Vehicle Fusion Positioning Model based on CSI

High precision positioning in non-open area has always been a bottleneck in the development of V2X. In order to ensure the positioning performance of V2X in non-open area, this paper proposes a vehicle fusion localization method based on Channel State Information (CSI). In the proposed method, a positioning framework for on-board unit (OBU) and road-side unit (RSU) is established based on the communication characteristics of V2X. Meanwhile, the algorithms for the operation of OBU and RSU are given respectively. On this basis, the proposed method uses CSI to calculate the signal flight time, and combines with the least square method to locate the vehicle on the basis of communication equipment. To improve the reliability of CSI data analysis and solve the problem of CSI analysis under multipath propagation, the traditional optimization model is solved by a quadratic convex programming method based on algebraic optimization.

[1]  Abdulmotaleb El-Saddik,et al.  Toward Social Internet of Vehicles: Concept, Architecture, and Applications , 2015, IEEE Access.

[2]  Mario Gerla,et al.  Vehicular networks and the future of the mobile internet , 2011, Comput. Networks.

[3]  Jie Wang,et al.  An Intersection Collision Warning System Using Wi-Fi Smartphones in VANET , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[4]  Eylem Ekici,et al.  Vehicular Networking: A Survey and Tutorial on Requirements, Architectures, Challenges, Standards and Solutions , 2011, IEEE Communications Surveys & Tutorials.

[5]  KatabiDina,et al.  See through walls with WiFi , 2013 .

[6]  Raymond Knopp,et al.  A practical method for wireless channel reciprocity exploitation through relative calibration , 2005, Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005..

[7]  Fadel Adib,et al.  See through walls with WiFi! , 2013, SIGCOMM.

[8]  Yunhao Liu,et al.  Widar: Decimeter-Level Passive Tracking via Velocity Monitoring with Commodity Wi-Fi , 2017, MobiHoc.

[9]  Yunhao Liu,et al.  Widar2.0: Passive Human Tracking with a Single Wi-Fi Link , 2018, MobiSys.

[10]  Izhak Rubin,et al.  GPS aided inter-vehicular wireless networking , 2013, 2013 Information Theory and Applications Workshop (ITA).

[11]  Swarun Kumar,et al.  Decimeter-Level Localization with a Single WiFi Access Point , 2016, NSDI.

[12]  Yunhao Liu,et al.  Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi , 2019, MobiSys.

[13]  Robert D. Nowak,et al.  Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels , 2010, Proceedings of the IEEE.

[14]  Rob Miller,et al.  3D Tracking via Body Radio Reflections , 2014, NSDI.