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 local-ization accuracy and reduce the system energy consump-tion, we propose an improved RSS localization algorithm based on the joint sensor selection and semidefinite pro-gramming (SDP). An initial position estimate is first ob-tained using RSSs available at a random set of sensors. A refined sensor set is then selected to complete the sec-ond 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 locali-zation accuracy of approximately 1.5 m with 8 to 10 sen-sors. The method outperforms the second-order cone pro-gramming (SOCP) and the least squared relative error (LSRE)-based SDP algorithms in terms of both the loca-tion and the transmit power estimation accuracy.