抄録
Most algorithms currently proposed for Sensor Fusion assume that the data from multiple variant sensors are coherent (synchronus and without time delay of measurement). In this paper, we propose a new Sensor Fusion algorithm which fuses incoherent multi-sensor data according to the fixed sequence of time-variant combinations of sensors. This algorithm is proved by the existence of equivalent Kalman filter, which corresponds to this sequence. observability and controllability of equivalent Kalman filter assure the steady state solution of unique estimation error covarince matrix. We also propose a new method of evaluating Sensor Fusion system by mutual information rate.
