Uncooperative Emitter Localization Based on Joint Sensor Selection and Semidefinite Programming

Abstract

. Radio emitter localization based on Received Signal Strength (RSS) is promising in large-scale Internet of Things (IoT) and wireless sensor networks (WSNs) for its low hardware and computation costs. To improve its localization accuracy and reduce the system energy consumption, we propose an improved RSS localization algorithm based on the joint sensor selection and semidefinite programming (SDP). An initial position estimate is first obtained using RSSs available at a random set of sensors. A refined sensor set is then selected to complete the second estimation by analyzing the geometric structure of sensing network. Performance of the method is evaluated in terms of localization accuracy and execution time, and compared with existing methods. Extensive simulations demonstrate that the proposed approach achieves a localization accuracy of approximately 1.5 m with 8 to 10 sensors. The method outperforms the second-order cone programming (SOCP) and the least squared relative error (LSRE)-based SDP algorithms in terms of both the location and the transmit power estimation accuracy.