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 binary outputs and the positions of the sensors, we develop optimal maximum likelihood and suboptimal line-fitting-based estimators and derive the Crameacuter-Rao lower bound on estimation accuracy. We extend our results from single source to multisource settings, both with and without explicit incorporation of a reflection model that links the target orientation to the propagation direction. 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