Reconnaissance and Surveillance in Urban Terrain with Unmanned Aerial Vehicles
Abstract
Unmanned vehicles endowed with attributes of intelligence are finding applications in reconnaissance, surveillance, and rescue operations in both military and civilian domains. We are introducing a methodology to locate a number of such Unmanned Aerial Vehicles (UAVs) optimally over an urban environment and identify and track potential ground targets using a particle filtering framework. The particle filtering framework, when used in conjunction with novel initialization and adaptation techniques, is a robust, reliable state estimation tool that avoids many of the drawbacks of classical techniques. Simulation results support the efficacy of the proposed approach and validate the effectiveness of the algorithmic developments.
