A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPU
To achieve on-board real-time processing for sliding-spotlight mode synthetic aperture radar (SAR), on the one hand, this paper proposes an adaptive and efficient imaging algorithm for the sliding-spotlight mode. On the other hand, a batch processing method was designed and optimized based on the AG...
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MDPI AG
2025-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/9/1495 |
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| author | Yunju Zhang Mingyang Shang Yini Lv Xiaolan Qiu |
| author_facet | Yunju Zhang Mingyang Shang Yini Lv Xiaolan Qiu |
| author_sort | Yunju Zhang |
| collection | DOAJ |
| description | To achieve on-board real-time processing for sliding-spotlight mode synthetic aperture radar (SAR), on the one hand, this paper proposes an adaptive and efficient imaging algorithm for the sliding-spotlight mode. On the other hand, a batch processing method was designed and optimized based on the AGX Orin platform to implement the algorithm effectively. Based on the chirp scaling (CS) algorithm, sliding-spotlight mode imaging can be achieved by adding Deramp preprocessing along with either zero-padding or performing an extra chirp scaling operation. This article analyzes the computational complexity of the two algorithms and provides a criterion called the Method Choice Indicator (MCI) for selecting the appropriate method. Additionally, the mathematical expressions for time–frequency transformation are derived, providing the theoretical basis for calculating the equivalent PRF and the azimuth width represented by a single pixel. To increase the size of the data that AGX Orin can process, the batch processing method was proposed to reduce peak memory usage during imaging, so that the limited memory could be better utilized. Meanwhile, this algorithm was also compatible with strip mode and TOPSAR (Terrain Observation by Progressive scans SAR) mode imaging. While batch processing increased data transfers, the integrated architecture of AGX Orin minimized the negative impact. Subsequently, through a series of optimizations of the algorithm, the efficiency of the algorithm was further improved. As a result, it took 19.25 s to complete the imaging process for sliding-spotlight mode data with a size of 42,966 × 27,648. Since satellite data acquisition time was 11.43 s, it can be considered that this method achieved near-real-time imaging. The experimental results demonstrate the feasibility of on-board processing. |
| format | Article |
| id | doaj-art-af6e61423cc74faab0dd5ae9d1f1d0f7 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-04-01 |
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| series | Remote Sensing |
| spelling | doaj-art-af6e61423cc74faab0dd5ae9d1f1d0f72025-08-20T01:49:24ZengMDPI AGRemote Sensing2072-42922025-04-01179149510.3390/rs17091495A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPUYunju Zhang0Mingyang Shang1Yini Lv2Xiaolan Qiu3National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaSuzhou Aerospace Information Research Institute, Suzhou 215123, ChinaSuzhou Aerospace Information Research Institute, Suzhou 215123, ChinaNational Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaTo achieve on-board real-time processing for sliding-spotlight mode synthetic aperture radar (SAR), on the one hand, this paper proposes an adaptive and efficient imaging algorithm for the sliding-spotlight mode. On the other hand, a batch processing method was designed and optimized based on the AGX Orin platform to implement the algorithm effectively. Based on the chirp scaling (CS) algorithm, sliding-spotlight mode imaging can be achieved by adding Deramp preprocessing along with either zero-padding or performing an extra chirp scaling operation. This article analyzes the computational complexity of the two algorithms and provides a criterion called the Method Choice Indicator (MCI) for selecting the appropriate method. Additionally, the mathematical expressions for time–frequency transformation are derived, providing the theoretical basis for calculating the equivalent PRF and the azimuth width represented by a single pixel. To increase the size of the data that AGX Orin can process, the batch processing method was proposed to reduce peak memory usage during imaging, so that the limited memory could be better utilized. Meanwhile, this algorithm was also compatible with strip mode and TOPSAR (Terrain Observation by Progressive scans SAR) mode imaging. While batch processing increased data transfers, the integrated architecture of AGX Orin minimized the negative impact. Subsequently, through a series of optimizations of the algorithm, the efficiency of the algorithm was further improved. As a result, it took 19.25 s to complete the imaging process for sliding-spotlight mode data with a size of 42,966 × 27,648. Since satellite data acquisition time was 11.43 s, it can be considered that this method achieved near-real-time imaging. The experimental results demonstrate the feasibility of on-board processing.https://www.mdpi.com/2072-4292/17/9/1495adaptive selectionAGX Orinon-board near-real-time processingsynthetic aperture radar (SAR) |
| spellingShingle | Yunju Zhang Mingyang Shang Yini Lv Xiaolan Qiu A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPU Remote Sensing adaptive selection AGX Orin on-board near-real-time processing synthetic aperture radar (SAR) |
| title | A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPU |
| title_full | A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPU |
| title_fullStr | A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPU |
| title_full_unstemmed | A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPU |
| title_short | A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPU |
| title_sort | near real time imaging algorithm for focusing spaceborne sar data in multiple modes based on an embedded gpu |
| topic | adaptive selection AGX Orin on-board near-real-time processing synthetic aperture radar (SAR) |
| url | https://www.mdpi.com/2072-4292/17/9/1495 |
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