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Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

Jincheng Li1, Jie Chen2,3, Pengbo Wang4,5

  • 1School of Electronic and Information Engineering, Beihang University, Beijing 100191, China. lijincheng_buaa@163.com.

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This study introduces an image-based path planner for lightweight unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) systems. The novel approach enhances reconnaissance performance by optimizing UAV routes for multiple regions of interest.

Keywords:
A* search algorithmaerial surveillancelightweight unmanned aerial vehicle (UAV)path planningsynthetic aperture radar (SAR)

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Area of Science:

  • Robotics and Control Systems
  • Remote Sensing Technology
  • Artificial Intelligence for Navigation

Background:

  • Unmanned aerial vehicle (UAV) surveillance performance is critically dependent on motion control and sensor operation.
  • Lightweight UAV synthetic aperture radar (SAR) systems face challenges in planning paths for multiple regions of interest (ROIs) comparable in size to the radar swath width.

Purpose of the Study:

  • To address the 2D path planning problem for lightweight UAV SAR systems operating in environments with multiple ROIs.
  • To develop a sensor-oriented path planner that accounts for the specific motion requirements of SAR systems.

Main Methods:

  • Modeling UAV SAR path planning as a constrained multiobjective optimization problem (MOP).
  • Proposing an image-based path planner utilizing morphological operations to merge neighboring ROIs.
  • Employing geometric features and observation geometry for route segment localization.
  • Connecting route segments using the sampling-based sparse A* search (SSAS) algorithm.

Main Results:

  • The proposed image-based path planner effectively plans routes for lightweight UAV SAR systems.
  • Simulation experiments demonstrate significant improvements in reconnaissance performance compared to conventional zigzag path planners.
  • The sensor-oriented approach optimizes data collection for ROIs of varying sizes.

Conclusions:

  • The developed image-based path planner offers a superior strategy for UAV SAR surveillance.
  • This method enhances the efficiency and effectiveness of reconnaissance missions for lightweight UAV SAR systems.
  • The SSAS algorithm integration provides robust route connectivity for complex surveillance scenarios.