Chen Shichao, Luo Feng, Hu Chong
National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China.
Sensors (Basel). 2020 Feb 11;20(4):955. doi: 10.3390/s20040955.
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.
海杂波模拟是雷达探测器分析与设计中一项广为人知的研究工作，近年来已提出了许多方法，其中零记忆非线性（ZMNL）和球不变随机过程（SIRP）是复合高斯分布最常用的两种方法。然而，在ZMNL方法中，复合高斯杂波模型的形状参数不能为非整数或非半整数，并且由于复杂的非线性运算，SIRP方法的计算复杂度非常高。尽管已提出一些改进方法来解决该问题，但由于引入了贝塔分布，这些方法的拟合度不高。为克服这些缺点，本文提出一种用于杂波模拟的新型伽马分布随机变量（RV）生成方法。在我们的方法中，通过将具有整数形状参数的伽马RV与参数大于0.5的贝塔RV相乘，直接生成具有非整数或非半整数形状参数的伽马RV，从而避免了贝塔RV模拟的偏差。大量仿真实验结果表明，所提方法不仅可用于具有非整数或非半整数形状参数值的杂波模拟，而且拟合度比现有方法更高。
