Positioning, Navigation, and Timing on the Air
Positioning, Navigation, and Timing on the Air
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DOI：
10.1109/dcoss-iot58021.2023.00105
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发表时间：
2023-06
期刊：
影响因子：
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通讯作者：
Md. Sadman Siraj;Aisha B. Rahman;P. Charatsaris;E. Tsiropoulou;S. Papavassiliou
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文献类型：
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作者：
Md. Sadman Siraj;Aisha B. Rahman;P. Charatsaris;E. Tsiropoulou;S. Papavassiliou
定位、导航和授时（PNT）服务在现代社会的许多应用中被广泛采用，导致了各种替代PNT系统的发展，旨在解决全球定位系统（GPS）的脆弱性。在本文中，我们引入了一种基于协作的PNT解决方案，通过共同利用无人机辅助无线网络，以及网络中目标和协作节点之间的协作，他们分别对其位置和时间有未知和粗略的估计。基于势博弈原理，提出并求解了整个系统和各协作节点以及目标位置和时间估计误差的最小化问题。证明了相应博弈纳什均衡的存在性，研究了获取博弈纳什均衡的两种不同方法，并对其权衡进行了评估。第一种方法遵循博弈论方法，第二种方法基于强化学习原理。通过建模和仿真，进行了详细的数值评估，以证明所提出的PNT解决方案的优点和权衡。
The widespread adoption of Positioning, Navigation, and Timing (PNT) services in many applications across modern society, has given rise to the development of various alternative PNT systems, aiming at addressing the Global Positioning System (GPS) vulnerabilities. In this paper, we introduce a collaborative-based PNT solution by jointly exploiting the use of UAV-assisted wireless networks and the collaboration among the targets and the collaborator nodes in the network, who have unknown and a rough estimate of their position and timing, respectively. The minimization problem of the overall system's and each collaborator node's and target's position and timing estimation error is formulated and solved based on the principles of potential games. The existence of a Nash Equilibrium (NE) of the corresponding game is proven, while two different approaches to obtain the game's NE are studied and their tradeoffs are evaluated. The first one follows a game-theoretic approach and the second one is based on the principles of reinforcement learning. A detailed numerical evaluation is performed, via modeling and simulation, in order to demonstrate the benefits and tradeoffs of the proposed PNT solution.