A nonparametric approach to signal detection in impulsive interference

Impulsive interference poses a challenge to conventional detection techniques. The alpha-stable distribution, while sometimes providing a goad 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 alpha-stable process. The performance of same 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 alpha.