Second Order Cone Programming for Sensor Node Localization in Mixed LOS/NLOS Conditions

TL;DR

This paper introduces a second order cone programming approach for sensor node localization that efficiently handles mixed LOS/NLOS conditions, outperforming existing methods in accuracy and computational complexity.

Contribution

The paper presents the first application of SOCP to sensor localization in mixed LOS/NLOS environments, offering a computationally efficient and robust alternative to SDP-based methods.

Findings

Outperforms similar methods in accuracy

Computational complexity is quadratic in neighbors

Effective in real field deployments

Abstract

In this paper, a novel method for sensor node localization under mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions based on second order cone programming (SOCP) is presented. SOCP methods have, hitherto, not been utilized in the node localization under mixed LOS/NLOS conditions. Unlike semidefinite programming (SDP) formulation, SOCP is computationally efficient for resource constrained ad-hoc sensor network. The proposed method can work seamlessly in mixed LOS/NLOS conditions. The robustness of the method is due to the fair utilization of all measurements obtained under LOS and NLOS conditions. The computational complexity of this method is quadratic in the number of nearest neighbours of the unknown node. Extensive simulations and real field deployments are used to evaluate the performance of the proposed method. The experimental results of the proposed method is reasonably better when compared to similar methods in literature.