A robust estimator and detector of circularity of complex signals

Recent research has revealed that circularity (or, propriety) of complex random signals can be exploited in developing optimal signal processors. In this paper, a robust estimator of circularity is pro posed. The estimate is found by solving M-estimation equations and employing a novel weighting scheme. A simple iterative algorithm for its computation is introduced. A robust circularity detector stemming from the large sample properties of the estimator is proposed. It is shown to be valid detector under the broad class of complex elliptically symmetric (CES) distributions. An illustrative example demonstrating the reliable performance of the detector in a practical signal processing application is provided.