论文标题
在基于RSS的被动定位中对无人机群的最佳测量和区域约束
Optimal Measurement of Drone Swarm in RSS-based Passive Localization with Region Constraints
论文作者
论文摘要
由多个无人机（UAV）进行的被动地理位置涵盖了各种军事和平民应用，包括救援，野生生命追踪和电子战。已知传感器目标几何形状会显着影响定位精度。现有的传感器放置策略主要在传感器位置没有任何约束的情况下进行。但是，由于现实的限制，例如地理限制，安全问题和最大飞行速度，无人机不能仅仅在任意区域中飞行/悬停。在本文中，研究了无人机在接收信号强度（RSS）基于区域约束下的定位中的最佳几何结构。采用D-最佳标准，即最大程度地减少Fisher信息矩阵（FIM）的确定，该最佳问题被提出。基于严格的代数和几何派生，提出了在不同飞行状态下无人机的最佳和封闭形式的配置。最后，通过模拟示例证明了所提出的配置的有效性和实用性。
Passive geolocation by multiple unmanned aerial vehicles (UAVs) covers a wide range of military and civilian applications including rescue, wild life tracking and electronic warfare. The sensor-target geometry is known to significantly affect the localization precision. The existing sensor placement strategies mainly work on the cases without any constraints on the sensors locations. However, UAVs cannot fly/hover simply in arbitrary region due to realistic constraints, such as the geographical limitations, the security issues, and the max flying speed. In this paper, optimal geometrical configurations of UAVs in received signal strength (RSS)-based localization under region constraints are investigated. Employing the D-optimal criteria, i.e., minimizing the determinate of Fisher information matrix (FIM), such optimal problem is formulated. Based on the rigorous algebra and geometrical derivations, optimal and also closed form configurations of UAVs under different flying states are proposed. Finally, the effectiveness and practicality of the proposed configurations are demonstrated by simulation examples.
