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The application of Internet of Things (IoT) in wide-area infrastructure inspection, such as power transmission corridors, necessitates advanced sensing on mobile edge nodes like Unmanned Aerial Vehicles (UAVs). Synthetic Aperture Radar (SAR) is a promising technology to achieve this aim, and the Range Migration Algorithm (RMA) stands out among kinds of SAR algorithms for its high accuracy. However, RMA suffers from interpolation efficiency and flexibility, which hinders its deployment for time-sensitive task on resource-constrained edge platform. To address this challenge, this paper proposes OSF-RMA, a fast RMA design based on an optimized mapping algorithm instead of interpolation, and a selective focusing module. OSF-RMA employs an adaptive approximation and algebraic unrolling scheme to improve the Interpolation-Free Stolt Mapping efficiency, which is a substitute for Stolt interpolation in traditional RMA. Subsequently, a range stacking based module is proposed to directly reconstruct a specified Region of Interest (ROI), thus bypassing the need of computation-intensive full-scene imaging. The simulation results demonstrate that OSF-RMA, compared to traditional RMA, improves the computational efficiency for the ROI-centric task by up to 92%. This work provides a promising solution for deploying flexible and high-timeliness SAR applications on aerial IoT sensing nodes.

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Accelerating SAR-Based Sensing for Wide-Area IoT: A Fast and Flexible RMA Framework

  • 会议论文

  • 发表日期：

    2026年

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  • Zheqi Su,
  • Xiong Wang,
  • Linghe Kong

摘要

The application of Internet of Things (IoT) in wide-area infrastructure inspection, such as power transmission corridors, necessitates advanced sensing on mobile edge nodes like Unmanned Aerial Vehicles (UAVs). Synthetic Aperture Radar (SAR) is a promising technology to achieve this aim, and the Range Migration Algorithm (RMA) stands out among kinds of SAR algorithms for its high accuracy. However, RMA suffers from interpolation efficiency and flexibility, which hinders its deployment for time-sensitive task on resource-constrained edge platform. To address this challenge, this paper proposes OSF-RMA, a fast RMA design based on an optimized mapping algorithm instead of interpolation, and a selective focusing module. OSF-RMA employs an adaptive approximation and algebraic unrolling scheme to improve the Interpolation-Free Stolt Mapping efficiency, which is a substitute for Stolt interpolation in traditional RMA. Subsequently, a range stacking based module is proposed to directly reconstruct a specified Region of Interest (ROI), thus bypassing the need of computation-intensive full-scene imaging. The simulation results demonstrate that OSF-RMA, compared to traditional RMA, improves the computational efficiency for the ROI-centric task by up to 92%. This work provides a promising solution for deploying flexible and high-timeliness SAR applications on aerial IoT sensing nodes.