A nonparametric approach to signal detection in impulsive interference

Impulsive interference poses a challenge to conventional detection techniques. The α-stable distribution, while sometimes providing a good model for impulsive interference, has proven to be no exception. Some of these difficulties have motivated the investigation and development of computationally tractable, locally suboptimum correlation, and rank correlation detectors for signals embedded in impulsive interference modeled as a symmetric α-stable process. The performance of some of these detectors is evaluated and compared with that of the locally optimum (LO), locally optimum rank (LOR), matched filter, and Cauchy detectors. Simulation results show that a rank-based detector is able to approach the performance of the computationally intensive LO and LOR detectors across a range of values for for α