LAUSR

Abstract The paper introduces a cooperative system to search for and localize targets by the use of low cost sensors. The system works based on collaboration of several decentralized, similar and self-organized components that are separately installed on flying vehicles. Interactions and information sharing between these flying vehicles construct a sensor and actuating network that cause the flying vehicles to search more intelligently and gather more efficient signals despite poor quality sensors. In each flying vehicle, a modified version of Monte-Carlo filter is implemented in order to fuse its own sensor measurements with the information received from the other vehicles and the priori of the targets to evolve into the posterior. The target posterior is then used to generate guidance points for the vehicle searching guidance law. The searching guidance law directs the vehicle through guidance points where the best measurements are available for an optimum search. Observability studies are performed to show that the developed system is able to extract the states of targets from measurements. In addition, numerical results by the use of an accurate simulation program, statistically show the performance of the developed system.