Cooperative Aerial Search by an Innovative Optimized Map Sharing Algorithm

Samin Karimi, F. Saghafi
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Abstract

In this paper, the problem of cooperative search and tracking by multiple flying vehicles is studied. An algorithm is proposed based on an optimal planning by minimizing a suitably defined cost function. In order to define the cost function, three maps are proposed: uncertainty map, detection probability map, and emitter map. In the uncertainty map, the geometrical status of the vehicle with respect to the region is considered and its suitability is measured. The detection probability map is defined such that the group of vehicles can detect new emitters that appear in their sensors’ coverage. Finally, the emitter map is a tool to keep tracking the detected emitters with acceptable error, while searching the region. The assumption of the vehicles being equipped with only one commonly used radar range indicator sensor, makes the proposed algorithms more applicable in the real world for a cost effective system. The efficiency of the proposed method from the search, detection and tracking points of view is verified through simulations.
通过创新的优化地图共享算法进行合作式空中搜索
本文研究了多飞行器合作搜索和跟踪问题。通过最小化适当定义的成本函数,提出了一种基于最优规划的算法。为了确定成本函数,提出了三个地图:不确定性地图、探测概率地图和发射器地图。在不确定地图中,考虑了车辆相对于区域的几何状态,并测量了其适用性。探测概率图的定义是,车辆群能够探测到其传感器覆盖范围内出现的新发射器。最后,发射器地图是在搜索区域时以可接受的误差跟踪已探测到的发射器的工具。假设车辆只配备一个常用的雷达测距仪传感器,这就使得所提出的算法更适用于现实世界中的高性价比系统。通过模拟验证了所提方法在搜索、探测和跟踪方面的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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