Projection-based circular constrained state estimation and fusion over long-haul links

Qiang Liu, N. Rao
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引用次数: 4

Abstract

In this paper, we consider a scenario where sensors are deployed over a large geographical area for tracking a target with circular nonlinear constraints on its motion dynamics. The sensor state estimates are sent over long-haul networks to a remote fusion center for fusion. We are interested in different ways to incorporate the constraints into the estimation and fusion process in the presence of communication loss. In particular, we consider closed-form projection-based solutions, including rules for fusing the estimates and for incorporating the constraints, which jointly can guarantee timely fusion often required in realtime systems. We test the performance of these methods in the long-haul tracking environment using a simple example.
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基于投影的环约束状态估计与长途链路融合
在本文中,我们考虑了一种场景,传感器部署在一个大的地理区域,以跟踪一个具有圆形非线性约束的目标运动动力学。传感器状态估计值通过长途网络发送到远程融合中心进行融合。我们感兴趣的是在存在通信损失的情况下将约束纳入估计和融合过程的不同方法。特别地,我们考虑了封闭形式的基于投影的解决方案,包括用于融合估计和合并约束的规则,它们共同可以保证实时系统中经常需要的及时融合。我们用一个简单的例子测试了这些方法在长途跟踪环境中的性能。
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