Navigation in Radio Frequency Landscapes Using Autonomous Vehicles and Multiple Antenna Systems

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Autonomous, or self-driving, vehicles have been making headlines in recent years as new technologies develop. While they are increasingly used for human transportation, it frequently remains important for autonomous rovers to maximize connectivity as they move. There have been recent developments in antenna technologies, called reconfigurable antennas, which allow reconfiguration of the radiation pattern through electromagnetic, rather than physical, means. This project focuses on engineering a control strategy which decides how to use omnidirectional, directional, and reconfigurable antenna systems while navigating an autonomous rover. We start with a path-planning algorithm optimizing signal strength by selecting the best path, then expand the algorithm to evaluate possible antenna configurations and choose when to use the appropriate configuration while traversing the optimal path. After running a series of tests using a number of metrics to make decisions in the control strategy, a control strategy has been developed with multiple optimization functions which would apply best to differing scenarios.

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RF navigation, antenna system, path-planning algorithm, Dijkstra, Wireless InSite, autonomous vehicle, autonomous rover, reconfigurable antenna, automation, graph theory, received signal strength, omnidirectional antenna, directional antenna, navigation algorithm, k shortest paths, path planning, Dijkstra's Algorithm, Friis Transmission Equation, horn antenna, heat map, k shortest paths algorithm, SNR, Shannon Capacity Formula, bandwidth, link capacity, navigation algorithm, autonomous navigation

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