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Fusion performance in long-haul sensor networks with message retransmission and retrodiction

机译:长途传感器网络中的融合性能,具有消息重传和造版

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In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks. We consider a class of such networks where sensors take measurements of one or more dynamic targets and send state estimates of the target(s) to a fusion center via satellite links. The severe loss and delay inherent over the satellite channels render insufficient the number of estimates successfully arriving at the fusion center, thereby limiting the potential fusion gain and resulting in suboptimal accuracy performance of the fused estimates. The system can adopt certain retransmission-based transport protocols so that lost messages can be recovered over time. However, excess delay may be incurred that can potentially violate the deadline for reporting the estimate. For many applications, though, retrodiction/smoothing techniques can be applied so that the chances of incurring such excess delay are greatly reduced. In this work, we analyze the extent to which retrodiction, along with message retransmission, can improve the performance of delay-sensitive state estimation tasks. Results of numerical and simulation studies of an illustrative example and a ballistic target tracking application are shown in the end to demonstrate the validity of our analysis.
机译:在长途传感器网络中,传感器在大型地理区域上远程部署,以执行某些任务。我们考虑一类这样的网络,其中传感器通过卫星链接将一个或多个动态目标进行测量,并将目标的状态估计发送到融合中心。卫星通道上固有的严重损失和延迟呈现成功到达融合中心的估计数量,从而限制了潜在的融合增益并导致融合估计的次优的精度性能。系统可以采用某些基于重传的传输协议,以便随着时间的推移可以恢复丢失的消息。然而,可能会产生过度的延迟,这可能可能违反报告估计的截止日期。然而,对于许多应用,可以应用销制/平滑技术,使得产生这种过度延迟的机会大大降低。在这项工作中,我们分析了传销范围以及消息重传的程度,可以提高延迟敏感状态估计任务的性能。终点显示了说明性示例的数值和模拟研究结果和弹道目标跟踪应用,以证明我们分析的有效性。

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