Detection and parameter estimation of a transient signal using order statistics

Detection and parameter estimation of a transient signal in noise is a problem of many applications. It is characterized by the fact that some of the measurements consist of noise only. Modern statistical signal processing techniques are applied on a discrete version of the received data and are implemented by digital signal processing (DSP). In this correspondence, we show how order statistics (OS)-based signal processing, which is of a discrete nature, can be used for simultaneous detection and estimation of parameters (such as time of arrival and signal duration) of a sampled transient signal in white noise. We show that the resulting processors are more robust than the conventional processors, whereas their performance is about the same, at the cost of increased computational complexity.