Framework Design and Simulation of VANET Vehicle Positioning using Two Stage Sigma Point Kalman Filter (TSSPKF)

Abstract

Improved GPS/INS/RFID integration method based on loosely coupled integrated federated approach (LCIFA) of variants of sigma point Kalman filter is proposed for vehicle localization application. It is applied to improve vehicle localization accuracy ubiquitously. This integrated localization method is useful in both indoor and outdoor environments comprises of different scenarios: Open area, dense area and tunnel area where GPS works in Open environment (GPS signal is available);GPS/INS works in dense/Semi-dense environment (GPS availability is short) and GPS/RFID works in Tunnel like area (No GPS available). GPS or GPS/INS system is used in outdoor environment and only Active RFID tags are hired (instead of complete RFID system) in case of indoor environment like Tunnel. A novel RFID tag placement strategy is introduced as placing active RFID tags at divider which gives very accurate localization with low cost investment and also passive RFID tags on the road side units i.e. sign posts. In this paper, the modeling of the LCIFA using sigma point Kalman filter based on position model only and TDNN is designed and simulated which provides better results as compared to real time evaluation. This is one of the novel sturdy approaches to vehicle communication.