Three-Dimensional Location Estimation Using Biased RSS Measurements

Received signal strength (RSS)-based techniques are promising for location estimation because of low cost and easy implementation. RSS measurements can be used to determine the location of a receiver, given the positions of multiple emitters. In addition, RSS measurements at receivers with known positions can be used to determine the location of an emitter. This article investigates both 3-D receiver navigation and source localization using RSS measurements. In practice, sensor measurements are often biased owing to design problems or other effects. However, almost all existing methods deal with bias-free cases. In contrast, we focus on biased cases. For both receiver navigation and source localization, we propose united-RSS (URSS) and differential-RSS (DRSS) approaches, where URSS estimates the location and sensor bias together, while DRSS estimates the location by eliminating the effect of bias. They are based on semidefinite programming and constrained least squares, respectively. The proposed methods avoid the nonconvexity in the maximum likelihood method. Numerical examples verify the necessity for sensor registration in RSS-based location estimation and show better performance of the proposed methods.