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Use of Artificial Potential Fields for UAV Guidance and Optimization of WLAN Communications

机译：人工势场在无人机制导和WLaN通信优化中的应用

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Wireless Local Area Networks (WLAN) are quickly becoming an important part of regional military operations. The use of standardized internet protocols enables a wide variety of vehicles, sensors and personnel to interoperate more effectively. For Autonomous Underwater Vehicles (AUV), they permit a potentially great improvement to distribute outputs from data intensive sensors like sonar and video to observers. For a fleet of AUVs tasked with area underwater search and survey, WLANs can facilitate situational awareness, retasking and expedience. Because of the limited range of the 802.11b 2.4GHz channels, one of the keys to realizing WLAN communications between multiple AUVs and Tactical Operations Centers is the positioning of aerial bridges. Unmanned Aerial Vehicles (UAVs) can be used as the platform and moreover sensory based autopilot navigation can be developed to optimize the throughput rate for multilink data transfers. Artificial Potential Function (APF) methods can be used for guidance law development, once antenna and signal strength models become available. This paper will discuss the results from the recent Naval Postgraduate School (NPS) Surveillance Targeting and Acquisition Network (STAN) experiment conducted at Camp Roberts, CA and follow-on Office of Naval Research (ONR) sponsored Joint Training Fleet Exercise (JTFEX) experiments at Camp Lejuene, NC. Vehicles used in the experiments include the NPS ARIES AUV and Tactically Expendable Remote Navigator (TERN) UAV.

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