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.
翻译:在本文中,我们提出了一个静态发射者被动定位的几何框架。目标是通过移动被动感应器的集中协调,使发射者在特定区域的位置本地化。这个框架仅使用问题的几何结构,在不使用信念或概率分布的情况下,最大限度地缩小发射者所在地的最大界限。这种几何方法为发射者的位置提供了有效的界限。它也可以用于评估协调移动被动感应器的不同决策战略,并在初始化过程中补充统计方法。几何方法的有效性表现在设计和评估贪婪的决策战略,其中传感器选择其未来位置,办法是使用全球目标函数之一,尽量减少下一次测量的最大不确定性。最后,我们分析和讨论拟议的算法的新兴行为和稳健性。