 Time-of-arrival–based localization algorithm in mixed line-of-sight/non-line-of-sight environmentsPeixin Wang, Youming Li, Shengming Chang, Xiaoping Jin and Xiaoli Wang International Journal of Distributed Sensor Networks, 2020, vol. 16, issue 3, 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. Keywords: Localization; time-of-arrival; non-line-of-sight; mixed semi-definite and second-order cone relaxation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:16:y:2020:i:3:p:1550147720913808 Access Statistics for this article More articles in International Journal of Distributed Sensor Networks |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.