Locally optimum distributed detection of dependent random signals based on ranks

Abstract

Distributed signal detection schemes based on observations which are dependent from sensor to sensor are studied. Cases where weak random signals are observed in possibly non-Gaussian additive noise are considered. The focus is on cases where the sensor tests are based only on the ranks and signs of the observations. We find analytical forms for the best (locally optimum) sensor test statistics for such cases, and we use these to find the best distributed detection schemes for some cases.<>