Nonlinear Filtering Methods for the INS/GPS In-Motion Alignment and Navigation

Abstract

In this paper we present the algorithms of land-vehicle INS (Inertial Navigation System) / DGPS (Differential Global Positioning System) In-Motion Alignment based on nonlinear filtering techniques (Quasi-Linear Optimal filter [1], Gaussian Sum filter [2], the Extended Kalman filter [3] and Monte Carlo filter [4]). We also show results of comparative numerical experiments, and evaluate the nonlinear filtering performances under various error sources such as the errors of GPS, accelerometers and gyros.