Minimum-Based Sliding Window Detectors in Correlated Pareto Distributed Clutter

Recent investigations have resulted in the derivation of a multivariate Pareto model, which is consistent with the compound Gaussian model framework, allowing one to describe statistically a correlated Pareto distributed sequence. This has permitted the development of noncoherent sliding window detection processes, for operation in an X-band maritime surveillance radar context, which account for correlated clutter returns. Based upon this multivariate Pareto model, the structure of the sample minimum is investigated, which can then be used to produce decision rules robust to interference. Two such detectors will be examined, and their performance in real high-resolution X-band maritime radar clutter will be investigated. It will be shown that a number of avenues of future work are available.