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Robust transcale state estimation for multiresolution discrete-time systems based on wavelet transform

机译:基于小波变换的多分辨率离散时间系统鲁棒跨尺度状态估计

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In this study, an effective robust transcale estimation algorithm is proposed for discrete-time systems, which are observed by a single sensor at the finest resolution or by two sensors at the finest and coarsest resolutions. The discrete-time state-space models of approximation and detail coefficients at each resolution are established by using Haar wavelet decomposition, respectively. The algorithm is developed based on the standard H∞ filtering scheme, and hence preserves the merits of the H∞ filter for random signal estimation in the sense that it minimises the effect of the worst possible disturbances on the estimation errors. The proposed algorithm is demonstrated through Monte Carlo simulations involving tracking of a target in CV model.
机译:在这项研究中,为离散时间系统提出了一种有效的鲁棒跨尺度估计算法,该算法可以由单个传感器以最高分辨率观察,或者由两个传感器以最高分辨率和最粗糙分辨率观察。利用Haar小波分解分别建立了每种分辨率下的近似时间和细节系数的离散时间状态空间模型。该算法是基于标准H∞滤波方案开发的,因此保留了H∞滤波器用于随机信号估计的优点,因为它可以最大程度地减少最严重的干扰对估计误差的影响。通过蒙特卡洛仿真演示了该算法,该仿真涉及在CV模型中跟踪目标。

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