Radar detection of correlated targets in clutter

This paper provides general models of radar echoes from a target. The rationale of the approach is to consider the echoes as the output of a linear dynamic system driven by white Gaussian noise. Two models can be conceived to generate N target returns: samples generated as a batch, or sequentially generated one by one. The theory of 'estimator-correlator' receiver is applied to the case of a Gaussian-distributed time-correlated target embedded in clutter and thermal noise. Two equivalent detection schemes are obtained. A combined analytic-numeric method has been conceived to obtain a set of original detection curves related to operational cases of interest, and an adaptive implementation of the proposed processor is suggested with reference to the problem of on-line estimation of the clutter covariance matrix and of the CFAR threshold. In both cases, detection loss due to adaptation has been evaluated by means of a Monte Carlo simulation approach.