UAV Mission Planning with SAR Application.

Area of Science:

• Robotics and Automation
• Aerospace Engineering
• Operations Research

Background:

• Short-range tactical Unmanned Aerial Vehicles (UAVs) are crucial for aerial reconnaissance in military operations.
• Effective mission planning is essential to maximize sensor utilization (EO/NIR, SAR, ELINT) for target recognition.
• Existing methods require optimization for dynamic tactical environments.

Purpose of the Study:

• To develop an optimized mission planning framework for tactical UAVs.
• To determine optimal flight routes and sensor assignments for reconnaissance tasks.
• To integrate technical parameters and tactical constraints into a unified planning approach.

Main Methods:

• Decomposition of the mission planning problem into subproblems: task assignment, sensor selection, and initial/detailed route planning.
• Formulation of the task scheduling as a Vehicle Route Planning with Time Window (VRPTW) problem.
• Solving the VRPTW using Mixed Integer Linear Programming (MILP) for detailed trajectory generation.

Main Results:

• An algorithm for generating precise UAV flight trajectories considering time constraints and sensor characteristics.
• Successful integration of enemy presence and air corridor data into route planning.
• Demonstrated capability for both individual and cooperative UAV mission planning.

Conclusions:

• The proposed MILP-based approach provides a practical and effective method for tactical UAV mission planning.
• The system optimizes reconnaissance capabilities by intelligently assigning tasks and planning routes.
• This framework supports the implementation of advanced autonomous reconnaissance missions in real-world systems.