论文标题

被动定位的几何方法

A Geometric Approach to Passive Localisation

论文作者

Triommatis, Theofilos, Potapov, Igor, Rees, Gareth, Ralph, Jason F.

论文摘要

在本文中,我们提出了一个用于静态发射器的被动定位的几何框架。目的是通过集中的移动被动传感器协调将发射器的位置定位在给定区域。该框架仅使用问题的几何形状来最大程度地减少发射器位置的最大边界,而无需使用信念或概率分布。这种几何方法在发射器的位置上提供了有效的边界。它也可以在评估不同的决策策略来协调移动被动传感器和在初始化过程中补充统计方法的不同决策策略。通过设计和评估贪婪的决策策略来显示几何方法的有效性,其中传感器通过使用全球目标函数之一将其下一个测量的最大不确定性最小化,从而选择其未来位置。最后,我们分析并讨论了所提出算法的新兴行为和鲁棒性。

In this paper, we present a geometric framework for the passive localisation of static emitters. The objective is to localise the position of the emitters in a given area by centralised coordination of mobile passive sensors. This framework uses only the geometry of the problem to minimise the maximal bounds of the emitters' locations without using a belief or probability distribution. This geometric approach provides effective boundaries on the emitters' position. It can also be useful in evaluating different decision-making strategies for coordinating mobile passive sensors and complementing statistical methods during the initialisation process. The effectiveness of the geometric approach is shown by designing and evaluating a greedy decision-making strategy, where a sensor selects its future position by minimising the maximum uncertainty on its next measurement using one of the global objective functions. Finally, we analyse and discuss the emergent behaviour and robustness of the proposed algorithms.

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