Submarine Location Estimation via a Network of Detection-Only Sensors

It is well known to active-sonar engineers that the reflected signal from a target can be highly aspect-dependent, hence in many cases only receivers located in a particular zone determined by the source/target receive-geometry and the target aspect can detect the return signal. Thus, submarines can hide well from traditional sonar systems. For these low-visibility targets, we propose a target localization paradigm based on a distributed sensor network which consists of low complexity sensors that only report binary detection results. Based on the binary outputs and the positions of the sensors, we develop optimal maximum likelihood and suboptimal line-fitting based estimators, and derive the Cramer-Rao lower bound on estimation accuracy, for both single-source and multi-source settings. Our numerical results verify the feasibility of the proposed estimators. We do not rely on continuous quantities such as signal strength, direction of arrival, time or time-difference of arrival, and instead localize based on discrete detection results which include both false alarms and missed detections.