Joint Vehicle Tracking and RSU Selection for V2I Communications with Extended Kalman Filter
- Authors
- Song, Jiho; Hyun, Seong-Hwan; Lee, Jong-Ho; Choi, Jeongsik; Kim, Seong-Cheol
- Issue Date
- May-2022
- Publisher
- Institute of Electrical and Electronics Engineers
- Keywords
- extended Kalman filter; Joint vehicle tracking; millimeter wave V2I communications; road side unit selection
- Citation
- IEEE Transactions on Vehicular Technology, v.71, no.5, pp 5609 - 5614
- Pages
- 6
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE Transactions on Vehicular Technology
- Volume
- 71
- Number
- 5
- Start Page
- 5609
- End Page
- 5614
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/112869
- DOI
- 10.1109/TVT.2022.3153345
- ISSN
- 0018-9545
1939-9359
- Abstract
- We develop joint vehicle tracking and road side unit (RSU) selection algorithms suitable for vehicle-to-infrastructure (V2I) communications. We first design an analytical framework for evaluating vehicle tracking systems based on the extended Kalman filter. A simple, yet effective, metric that quantifies the vehicle tracking performance is derived in terms of the angular derivative of a dominant spatial frequency. Second, an RSU selection algorithm is proposed to select a proper RSU that enhances the vehicle tracking performance. A joint vehicle tracking algorithm is also developed to maximize the tracking performance by considering sounding samples at multiple RSUs while minimizing the amount of sample exchange. The numerical results verify that the proposed vehicle tracking algorithms give better performance than conventional signal-to-noise ratio-based tracking systems. © 1967-2012 IEEE.
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