期刊
IEEE SIGNAL PROCESSING LETTERS
卷 23, 期 12, 页码 1848-1852出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2016.2627001
关键词
Finite-impulse response (FIR) filter; kalman filter (KF); maximum likelihood (ML); state space; time-variant model
资金
- National Natural Science Foundation of China [61603155]
- 111 project [B12018]
In this letter, the maximum likelihood (ML) finite-impulse response (FIR) filter is proposed for discrete time-variant state-space models with nonsingular system matrix. The ML FIR filter has the deadbeat property and its form is universal for all known bias constrained FIR filters. By the identity weighting matrix, the ML FIR filter becomes the unbiased FIR filter, which ignores the noise statistics and the initial error statistics. Otherwise, the ML FIR filter is equivalent to the optimal FIR filter with embedded unbiasedness and to the minimum variance unbiased FIR filter. An example of a stochastic resonator demonstrates higher immunity of the ML FIR filter against errors in the imprecisely defined noise statistics than in the kalman filter.
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