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Distributed Fusion Estimation With Communication Bandwidth Constraints

机译:具有通信带宽约束的分布式融合估计

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摘要

This technical note is concerned with the distributed Kalman filtering problem for a class of networked multi-sensor fusion systems (NMFSs) with communication bandwidth constraints. To satisfy finite communication bandwidth, only partial components of the local vector estimation signals are transmitted to the fusion center (FC) at each time step, where multiple binary variables are introduced to model this component transmitting process. A novel compensation strategy is proposed to restructure the untransmitted components of each local estimate at the FC end, and a recursive distributed fusion kalman filter (DFKF) is designed in the linear minimum variance sense. Moreover, a simple suboptimal judgement criterion is proposed to determine a group of binary variables such that the mean square error of the designed DFKF is minimal at each time step. An illustrative example is given to show the effectiveness of the proposed methods.
机译:本技术说明涉及一类具有通信带宽约束的网络化多传感器融合系统(NMFS)的分布式卡尔曼滤波问题。为了满足有限的通信带宽,在每个时间步长仅将局部矢量估计信号的部分分量发送到融合中心(FC),在此引入多个二进制变量以对该分量发送过程进行建模。提出了一种新颖的补偿策略来重构FC端的每个局部估计的未传输分量,并在线性最小方差意义上设计了递归分布融合卡尔曼滤波器(DFKF)。此外,提出了一种简单的次优判断标准来确定一组二进制变量,以使设计的DFKF的均方误差在每个时间步均最小。给出了一个说明性的例子来说明所提出方法的有效性。

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