Robust NLOS Bias Mitigation for Hybrid RSS-TOA Based Source Localization Under Unknown Transmission Parameters

This letter addresses the problem of source localization in non-line of sight (NLOS) environment using received signal strength (RSS) and time of arrival (TOA) measurements when both transmission time and power are unknown. To mitigate the NLOS bias, a robust weighted least square (RWLS) problem is formulated from original non-convex maximum-likelihood (ML) estimation problem using a set of tight approximations. The RWLS problem is further tightened by a novel convex-hull constraint and is ultimately solved using second-order cone programming (SOCP). Simulation results confirm the optimal performance of the proposed robust method in various network scenarios and also validate its excellence over state-of-art methods.

Automated summary

This study proposes a robust method for source localization using RSS and TOA measurements in NLOS environments. By formulating a RWLS problem from the original non-convex ML estimation problem and tightening it with a convex-hull constraint, the NLOS bias is mitigated. Simulation results demonstrate the superior performance of the proposed method in various network scenarios and its excellence over existing methods.