Modeling and estimation of a class of multi-rate sensor dynamic systems

The state estimation problem of a kind of time-vary linear dynamic system with the multi-rate multi-sensor data fusion was studied. Firstly, a multi-rate system modeling algorithm was presented in times of multiple sensors observing the same target with different sampling rates. So the multiple sampling rate system could be transformed to the same sampling rate system, and the fusion of multi-rate multi -sensor state estimation problem was simplified. Online estimation of the target state was done with the Kalman filter. By use of the distributed fusion structure with feedback, the estimations were fused and the optimal state estimation was generated. The augmentation of state or measurement dimensions were avoided in this presented algorithm, and the real-time property of the algorithm was guaranteed. A kind of integrated navigation systems including GPS, INS and scene matching was simulated with the different two sampling rates separately. The results show that the presented algorithm is effective.