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Simultaneous system identification and decision-directed detection and estimation of jump inputs to linear systems

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1 Author(s)
Stirling, W.C. ; Brigham Young University, Provo, UT, USA

A decision-directed approach is presented for analyzing linear systems with unknown jump inputs. The system model parameters are estimated using a Kalman filter, and an empirical Bayes detection procedure is introduced to set the detector parameters, resulting in a decision-directed generalized likelihood ratio test coupled with recursive system parameter estimation. Monte Carlo results are presented to validate the performance of the algorithm.

Published in:

Automatic Control, IEEE Transactions on  (Volume:32 ,  Issue: 1 )