Adaptive and Reconfigurable Data Fusion Architectures in Vehicle Positioning Navigation Systems

In positioning navigation systems, at any time, any of the sensors can break down or stop sending information, temporarily or permanently. To ensure a practical solution for use in guidance and navigation systems, faulty sensors must be detected and isolated such that their erroneous data will not corrupt the global position estimates. It is well known that Kalman filter is usually being used for data fusion applications. An interesting novel alternative is to use it for fault detection architecture as well. This paper describes the research conducted to evaluate the potential of combining fault detection and data fusion into a single architecture to make a robust positioning navigation system.