The motivation of this research is to exploit three attributes of increased unmanned vehicle use for intelligence, surveillance, and reconnaissance missions. These attributes are increased numbers of unmanned vehicles, on-board vision, and wireless communications. The research begins with the development of a cooperative navigation system based on the measurement of vehicle position relative to shared landmark position estimates. Each vehicle in the network locates landmarks using it's on-board vision system and transmits the data to all other system vehicles. After receiving data from the other vehicles, the system fuses the landmarks with on-board measurements using a federated filter architecture. Simulations of the cooperative system, with and without ranging, are compared to a non-cooperative simulation. The comparison is performed using four platform motion scenarios: stationary, linear, angular, and full motion. The simulation results demonstrate position error estimate improvements of 0.5 cm to 1 cm. Additionally, the stationary and linear motion scenarios demonstrate attitude observability difficulties eliminated by the introduction of angular motion.
Vision-Aided, Cooperative Navigation for Multiple Unmanned Vehicles
2009
210 pages
Report
No indication
English
Aircraft , Military Intelligence , Navigation Systems , Common Carrier & Satellite , Wireless links , Cooperation , Surveillance , Drones , Intelligence , Aerial reconnaissance , Networks , Angular motion , Inertial navigation , Autonomous navigation , Data fusion , Estimates , Theses , Position(Location) , Computerized simulation , Errors , Image-aided navigation , Cooperative navigation , Federated filters , Feature tracking , Passive navigation , Onboard vision systems , Position error estimates , Stationary motion , Linear motion
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