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<p>In this paper, we develop censored maximum-likelihood estimation (CMLE) and Bayes estimation methods for the compound inverse Gaussian (CIG) clutter model shape parameter under Type-II right censoring. The joint likelihood function is derived, and numerical solutions for both CMLE and Bayes estimators are obtained for a known clutter mean parameter. For comparison purposes, standard MLE and [z log(z)] approaches are considered. Monte-Carlo (MC) simulations are conducted to evaluate estimator performance in terms of Bias and mean square error (MSE). Through simulated and Intelligent PIXel X-band radar (IPIX) real data, results show that Bayesian and CMLE estimator remain the most reliable, offering low bias and MSE, making them ideal for clutter modeling under censoring conditions.</p>

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Parameter estimation of CIG radar clutter using Bayes and right censored samples methods

  • 期刊论文

  • 发表日期：

    2026年3月10日

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  • Khaled Zebiri,
  • Amar Mezache

摘要

In this paper, we develop censored maximum-likelihood estimation (CMLE) and Bayes estimation methods for the compound inverse Gaussian (CIG) clutter model shape parameter under Type-II right censoring. The joint likelihood function is derived, and numerical solutions for both CMLE and Bayes estimators are obtained for a known clutter mean parameter. For comparison purposes, standard MLE and [z log(z)] approaches are considered. Monte-Carlo (MC) simulations are conducted to evaluate estimator performance in terms of Bias and mean square error (MSE). Through simulated and Intelligent PIXel X-band radar (IPIX) real data, results show that Bayesian and CMLE estimator remain the most reliable, offering low bias and MSE, making them ideal for clutter modeling under censoring conditions.