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Robust Filtering Algorithm for Uncertain Systems with Observation Losses in Sensor Network

机译:传感器网络中具有观测损失的不确定系统的鲁棒滤波算法

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摘要

In this paper, robust minimum variance filtering problem is considered for discrete time-varying systems with observation losses. The system is subjected to time-varying norm-bounded parameter uncertainties in both the state and output matrices, and the observation losses are described by a Bernoulli process with a known probability. Based on an upper bound on the variance of the state estimation error, a robust filter is derived by minimizing the prescribed upper bound in the sense of the matrix norm. Eventually, an algorithm suitable for online computation is summarized and a simulation example is presented to demonstrate the effectiveness of the proposed algorithms.
机译:在本文中,考虑具有观测损失的离散时变系统的鲁棒最小方差滤波问题。该系统在状态矩阵和输出矩阵中都受到时变范数界参数的不确定性,并且观测损失通过伯努利过程以已知概率描述。基于状态估计误差的方差的上限,从矩阵范数的意义上说,通过最小化规定的上限来得出鲁棒滤波器。最后,总结了适用于在线计算的算法,并给出了仿真示例,以证明所提算法的有效性。

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