Entropy based detection on the time-frequency plane

A comprehensive theory for time-frequency based signal detection has been developed during the past decade. The time-frequency detectors proposed in the literature are linear structures operating on the time-frequency representation of the signals and are equivalent to quadratic receivers that are defined in the time domain. We introduce the concept of entropy based detection on the time-frequency plane. In recent years, Renyi entropy has been proposed as an effective measure for quantifying signal complexity on the time-frequency plane and some important properties of this measure have been proven. A new approach that uses the entropy functional as the test statistic for signal detection is developed. A minimum error detection algorithm is derived and the performance of this new signal detection method is demonstrated through examples.