Analysis on the Kalman Filter Performance in GPS/INS Integration at Different Noise Levels, Sampling Periods and Curvatures

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Executive Summary

Kalman Filters (KF) has been extensively used in the integration of Global Positioning System (GPS) and Inertial Navigation System (INS) data. Often, the GPS data is used as a benchmark to update the INS data. In this paper, an analysis of integration of GPS data with INS data using an Extended Kalman filter is performed in terms of the filter's performance with respect to the amount of noise in the GPS data and the sampling time of the vehicle position. The paper further analyzes and compares the pattern of error at varying sampling periods in vehicle trajectories with high curvature path segments and low curvature path segments. Simulation results are presented at the end.

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