Time-of-arrival–based localization algorithm in mixed line-of-sight/non-line-of-sight environments

Peixin Wang,Shengming Chang,Xiaoping Jin,Youming Li,Xiaoli Wang

doi:10.1177/1550147720913808

Abstract

A novel time-of-arrival–based localization algorithm in mixed line-of-sight/non-line-of-sight environments is proposed. First, an optimization problem of target localization in the known distribution of line-of-sight and non-line-of-sight is established, and mixed semi-definite and second-order cone programming techniques are used to transform the original problem into a convex optimization problem which can be solved efficiently. Second, a worst-case robust least squares criterion is used to form an optimization problem of target localization in unknown distribution of line-of-sight and non-line-of-sight, where all links are treated as non-line-of-sight links. This problem is also solved using the similar techniques used in the known distribution of line-of-sight and non-line-of-sight case. Finally, computer simulation results show that the proposed algorithms have better performance in both the known distribution and the unknown distribution of line-of-sight and non-line-of-sight environments.

Highlights

In recent years, localization technology in wireless sensor network has been widely used in many fields such as target tracking, navigation, and communication
The proposed method improves the localization performance compared with the other methods, which is verified by simulation results
The main contributions of this article are summarized as follows: 1. The optimization problems of target localization in the known and unknown distribution of LOS and NLOS are established, which are transformed into convex optimization problems using the mixed semi-definite and secondorder cone programming (SOCP) techniques

Summary

Introduction

Localization technology in wireless sensor network has been widely used in many fields such as target tracking, navigation, and communication. Chan et al.[8] discussed localization problem when the number of LOS/NLOS links is known, and proposed an optimization problem using LOS information. We discuss a TOA-based target localization method under the condition of known and unknown distribution of LOS/NLOS, respectively.

Results

Conclusion