Source Localization Based on Hybrid AOA, TDOA, and RSS Measurements

• Published in: IEEE sensors journal Vol. 23; no. 14; p. 1
• Main Authors: Zou, Yanbin, Wu, Wenbo, Zhang, Zekai
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.07.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Angle of arrival; Angle-of-arrival (AOA); Constraints; fixed point iteration (FPI); iterative constrained weighted least squares (ICWLS); Iterative methods; Lagrange multiplier; Least squares; Localization; Maximum likelihood estimators; received-signal-strength (RSS); Semidefinite programming; semidefinite programming (SDP); Signal strength; time-difference-of-arrival (TDOA)
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2023.3283276

In this paper, a constrained weighted least squares (CWLS) problem with two quadratic constraints for hybrid AOA, TDOA, and RSS localization is formulated. The Lagrange multiplier method cannot be efficiently used in this situation, so we provide four methods to solve the CWLS problem: 1) weighted least squares (WLS); 2) iterative constrained weighted least squares (ICWLS); 3) Lagrange multiplier method combined with Newton's method (LMM+NM); 4) semidefinite programming (SDP). Furthermore, in order to obtain a good balance between accuracy and computational burden, we develop a fixed point iteration (FPI)-based algorithm that is derived from an approximate maximum likelihood estimator (MLE). Simulation results show that the accuracy of the proposed FPI method is better than the other four methods; besides, its computational burden is one in ten of the SDP algorithm.