Time-of-arrival–based localization algorithm in mixed line-of-sight/non-line-of-sight environments. (March 2020)

• Record Type: Journal Article
• Authors: Wang, Peixin; Li, Youming; Chang, Shengming; Jin, Xiaoping; Wang, Xiaoli
• Is Part Of: International journal of distributed sensor networks. Volume 16:Number 3(2020)
• Publication Date: 2020-03
• Subjects: Localization -- time-of-arrival -- non-line-of-sight -- mixed semi-definite and second-order cone relaxation; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147720913808
• Languages: English
• ISSNs: 1550-1329

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.