, characterized in that, The length of the simulation space includes: in, Indicates the length of the simulation space; This represents the dynamic adjustment factor; K represents the single extinction coefficient of clutter particles. This represents a preset empirical constant, typically ranging from 1.3 to 1.

5. The asymmetry factor representing clutter particles.

4. The statistical scattering method for detecting clutter particles in the environment in radar detection according to claim 1, characterized in that, The determination of whether photon packets are scattered includes: The scattering probability is calculated based on the single extinction coefficient of the photon packet and the current cumulative propagation step size: in, This represents the scattering probability of a photon packet; Represents an exponential function; Indicates the single extinction coefficient of clutter particles; This indicates the current cumulative propagation step size of the photon packet; Random numbers are drawn from the quasi-Monte Carlo low-dispersion sequence. If random number Less than the scattering probability If the random number is 0, then it is determined that the photon packet has been scattered. Greater than or equal to scattering probability If the photon packet is not scattered, then it is determined that no scattering has occurred.

5. The statistical scattering method for detecting clutter particles in the environment in radar detection according to claim 1, characterized in that, The quasi-Monte Carlo low-difference sequence is The Sobol sequence of the interval; the update of the scattering direction of the photon packet based on the Henyey Greenstein phase function of the quasi-Monte Carlo low-difference sequence includes: S51: Take random numbers from a quasi-Monte Carlo low-dispersion sequence ; S52: Based on the asymmetry factor of clutter particles With random numbers Calculate the cosine of the photon packet scattering angle using the Henyey-Greenstein phase function: in, The cosine of the photon packet scattering angle; Represents the intermediate calculation variables of the Henyey Greenstein phase function; The angle between the scattering direction of the photon packet and the initial propagation direction of the photon packet; The asymmetry factor representing clutter particles; S53: Calculate the scattering angle of the photon packet based on the cosine of the scattering angle of the photon packet, and then obtain the scattering direction of the photon packet.

6. The statistical scattering method for detecting clutter particles in the environment in radar detection according to claim 1, characterized in that, The attenuation of the energy weight of the photon packet includes: in, Indicates the energy weight of the photon packet; Represents an exponential function; This indicates the current cumulative propagation step size of the photon packet; Indicates the single extinction coefficient of clutter particles; The calculation of the dynamic threshold includes: in, Indicates a dynamic threshold; This represents the base threshold for roulette; and Indicates preset parameters; Indicates the total number of photon packets; This indicates the current photon packet number.

7. The statistical scattering method for detecting clutter particles in the environment in radar detection according to claim 1, characterized in that, The survival probability of the photon packet includes: in, This indicates the survival probability of the photon packet; Indicates the scattering efficiency of clutter particles; , These are preset parameters; H represents the coordinates of the photon packet in the initial propagation direction; H is the length of the simulation space in the initial propagation direction of the photon packet. This represents the component of the photon packet in the initial propagation direction; Represents an exponential function; The energy weights of the amplified photon packet include: in, Indicates the energy weight of the photon packet; This represents the survival probability of the photon packet.

8. The statistical scattering method for detecting clutter particles in the environment in radar detection according to claim 1, characterized in that, The calculated equivalent extinction coefficient and radar cross section include: in, The equivalent extinction coefficient is... Radar cross section, This represents the total transmitted energy. The total reflected energy, The total number of photon packets. This represents the length of the simulated space.

9. A statistical scattering system for radar detection of clutter particles in the environment, characterized in that, The system includes a memory and a processor; the memory is used to store an application program; the processor is used to run the application program and execute a statistical scattering method for detecting clutter particles in the environment in radar, as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements a statistical scattering method for detecting clutter particles in the environment as described in any one of claims 1 to 8.

Images