2D Location estimation of angle-only sensor arrays using targets of opportunity

Abstract

Passive acoustic sensor arrays for tracking ground targets are becoming increasingly popular due to their low cost and ease of deployment. In this paper we present an algorithm for locating sensor arrays in two-dimensions in an acoustic network (or in any network where angle-only measurements are used) when external references, such as GPS or known-location targets, are unavailable. We consider sensor localization when angular measurements are taken from the sensor arrays to targets of opportunity when all sensors take measurements with respect to a common axis of unknown orientation and where the sensors can not “see” each other. The solutions provided consist of low-complexity (generally closed-form) methods of getting initial estimates with no prior information, followed by maximum likelihood (ML) optimization to refine the estimates. Simulation shows that the accuracy approaches the Cramér Rao Lower Bound (CRLB), something that similar algorithms from previous research have been unable to achieve.