Unified Maximum Likelihood Form for Bias Constrained FIR Filters

Unified Maximum Likelihood Form for Bias Constrained FIR Filters
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偏置约束 FIR 滤波器的统一最大似然形式

DOI:
10.1109/lsp.2016.2627001
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发表时间:
2016-11
影响因子:
3.9
通讯作者:
Shmaliy Yuriy S
Shmaliy Yuriy S
中科院分区:
工程技术2区
文献类型:
--
作者:
Zhao Shunyi;Shmaliy Yuriy S

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针对具有非奇异系统矩阵的离散时变状态空间模型,提出了极大似然(ML)有限脉冲响应(FIR)滤波器。ML FIR滤波器具有无差拍特性,其形式对所有已知的偏置约束FIR滤波器都是通用的。通过恒等式加权矩阵,ML FIR滤波器变成了忽略噪声统计量和初始误差统计量的无偏FIR滤波器。否则,ML FIR滤波器等价于嵌入无偏的最优FIR滤波器,等价于最小方差无偏FIR滤波器。随机谐振器的一个例子表明,ML FIR滤波器对不精确定义的噪声统计中的错误具有比卡尔曼滤波器更高的免疫力。
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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