Fault detection and isolation in multisensor train navigation systems

In new automatic train control (ATC) and automatic train protection (ATP) systems, the onboard navigation system plays a vital role. Applying multisensor fusion algorithms in the vehicle navigation field has made it possible to make inexpensive and accurate positioning systems which will satisfy the requirements of railway systems. Kalman filtering, as one of the well known state estimation methods, has proved to be the most effective technique in multisensor data fusion for navigation applications. On the other hand reliability of the navigation system is of great concern which necessitates the design of a fault tolerant navigation system in which the detection and isolation of the faults is possible. The paper first addresses different multisensor integration methods and later discusses some of the fault detection methods for navigation systems using Kalman filtering and some simulation results are presented. Fault isolation using the proposed sensor architecture is another topic which is discussed in more detail.