Open AccessAn Improved Algorithm for TDOA Trajectory Tracking
Author(s) -
Beibei Li,
Zhanjun Hao,
Xiaochao Dang
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/569/2/022033
Subject(s) - multilateration , non line of sight propagation , computer science , trajectory , synchronization (alternating current) , real time computing , base station , tracking (education) , position (finance) , time of arrival , algorithm , positioning system , wireless , channel (broadcasting) , telecommunications , engineering , mathematics , azimuth , psychology , pedagogy , physics , geometry , structural engineering , finance , astronomy , node (physics) , economics
In a precision positioning system, one important source of positioning error is the clock synchronization problem, which is caused by multiple base stations. Therefore, eliminating the clock synchronization problem in a no-line-of-sight (NLOS) environment plays an important role in reducing errors in a positioning system. To address this problem, this study designs a practical experimental environment and proposes the concepts of Time Difference of Arrival (TDOA) and non-line-of-sight-Time Difference of Arrival (N-TDOA). First, the improved TDOA algorithm is used to determine the tag’s position; second, the tag’s trajectory is drawn at different times; then, a map of the monitored area is loaded, and the tag trajectory is displayed in the actual experimental environment. The experimental results show that the N-TDOA algorithm synchronizes the base stations at the algorithmic layer; thus, deploying network cables or wires to achieve clock synchronization is unnecessary: wireless deployment can be used. In an NLOS environment, the N-TDOA method significantly improves the positioning accuracy compared with that of other algorithms, which facilitates further trajectory tracking research. Overall, the proposed approach improves both the accuracy and stability of trajectory tracking.