Scholarlink

<p>This paper investigates detecting a far-field dynamic particle source using cubical and spherical directional arrays. First, we present a discussion on likelihood ratio test (LRT), generalized LRT (GLRT) and truncated mean test (TMT) in case of a cubical array, considering scenarios with stationary and moving targets. Further, two underlying sub-cases are considered, including the sets of correlated and independent and identically distributed observations. Next, we consider the case of a spherical array where LRT, GLRT and TMT are discussed. In all cases, we present an analysis in terms of probabilities of detection and false-alarm for the associated hypothesis testing problems. Through simulations, we show that TMT outperforms the other existing tests in the literature, namely the mean difference test, the source intensity test, and the GLRT.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Cubical and spherical directional array-based particle source detection with poisson statistics

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月4日

查看全文
  • Sahana Srikanth,
  • Sanjeev Gurugopinath,
  • Koshy George

摘要

This paper investigates detecting a far-field dynamic particle source using cubical and spherical directional arrays. First, we present a discussion on likelihood ratio test (LRT), generalized LRT (GLRT) and truncated mean test (TMT) in case of a cubical array, considering scenarios with stationary and moving targets. Further, two underlying sub-cases are considered, including the sets of correlated and independent and identically distributed observations. Next, we consider the case of a spherical array where LRT, GLRT and TMT are discussed. In all cases, we present an analysis in terms of probabilities of detection and false-alarm for the associated hypothesis testing problems. Through simulations, we show that TMT outperforms the other existing tests in the literature, namely the mean difference test, the source intensity test, and the GLRT.