最优降阶滤波

L. Hong
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引用次数: 4

摘要

针对测量向量的维数小于状态向量的维数且没有测量值是无噪声的情况,提出了一种最优降阶滤波器,可以提供状态估计的全向量。降阶滤波器由一个观测器类型子滤波器和一个互补子滤波器组成,每个子滤波器提供最优估计的一个子集。采用两步L-K变换最小化每个子滤波器的估计误差协方差。以目标跟踪问题为例进行了研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal reduced-order filtering
An optimal reduced-order filter is developed which can provide a full vector of state estimates for the case where the dimension of the measurement vector is smaller than that of the state vector and no measurements are noise-free. The reduced-order filter consists of an observer type subfilter and a complementary subfilter, each of which provides a subset of the optimal estimate. A two-step L-K transformation is employed to minimize the estimate error covariance of each subfilter. A target tracking problem is studied as an example.<>
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