State estimation for discrete linear systems with observation time-delayed noise
Peng Cui Hongguo Zhao Jun-e Feng
Journal of Industrial & Management Optimization 2011, 7(1): 79-85 doi: 10.3934/jimo.2011.7.79
State estimation problem is discussed for discrete-time systems with delays in measurement noise sequence, which is usually seen in network control and geophysical prospecting systems. An optimal recursive filter is derived via state augmentation. Dimensions of the optimal filter just are the sum of dimensions of state and observation vector. Therefore, they are not related to the size of delay. Besides, a sub-optimal recursive filter with same dimension as the original state is designed. The sub-optimal filter realizes instant optimization at current time. One example shows the effectiveness of the proposed approach.
keywords: Kalman filtering. optimal estimation sub-optimal estimation Time-delayed noise

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