不同视场分布式传感器的广义协方差联合融合方法

Feng Ma, Huan-zhang Lu, Luping Zhang, Xinglin Sheng
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引用次数: 0

摘要

针对不同视场传感器的分布式融合问题,提出一种广义协方差联合(GCU)方法。利用视场(IoF)交点内的融合结果估计(目标定位)测量误差,然后利用该估计误差对IoF外的多目标密度进行校正。与现有方法相比,GCU方法对传感器相关的测量误差具有更强的鲁棒性。仿真实验验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The generalized covariance union fusion approach for distributed sensors with different fields of view
This paper proposes a generalized covariance union(GCU) approach to solve the distributed fusion problem of sensors with different fields of view (FoVs). It uses the fusion results within the intersection of the FoVs (IoF)to estimate the(target positioning) measurement error, and then employs this estimated error to correct the multitarget densities outside the IoF. Compared with the current approach, GCU approach is more robust to the sensor-related measurement error. Simulation experiments verified the effectiveness of the proposed approaches.
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