Comparison of GLR and invariant detectors under structured cluttercovariance
Hyung Soo Kim; Hero, A.O., III
Image Processing, IEEE Transactions on
Volume 10, Issue 10, Oct 2001 Page(s):1509 - 1520
Digital Object Identifier 10.1109/83.951536
Summary:This paper addresses a target detection problem in radar imaging
for which the covariance matrix of unknown Gaussian clutter has block
diagonal structure. This block diagonal structure is the consequence of
a target lying along a boundary between two statistically independent
clutter regions. Here, we design adaptive detection algorithms using
both the generalized likelihood ratio (GLR) and the invariance
principles. There has been considerable interest in applying invariant
hypothesis testing as an alternative to the GLR test. This interest has
been motivated by several attractive properties of invariant tests
including: exact robustness to variation of nuisance parameters and
possible finite-sample min-max optimality. However, in our deep-hide
target detection problem, there are regimes for which neither the GLR
nor the invariant tests uniformly outperforms the other. We discuss the
relative advantages of GLR and invariance procedures in the context of
this radar imaging and target detection application
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