{"title":"合成孔径雷达机载图像处理的资源约束优化","authors":"Maron Schlemon, M. Schulz, R. Scheiber","doi":"10.1109/HPEC55821.2022.9926327","DOIUrl":null,"url":null,"abstract":"Synthetic Aperture Radar (SAR) can be used to create realistic and high-resolution 2D or 3D reconstructions of landscapes. The data capture is typically deployed using radar instruments in specially equipped, low flying planes, resulting in a large amount of raw data, which needs to be processed for image reconstruction. However, due to limited on-board processing capacities on the plane (power, size, weight, cooling, communication bandwidth to ground stations, etc.) and the need to capture many images during a single flight, the raw data must be processed on-board and then sent to the ground station efficiently as image products. In this paper we describe the processing architecture of the digital beamforming SAR (DBFSAR) of the German Areaospace Center (DLR) and the special steps that had to be taken to enable the on-board processing. We explain the required software optimizations and under which conditions their integration in the SAR imaging process leads to (near) real-time capability. We further describe the lessons learned in our work and discuss how they can be applied to other processing scenarios with limited resource availability.","PeriodicalId":200071,"journal":{"name":"2022 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Resource-Constrained Optimizations For Synthetic Aperture Radar On-Board Image Processing\",\"authors\":\"Maron Schlemon, M. Schulz, R. Scheiber\",\"doi\":\"10.1109/HPEC55821.2022.9926327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Synthetic Aperture Radar (SAR) can be used to create realistic and high-resolution 2D or 3D reconstructions of landscapes. The data capture is typically deployed using radar instruments in specially equipped, low flying planes, resulting in a large amount of raw data, which needs to be processed for image reconstruction. However, due to limited on-board processing capacities on the plane (power, size, weight, cooling, communication bandwidth to ground stations, etc.) and the need to capture many images during a single flight, the raw data must be processed on-board and then sent to the ground station efficiently as image products. In this paper we describe the processing architecture of the digital beamforming SAR (DBFSAR) of the German Areaospace Center (DLR) and the special steps that had to be taken to enable the on-board processing. We explain the required software optimizations and under which conditions their integration in the SAR imaging process leads to (near) real-time capability. We further describe the lessons learned in our work and discuss how they can be applied to other processing scenarios with limited resource availability.\",\"PeriodicalId\":200071,\"journal\":{\"name\":\"2022 IEEE High Performance Extreme Computing Conference (HPEC)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE High Performance Extreme Computing Conference (HPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPEC55821.2022.9926327\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC55821.2022.9926327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Resource-Constrained Optimizations For Synthetic Aperture Radar On-Board Image Processing
Synthetic Aperture Radar (SAR) can be used to create realistic and high-resolution 2D or 3D reconstructions of landscapes. The data capture is typically deployed using radar instruments in specially equipped, low flying planes, resulting in a large amount of raw data, which needs to be processed for image reconstruction. However, due to limited on-board processing capacities on the plane (power, size, weight, cooling, communication bandwidth to ground stations, etc.) and the need to capture many images during a single flight, the raw data must be processed on-board and then sent to the ground station efficiently as image products. In this paper we describe the processing architecture of the digital beamforming SAR (DBFSAR) of the German Areaospace Center (DLR) and the special steps that had to be taken to enable the on-board processing. We explain the required software optimizations and under which conditions their integration in the SAR imaging process leads to (near) real-time capability. We further describe the lessons learned in our work and discuss how they can be applied to other processing scenarios with limited resource availability.