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A Novel Gamma Distributed Random Variable (RV) Generation Method for Clutter Simulation with Non-Integral Shape

Shichao Chen1, Feng Luo1, Chong Hu1

  • 1National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China.

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|February 15, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a new Gamma distribution method for simulating sea clutter, overcoming limitations of existing zero memory non-linear and spherically invariant random process techniques. The novel approach offers improved accuracy for radar detector analysis.

Keywords:
Gamma distributionclutter simulationcompound Gaussian distributed model

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Area of Science:

  • Radar Systems Engineering
  • Signal Processing
  • Statistical Modeling

Background:

  • Sea clutter simulation is crucial for radar detector analysis and design.
  • Current methods like zero memory non-linear (ZMNL) and spherically invariant random process (SIRP) have limitations.
  • ZMNL struggles with non-integer shape parameters, while SIRP has high computational complexity.

Purpose of the Study:

  • To propose a novel method for simulating sea clutter using Gamma distributed random variables.
  • To overcome the limitations of existing ZMNL and SIRP methods.
  • To achieve higher fitting accuracy in sea clutter simulation.

Main Methods:

  • Developed a new method to generate Gamma random variables (RV) with non-integral or non-semi-integral shape parameters.
  • Generated Gamma RV by multiplying an integral-shape-parameter Gamma RV with a Beta RV (parameters > 0.5).
  • This approach avoids simulation deviations associated with Beta RV.

Main Results:

  • The proposed method successfully generates Gamma RV for non-integer/non-semi-integer shape parameters.
  • Simulation experiments demonstrate a higher fitting degree compared to existing methods.
  • The method is applicable to complex sea clutter scenarios.

Conclusions:

  • The novel Gamma distributed RV generation method effectively simulates sea clutter.
  • It offers improved accuracy and flexibility over ZMNL and SIRP.
  • This advancement benefits radar detector analysis and design.