Title :
A GLRT detector for bursty targets in multiplicative noise
Author_Institution :
Dept. of Math., Bucknell Univ., Lewisburg, PA, USA
fDate :
5/1/1999 12:00:00 AM
Abstract :
A robust generalized likelihood ratio test (GLRT) detector is derived for targets in multiplicative noise with gamma-Weibull statistics. The target is assumed to have a spatial distribution (burstiness) modeled by the incomplete binomial distribution. The GLRT detector is found to be similar in performance to the optimized power law detector.
Keywords :
Weibull distribution; binomial distribution; gamma distribution; maximum likelihood detection; noise; GLRT detector; bursty targets; gamma-Weibull statistics; generalized likelihood ratio test; incomplete binomial distribution; maximum likelihood estimates; multiplicative noise; optimized power law detector; performance; spatial distribution; Additive noise; Background noise; Detectors; Image sensors; Maximum likelihood estimation; Random variables; Signal to noise ratio; Statistical analysis; Statistical distributions; Testing;
Journal_Title :
Signal Processing Letters, IEEE
