Improved Real-Time SPGA Algorithm and Hardware Processing Architecture for Small UAVs
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| הוצא לאור ב: | Remote Sensing vol. 17, no. 13 (2025), p. 2232-2263 |
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| מחברים אחרים: | , , , , , |
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MDPI AG
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| גישה מקוונת: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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MARC
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|---|---|---|---|
| 001 | 3229156930 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2072-4292 | ||
| 024 | 7 | |a 10.3390/rs17132232 |2 doi | |
| 035 | |a 3229156930 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231556 |2 nlm | ||
| 100 | 1 | |a Wang, Huan |u National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China; wanghuan21a@mails.ucas.ac.cn (H.W.); | |
| 245 | 1 | |a Improved Real-Time SPGA Algorithm and Hardware Processing Architecture for Small UAVs | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Real-time Synthetic Aperture Radar (SAR) imaging for small Unmanned Aerial Vehicles (UAVs) has become a significant research focus. However, limitations in Size, Weight, and Power (SwaP) restrict the imaging quality and timeliness of small UAV-borne SAR, limiting its practical application. This paper presents a non-iterative real-time Feature Sub-image Based Stripmap Phase Gradient Autofocus (FSI-SPGA) algorithm. The FSI-SPGA algorithm combines 2D Constant False Alarm Rate (CFAR) for coarse point selection and spatial decorrelation for refined point selection. This approach enables the accurate extraction of high-quality scattering points. Using these points, the algorithm constructs a feature sub-image containing comprehensive phase error information and performs a non-iterative phase error estimation based on this sub-image. To address the multifunctional, low-power, and real-time requirements of small UAV SAR, we designed a highly efficient hybrid architecture. This architecture integrates dataflow reconfigurability and dynamic partial reconfiguration and is based on an ARM + FPGA platform. It is specifically tailored to the computational characteristics of the FSI-SPGA algorithm. The proposed scheme was assessed using data from a 6 kg small SAR system equipped with centimeter-level INS/GPS. For SAR images of size 4096 × 12,288, the FSI-SPGA algorithm demonstrated a 6 times improvement in processing efficiency compared to traditional methods while maintaining the same level of precision. The high-efficiency reconfigurable ARM + FPGA architecture processed the algorithm in 6.02 s, achieving 12 times the processing speed and three times the energy efficiency of a single low-power ARM platform. These results confirm the effectiveness of the proposed solution for enabling high-quality real-time SAR imaging under stringent SwaP constraints. | |
| 653 | |a Accuracy | ||
| 653 | |a Constant false alarm rate | ||
| 653 | |a Algorithms | ||
| 653 | |a Unmanned aerial vehicles | ||
| 653 | |a Synthetic aperture radar | ||
| 653 | |a Energy efficiency | ||
| 653 | |a Miniature aircraft | ||
| 653 | |a Design | ||
| 653 | |a Error analysis | ||
| 653 | |a Phase error | ||
| 653 | |a Field programmable gate arrays | ||
| 653 | |a Digital signal processors | ||
| 653 | |a Radar imaging | ||
| 653 | |a Real time | ||
| 653 | |a Reconfiguration | ||
| 653 | |a Parameter estimation | ||
| 700 | 1 | |a Liu, Yunlong |u National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China; wanghuan21a@mails.ucas.ac.cn (H.W.); | |
| 700 | 1 | |a Li, Yanlei |u National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China; wanghuan21a@mails.ucas.ac.cn (H.W.); | |
| 700 | 1 | |a Li, Hang |u National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China; wanghuan21a@mails.ucas.ac.cn (H.W.); | |
| 700 | 1 | |a Ge Xuyang |u National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China; wanghuan21a@mails.ucas.ac.cn (H.W.); | |
| 700 | 1 | |a Jihao, Xin |u National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China; wanghuan21a@mails.ucas.ac.cn (H.W.); | |
| 700 | 1 | |a Liang Xingdong |u National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China; wanghuan21a@mails.ucas.ac.cn (H.W.); | |
| 773 | 0 | |t Remote Sensing |g vol. 17, no. 13 (2025), p. 2232-2263 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3229156930/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3229156930/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3229156930/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |