A moving fixed-interval filter/smoother for estimation of vehicle position using odometer and map-matched GPS

摘要

This paper presents some optimal real-time and post-processing estimators ofvehicle position using odometer and map-matched GPS measurements. Theseestimators were based on a simple statistical error model of the odometer andthe GPS which makes the model generalizable to other applications. Firstly, anasymptotically minimum variance unbiased estimator and two optimal moving fixedinterval filters which are more flexibles are exposed. Then, thepost-processing case leads to the construction of two moving fixed intervalsmoothers. These estimators are tested and compared with the classical Kalmanfilter with simulated and real data, and the results show a good accuracy ofeach of them.