Polarimetric Detection in Compound Gaussian Clutter with Kronecker Structured Covariance Matrix

Yikai Wang, Wei Xia, Zishu He, Hongbin Li, Athina P. Petropulu

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

In this paper, we consider polarimetric adaptive detection in compound Gaussian clutter whose covariance matrix (CM) has a Kronecker structure. We derive the Cramér-Rao bound of a Kronecker structured CM estimate and analyze the constant false alarm rate property of the adaptive subspace matched filter detector that uses Kronecker structured estimates. We provide a general expression for the average signal-to-clutter ratio loss (SCRL) as a function of the mean square error of the covariance estimate. The aforementioned expression is helpful in determining how many samples are required in order to achieve a desired average SCRL level in practical scenarios. Based on that expression, we show that the required sample size can be effectively reduced by exploiting the Kronecker structure of the clutter CM. We also derive the asymptotic detection performance of the adaptive subspace matched filter. The analysis of SCRL and detection performance can be extended to more general scenarios, especially when the maximum-likelihood estimate of the structured CM involves solving fixed point equations. Numerical simulations validate the merits of the proposed methods.

Original languageEnglish
Article number7950961
Pages (from-to)4562-4576
Number of pages15
JournalIEEE Transactions on Signal Processing
Volume65
Issue number17
DOIs
StatePublished - 1 Sep 2017

Keywords

  • Cramér-Rao bound
  • Kronecker structure
  • Polarimetric detection
  • SCR loss
  • asymptotic performance
  • compound Gaussian clutter
  • constant false alarm rate

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