Multi-stage Planning for Multi-target Surveillance using Aircrafts Equipped with Synthetic Aperture Radars Aware of Target Visibility

• URL: http://arxiv.org/abs/2604.16962v1
• Date: Sat, 18 Apr 2026 11:04:25 GMT
• Title: Multi-stage Planning for Multi-target Surveillance using Aircrafts Equipped with Synthetic Aperture Radars Aware of Target Visibility
• Abstract summary: This paper presents a novel system for generating trajectories for synthetic aperture radar (SAR)-equipped aircraft.<n>A novel neural network trained with deep reinforcement learning is used to predict straight-flight segments maximizing target visibility according to the 3D terrain.<n>The system ensures high-quality multi-target SAR image acquisition aware of 3D terrain and target visibility, and real-time performance.
• Score: 40.94744872735617
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Generating trajectories for synthetic aperture radar (SAR)-equipped aircraft poses significant challenges due to terrain constraints, and the need for straight-flight segments to ensure high-quality imaging. Related works usually focus on trajectory optimization for predefined straight-flight segments that do not adapt to the target visibility, which depends on the 3D terrain and aircraft orientation. In addition, this assumption does not scale well for the multi-target problem, where multiple straight-flight segments that maximize target visibility must be defined for real-time operations. For this purpose, this paper presents a multi-stage planning system. First, the waypoint sequencing to visit all the targets is estimated. Second, straight-flight segments maximizing target visibility according to the 3D terrain are predicted using a novel neural network trained with deep reinforcement learning. Finally, the segments are connected to create a trajectory via optimization that imposes 3D Dubins curves. Evaluations demonstrate the robustness of the system for SAR missions since it ensures high-quality multi-target SAR image acquisition aware of 3D terrain and target visibility, and real-time performance.

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