Analysis of Weak Signal Detectors Under Moving Average of Impulsive Noise

Abstract

The performance of weak signal detectors is addressed in additive noise described by the first order moving average (FOMA) of an impulsive process. The decision regions of the maximum likelihood (ML) and suboptimum ML (S-ML) detectors are derived in the FOMA model. The ML and S-ML detectors are employed in the antipodal signaling system, and compared in terms of the bit-error-rate performance in impulsive environment. Numerical results show that the S-ML detector, despite its reduced complexity and simpler structure, exhibits practically the same performance as the ML detector. It is also shown that the performance gap between detectors for FOMA and independent and identically distributed noise becomes larger as the degree of noise impulsiveness increases.