The cell averaging constant false alarm rate detector has been assumed to be optimal for detecting Swerling I targets embedded in exponential clutter and noise of unknown power. This is because the detector uses a minimum variance unbiased estimate (which is also a maximum likelihood estimate) of the unknown clutter-plus-noise power to set the threshold. The authors prove, using a result concerning least favorable distributions in composite hypotheses testing, that the cell averaging detector is indeed optimal in that it is a uniformly most powerful detector.>

The use of filters and detectors based on amplitude-ordered data has become quite popular in applications such as image and radar signal processing. However, current data quantization schemes do not take into account the amplitude-ordered data and therefore may not perform optimally. The problem of determining optimum quantizers for ordered data is considered. Two different design approaches are presented, and performance characteristics of quantizers obtained using the two approaches are given.>

For restoration of nonstationary signals in impulsive noise the combination or C-filter uses rank-order dependent coefficients in an FIR (finite-impulse response) filter structure. This allows frequency selectivity as well as edge-preservation and impulse rejection. The nonlinear C-filter design is facilitated by the use of an LMS (least-mean-squares) algorithm. This approach is explained and examples are given of C-filter performance for one- and two-dimensional signals.>