分布式跟踪中主动传感器的选择算法:飞盘与GNS方法的比较

A. Capponi, C. Pilotto, G. Golino, A. Farina, Lance M. Kaplan
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引用次数: 12

摘要

本文比较了两种不同的分布式跟踪传感器选择方法:飞盘法和全局节点选择(GNS)。飞盘方法基于节点与目标预测位置的接近度;GNS基于最小化无偏Cramer - Rao下界(CRLB)。理论和实验结果都表明,飞盘法与GNS法一样有效。此外,飞盘方法由于其非常轻的计算负荷而具有吸引力
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithms for the selection of the active sensors in distributed tracking: comparison between Frisbee and GNS methods
This paper compares two different approaches for sensor selection for distributed tracking: 1) the Frisbee method, and 2) global node selection (GNS). The Frisbee method is based on the proximity of the nodes to the predicted location of the target; GNS is based on minimizing the unbiased Cramer Rao lower bound (CRLB). Both theoretical and experimental results indicate that the Frisbee method is as effective as GNS. Furthermore, the Frisbee method is attractive due to its very light computational load
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