Optimal Sensor Placement Using Decentralized TDOA Sensor Network in Source Localization

Abstract

Most existing studies for time difference of arrival (TDOA)-based source localization adopt a centralized framework that utilizes one sensor as a reference to generate arrival time differences. This work considers adecentralized sensor network to acquire TDOAs for localization, which has lower communication cost, less synchronization requirement and higher flexibility compared to the centralized approach. In particular, the focus is on finding the optimal sensor placement that achieves the best positioning accuracy. We first formulate a general decentralized TDOA source localization system consisting of multiple sensor groups with different numbers of sensors(at least two sensors) in each. By minimizing the trace of the Cramér–Rao lower bound, the optimal performance limit and sensor placement strategy are established. We next extend the derivation and analysis to scenarios with spatial constraints and propose an efficient numerical optimization algorithm. Finally, extensive simulation examples verify the theoretical findings and the effectiveness of the optimized sensor placement strategy.