Map-assisted Kalman filtering

Abstract

We describe a method for incorporating map information to the Kalman filter that is commonly used in indoor and outdoor navigation systems. The map information is provided as a measurement to the Kalman filter to ensure the consistency of the Kalman estimate. The proposed method provides huge computational saving over common map matching algorithms that use the more computationally expensive particle filter. We show indoor navigation examples that highlight the efficiency of the proposed algorithm.