Flight Path Optimization for UAV-Aided Reconnaissance Data Collection

While UAV-aided reconnaissance data collection grows rapidly, its path optimization is severely hindered by environmental dynamics, node mobility, and overlapping security/interference risks. This paper addresses the problem of data collection from mobile reconnaissance nodes in interference environments, incorporating safety flight constraints and dynamic constraints. We propose an integrated path optimization framework combining initial path guidance with dynamic replanning capabilities. The system first predicts reconnaissance node and interference source positions while analyzing channel conditions to generate an optimal initial path within the designated communication flight corridor. Subsequently, the framework addresses non-convex path planning challenges using slack variables and equivalent constraints, with the successive convex approximation algorithm providing efficient iterative solutions. Numerical results show that in dynamically changing scenarios, the proposed method achieves high reliability and planning efficiency for real-time, data-collection-oriented path optimization.