Adaptive Kalman Filtering based on Matched Filtering of the Innovations Sequence
نویسندگان
چکیده
An adaptive tracking filter for maneuvering targets is developed. The approach is based on matched filtering of the innovations sequence. Analytical solutions based on the invariant subspace method for time-invariant kinematic models along with the corresponding steady-state Kalman filter kernels are derived. Asymptotic and finite-memory operating characteristics are deduced. The proposed adaptive tracking filter is compared to the interacting multiple model filter based on simulation results.
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