Non-linear filtering techniques for high precision GPS applications

Abstract

Nonlinear family of Kalman filters is employed to a nonlinear dynamic system for the purpose of state estimation. Extended, unscented and cubature Kalman filters are formulated and deployed to the nonlinear estimation of Global Positioning System(GPS) model. The state dynamics and measurement model of GPS is illustrated. Performance of extended, unscented and cubature Kalman filter is presented through simulation results. The results prove that the proposed use of CKF for GPS navigation outperforms other nonlinear filters. Computation complexity of each filter is also computed for comparison.