F. Gini et al., Clairvoyant and adaptive signal detection in non-Gaussian clutter: A data-dependent threshold interpretation, IEEE SIGNAL, 47(6), 1999, pp. 1522-1531
This paper addresses the problem of signal detection in correlated non-Gaus
sian clutter modeled as a spherically invariant random process. The optimum
strategy to detect a constant signal, with either known or unknown complex
amplitude, embedded in correlated Gaussian clutter is given by comparing t
he whitening-matched filter output with a fixed threshold. When the clutter
is non-Gaussian, the performance of the matched filter sensibly degrades,
The optimum strategy is the classical whitening-matched filter output compa
red with a data-dependent threshold. This interpretation provides a deeper
insight into the structure of the optimum detector and allows us to single
out a family of suboptimum detectors based on a polynomial approximation of
the data-dependent threshold. They are easy to implement and have performa
nce that is really close to the optimal. The adaptive implementation of the
polynomial detectors is also investigated, and their performance is analyz
ed by means of Monte Carlo simulation for various clutter scenarios.