A state decoupling approach to estimate unobservable trackingsystems |
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| Authors: | Pan-Tai Liu Fu Li Heng Xiao |
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| Institution: | Dept. of Math., Rhode Island Univ., Kingston, RI ; |
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| Abstract: | If a system is unobservable, the error covariance associated with a Kalman filter will be nearly singular. As a consequence, an optimum estimation in the sense of minimum error covariance does not exist. In this paper, we show that this (unobservable) system can be transformed into a nonlinear system with a linear measurement equation. In addition to other useful features, this transformation also serves to decouple the state in such a way that an observable part can be extracted and estimated while no information can be gained and processed for the unobservable part |
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