Indoor location tracking using AGPS and Kalman filter

In this paper, the proposed system depends on the assist GPS (AGPS) idea in order to calculate the user position inside a building by using a roof-antenna (at known position) that has LOS with satellites. The antenna receives navigation data and sends it to the user using a wireless network. The distance between the user and the roof antenna is assumed less than 300 m. In this case, the time delay between them is approximately equal to 1 Clear/Acquisition (C/A) code chip period, and it is detected by using autocorrelation with error in cm. In the simulations, real data from a GPS receiver were used to track user moves inside building through a path with constant velocity. The performance of system under AWGN and effect of bias due to multipath and NLOS is improved using Extended Kalman filter (EKF). The results with EKF are compared with Nonlinear Least Square method (Nonlinear LS) at different processing time and noise level. EKF gives high improvement compared with Nonlinear LS. The overall system with EKF is simple to implement and generally, the error in user position small and acceptable for most indoor applications.