Autonomous Navigation of UAVs in Complex Battlefield Environments Using Ant Colony Optimization

This study explores how UAVs achieve autonomous flight in complex combat zones using Ant Colony Optimization algorithm implemented in MATLAB. The simulation assumes a 20km×20km operational area with UAV starting coordinates at [1,2] km and target coordinates at [19,18] km, ignoring takeoff/landing constraints. The implementation includes digital terrain mapping with three simplified categories (highland, lowland, transition zones) and radar threat modeling provided in attachments.