Abstract
In this paper, we consider the problem of vehicular positioning enhancement with emerging connected vehicles (CV) technologies. In order to actually describe the scenario, the Interacting Multiple Model (IMM) filter is used for depicting varies of observation models. A CV-enhanced IMM filtering approach is proposed to locate a vehicle by data fusion from both coarse GPS data and the Doppler frequency shifts (DFS) measured from dedicated short-range communications (DSRC) radio signals. Simulation results state the effectiveness of the proposed approach called CV-IMM-EKF.
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CITATION STYLE
Tian, D., Liu, W., Duan, X., Rong, H., Guo, P., Wang, W., & Zhang, H. (2018). A Vehicular Positioning Enhancement with Connected Vehicle Assistance Using Extended Kalman Filtering. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 211, pp. 597–608). Springer Verlag. https://doi.org/10.1007/978-3-319-72823-0_55
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