Network Centric Fusion Approaches for Command and Control Platforms with Multiple Unmanned Aerial Vehicles

ABSTRACT: The coordination and management of sensor data collection has a strong influence on the accuracy and completeness of the fused situational awareness picture. To provide the best possible picture, Toyon Research proposes to develop algorithms which generate controls for a collection of UAVs in order to maximize the probability of identifying and maintaining track on suspected enemy vehicles or dismounts. Algorithm inputs will include environmental data (terrain, roads, buildings), sensor, platform, and target motion models, and the current network centric fused estimate of the surveillance region. We will develop our control algorithms to address a number of real-world issues (e.g., limits on communication links, UAV fuel limits, communication and processing delays) as well as incorporate environmental information (traffic densities, obscuration, etc.) and operational priorities into the routing algorithm"s objective function. Our sensor systems will include one standoff platform with radar, UGS distributed throughout the surveillance region, and multiple UAVs with video sensors. We will consider a decentralized architecture in which multiple operation centers are distributed throughout the region, each maintaining control of multiple UAVs but sharing track information to promote collaboration. The algorithms will be tested and evaluated within a simulated environment as well as in hardware-in-the-loop experiments. BENEFIT: Automatic route and task generation for sensor assets has immediate application to network centric warfare. In addition, the algorithm technology can seamlessly transition into our Geospatial Analysis and Planning Support (GAPS) Toolbox application, which is sponsored by JFCOM Joint Urban Operation Office. In addition to military systems, the technology developed during this project will serve as a foundation for planning tools for manned and unmanned systems, providing, for example, emergency response plans for natural disasters or biological, chemical, or nuclear attacks.