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Robust recursive filter for multi-sensor nonlinear stochastic system with random uncertainties and missing measurements

机译:具有随机不确定性和缺失测量的多传感器非线性随机系统的鲁棒递归滤波器

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This paper is concerned with the robust recursive filtering problem for multi-sensor nonlinear stochastic system with random uncertainties and missing measurements. The phenomenon of random uncertainties or multiplicative noises is included in the system model, measurement model and the filter parameters. The missing measurements of multi-sensor are assumed to be independent of each other with different sensor failure rates. Then, a robust recursive filter is designed in the minimum-variance sense at each sampling instant against the random uncertainties and missing measurements. A simulation example is employed to demonstrate the effectiveness of the proposed method.
机译:本文涉及具有随机不确定性和缺失测量的多传感器非线性随机系统的鲁棒递归滤波问题。系统模型,测量模型和滤波器参数中包含随机不确定性或乘性噪声现象。假定多传感器丢失的测量值彼此独立,并且具有不同的传感器故障率。然后,针对每个随机不确定性和丢失的测量,在每个采样时刻以最小方差的意义设计一个鲁棒的递归滤波器。仿真实例证明了所提方法的有效性。

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