Abstract

Sea clutter simulation is a well-known research endeavour in radar detector analysis and design, and many approaches to it have been proposed in recent years, among which zero memory non-linear (ZMNL) and spherically invariant random process (SIRP) are the most two widely used methods for compound Gaussian distribution. However, the shape parameter of the compound Gaussian clutter model cannot be a non-integer nor non-semi-integer in the ZMNL method, and the computational complexity of the SIRP method is very high because of the complex non-linear operation. Although some improved methods have been proposed to solve the problem, the fitting degree of these methods is not high because of the introduction of Beta distribution. To overcome these disadvantages, a novel Gamma distributed random variable (RV) generation method for clutter simulation is proposed in this paper. In our method, Gamma RV with non-integral or non-semi-integral shape parameters is generated directly by multiplying an integral-shape-parameter Gamma RV with a Beta RV whose parameters are larger than 0.5, thus avoiding the deviation of simulation of Beta RV. A large number of simulation experimental results show that the proposed method not only can be used in the clutter simulation with a non-integer or non-semi-integer shape parameter value, but also has higher fitting degree than the existing methods.

Highlights

  • Clutter is one of the main factors restricting radar target detection and tracking performance

  • The research on sea clutter is of great significance for radar detection and system design [1,2]

  • An improved Gamma distributed random variable (RV) generation method is proposed in this paper

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Summary

Introduction

Clutter is one of the main factors restricting radar target detection and tracking performance. A method of simulation of coherent compound Gaussian clutter based on memorials non-linear transformation (MNLT) is proposed in [15]. Similar to SIRP method, the computational complexity of MNLT is high due to nonlinear computation To solve this problem, the additive property of Gamma RV is used to improve the ZMNL and SIRP methods in [16,17], in which the shape parameter of the compound Gaussian distribution is the same as the Gamma distribution. Density Function (PDF) because the simulation of Beta RV is deviated when the parameter is small, which will affect the obtained Gamma RV, and lead to the final clutter error To overcome this disadvantage, an improved Gamma distributed RV generation method is proposed in this paper. A large number of simulation experiments verify the effectiveness of our method

Compound Gaussian Distribution
Problem Formulation
Limitation of Beta
Y 1
Method for Clutter
Simulation of Compound Gaussian Distributed Clutter
U11 U11 U21
Simulation Results
Conclusions
Results and Applications
Full Text
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