Best Linear Unbiased Fir Filters for Continuous-time State Space Models
نویسندگان
چکیده
This paper proposes a new linear finite impulse response (FIR) filter called the best linear unbiased FIR (BLUF) filter for the state estimation in continuous-time state space models. The proposed BLUF filter for continuous-time state space models is obtained by a formal limiting procedure of discretized systems. The BLUF filter is represented in an iterative form and then in a standard FIR form. It is shown that the proposed BLUF filter has deadbeat and unbiasedness properties. It is also shown that the BLUF filter is equivalent to the existing receding horizon Kalman FIR (RHKF) filter whose optimality is not clear to understand. The former is more systematic and logical while the latter is heuristic due to handling of infinite covariance of the initial state.
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