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Sequential filtering for state constrained systems with cross-correlated measurement noises

机译:具有相互关联的测量噪声的状态约束系统的顺序滤波

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This paper deals with the data fusion problem for the state constrained systems with correlated measurement noises.The purpose is to present a new optimal sequential decentralized filtering algorithm.Using the constraint information,the original state equation is transferred into a dimension reduction system without constraint,and new measurement outputs with independent noises is obtained based on the successive orthogonalization of the original cross-correlated noises.Then the sequential filter of the dimension reduction state is presented and the estimate of the full state is also reconstructed.A numerical example is presented to demonstrate the effectiveness of the method.
机译:本文针对具有相关测量噪声的状态约束系统的数据融合问题进行研究。目的是提出一种新的最优顺序分散滤波算法。利用约束信息,将原始状态方程转化为无约束的降维系统,在原始互相关噪声连续正交的基础上,获得了具有独立噪声的新测量输出,然后提出了降维状态的顺序滤波器,并重构了全状态的估计,给出了一个数值例子。证明该方法的有效性。

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