New State Estimation Mechanisms for Systems with Random Biases using Recent Finite Measurements
نویسنده
چکیده
The two state estimation mechanisms are investigated for the system with a randomly varying bias using only most recent finite measurements. One is the augmented filtering mechanism using the treatment of the bias as part of the system state. The other is the two-stage filtering mechanism using the linear combination of the outputs of a bias-free filter and a bias filter. It is shown that proposed mechanisms has inherent good properties such as time-invariance, deadbeat property, and unbiasedness.
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