A New FIR Filter for State Estimation and Its Application

This paper proposes a new FIR (finite impulse response) filter under a least squares criterion using a forgetting factor. The proposed FIR filter does not require information of the noise covariances as well as the initial state, and has some inherent properties such as time-invariance, unbiasedness...

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Bibliographic Details
Published in:Journal of computer science and technology 2007-09, Vol.22 (5), p.779-784
Main Authors: Kim, Pyung-Soo, Lee, Myung-Eui
Format: Article
Language:English
Subjects:
Computer simulation
Covariance
FIR filters
Impulse response
Kalman filtering
Kalman filters
Least squares method
Noise
State estimation
Studies
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Summary:This paper proposes a new FIR (finite impulse response) filter under a least squares criterion using a forgetting factor. The proposed FIR filter does not require information of the noise covariances as well as the initial state, and has some inherent properties such as time-invariance, unbiasedness and deadbeat. The proposed FIR filter is represented in a batch form and then a recursive form as an alternative form. From discussions about the choice of a forgetting factor and a window length, it is shown that they can be considered as useful parameters to make the estimation performance of the proposed FIR filter as good as possible. It is shown that the proposed FIR filter can outperform the existing FIR filter with incorrect noise covariances via computer simulations. Finally, as a useful application, an image sequence stabilization problem is considered. Through this application, the FIR filtering based approach is shown to be superior to the Kalman filtering based approach.
ISSN:1000-9000
1860-4749
DOI:10.1007/s11390-007-9085-8