Paper Info
Title
Vehicle Localization Using Joint Doa/Toa Estimation Based On Tls-Esprit Algorithm
Abstract
In this paper, a high-resolution vehicle positioning estimation algorithm based on existing Vehicle to Infrastructure (V2I) communications is proposed to achieve joint estimation of vehicle target's direction of arrival (DOA) and time of arrival (TOA). We adopt the Estimating Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm based on total least squares (TLS) to estimate the DOA and TOA, and the vehicle location can be obtained from the estimated parameters. The TLS-ESPRIT algorithm not only has a relatively small amount of computation to meet the real-time requirements of vehicle localization, but also has the advantage of strong anti-noise. We also introduce unscented Kalman filter (UKF) to further improve the localization accuracy of the TLS-ESPRIT algorithm and to reduce the influence of noise interference. The simulation results show that compared with the traditional 2D-ESPRIT parameter estimation methods without UKF and the Global Positioning System (GPS), this method has better performance of positioning parameter estimation.
Year
DOI
Venue
2019
10.1007/978-3-030-19156-6_28
WIRELESS AND SATELLITE SYSTEMS, PT II
Keywords
DocType
Volume
Vehicle location, TLS-ESPRIT, Direction of arrival (DOA), Arrival time (TOA), Kalman filter
Conference
281
ISSN
Citations 
PageRank 
1867-8211
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Shanjie Zhang100.34
Y. Shi22211.24
Rui Zhang3103.30
Feng Yan47313.36
Yi Wu501.01
Weiwei Xia621.04
Lianfeng Shen751765.25