{"title":"MERSI 啸扫扫描仪的在轨几何校准","authors":"Hongbo Pan, Xue Zhang, Zixuan Liu, Tao Huang","doi":"10.1016/j.isprsjprs.2024.11.007","DOIUrl":null,"url":null,"abstract":"The whiskbroom scanner is a critical component in remote sensing payloads, such as the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Joint Polar Satellite System (JPSS) and the Medium Resolution Spectral Imager (MERSI) on FengYun-3. However, panoramic distortion in whiskbroom scanner images increases overlap from the nadir to the edges between adjacent scans. These distortions present significant challenges for improving geolocation accuracy, particularly when errors occur in sensors and platforms. This manuscript derives analytic expressions for all potential error sources, including sensors, platforms, and elevation, using homogeneous coordinates in the focal plane. This derivation demonstrates that geolocation errors vary with view angles and detector positions. To further investigate these error properties, a gradient-aware least-squares matching method was developed to extract highly accurate and dense ground control points (GCPs) with approximately 100,000 points in a single scene. A three-step geometric calibration method was then introduced, which includes boresight misalignment correction, parametric geometric calibration, and non-uniform scanning compensation. Given the varying spatial resolution of the GCPs, the weight of the GCPs was dynamically updated for least-squares estimation. This method effectively demonstrated the complex geolocation errors in MERSI on FY-3D, a system that was not meticulously calibrated in the laboratory. The initial root mean square errors (RMSEs) were 3.354 and 12.441 instantaneous field of view (IFoV) for the designed parameters. The proposed geometric calibration method successfully corrected view-angle and detector position-related geolocation errors, reducing them to 0.211 and 0.225 IFoV in the scan and track directions, respectively. The geolocation validation software and experiment results were provided <ce:inter-ref xlink:href=\"https://github.com/hongbop/whiskgeovalidation.git\" xlink:type=\"simple\">https://github.com/hongbop/whiskgeovalidation.git</ce:inter-ref>.","PeriodicalId":50269,"journal":{"name":"ISPRS Journal of Photogrammetry and Remote Sensing","volume":"190 1","pages":""},"PeriodicalIF":10.6000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On-orbit geometric calibration of MERSI whiskbroom scanner\",\"authors\":\"Hongbo Pan, Xue Zhang, Zixuan Liu, Tao Huang\",\"doi\":\"10.1016/j.isprsjprs.2024.11.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The whiskbroom scanner is a critical component in remote sensing payloads, such as the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Joint Polar Satellite System (JPSS) and the Medium Resolution Spectral Imager (MERSI) on FengYun-3. However, panoramic distortion in whiskbroom scanner images increases overlap from the nadir to the edges between adjacent scans. These distortions present significant challenges for improving geolocation accuracy, particularly when errors occur in sensors and platforms. This manuscript derives analytic expressions for all potential error sources, including sensors, platforms, and elevation, using homogeneous coordinates in the focal plane. This derivation demonstrates that geolocation errors vary with view angles and detector positions. To further investigate these error properties, a gradient-aware least-squares matching method was developed to extract highly accurate and dense ground control points (GCPs) with approximately 100,000 points in a single scene. A three-step geometric calibration method was then introduced, which includes boresight misalignment correction, parametric geometric calibration, and non-uniform scanning compensation. Given the varying spatial resolution of the GCPs, the weight of the GCPs was dynamically updated for least-squares estimation. This method effectively demonstrated the complex geolocation errors in MERSI on FY-3D, a system that was not meticulously calibrated in the laboratory. The initial root mean square errors (RMSEs) were 3.354 and 12.441 instantaneous field of view (IFoV) for the designed parameters. The proposed geometric calibration method successfully corrected view-angle and detector position-related geolocation errors, reducing them to 0.211 and 0.225 IFoV in the scan and track directions, respectively. The geolocation validation software and experiment results were provided <ce:inter-ref xlink:href=\\\"https://github.com/hongbop/whiskgeovalidation.git\\\" xlink:type=\\\"simple\\\">https://github.com/hongbop/whiskgeovalidation.git</ce:inter-ref>.\",\"PeriodicalId\":50269,\"journal\":{\"name\":\"ISPRS Journal of Photogrammetry and Remote Sensing\",\"volume\":\"190 1\",\"pages\":\"\"},\"PeriodicalIF\":10.6000,\"publicationDate\":\"2024-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISPRS Journal of Photogrammetry and Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1016/j.isprsjprs.2024.11.007\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISPRS Journal of Photogrammetry and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1016/j.isprsjprs.2024.11.007","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
On-orbit geometric calibration of MERSI whiskbroom scanner
The whiskbroom scanner is a critical component in remote sensing payloads, such as the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Joint Polar Satellite System (JPSS) and the Medium Resolution Spectral Imager (MERSI) on FengYun-3. However, panoramic distortion in whiskbroom scanner images increases overlap from the nadir to the edges between adjacent scans. These distortions present significant challenges for improving geolocation accuracy, particularly when errors occur in sensors and platforms. This manuscript derives analytic expressions for all potential error sources, including sensors, platforms, and elevation, using homogeneous coordinates in the focal plane. This derivation demonstrates that geolocation errors vary with view angles and detector positions. To further investigate these error properties, a gradient-aware least-squares matching method was developed to extract highly accurate and dense ground control points (GCPs) with approximately 100,000 points in a single scene. A three-step geometric calibration method was then introduced, which includes boresight misalignment correction, parametric geometric calibration, and non-uniform scanning compensation. Given the varying spatial resolution of the GCPs, the weight of the GCPs was dynamically updated for least-squares estimation. This method effectively demonstrated the complex geolocation errors in MERSI on FY-3D, a system that was not meticulously calibrated in the laboratory. The initial root mean square errors (RMSEs) were 3.354 and 12.441 instantaneous field of view (IFoV) for the designed parameters. The proposed geometric calibration method successfully corrected view-angle and detector position-related geolocation errors, reducing them to 0.211 and 0.225 IFoV in the scan and track directions, respectively. The geolocation validation software and experiment results were provided https://github.com/hongbop/whiskgeovalidation.git.
期刊介绍:
The ISPRS Journal of Photogrammetry and Remote Sensing (P&RS) serves as the official journal of the International Society for Photogrammetry and Remote Sensing (ISPRS). It acts as a platform for scientists and professionals worldwide who are involved in various disciplines that utilize photogrammetry, remote sensing, spatial information systems, computer vision, and related fields. The journal aims to facilitate communication and dissemination of advancements in these disciplines, while also acting as a comprehensive source of reference and archive.
P&RS endeavors to publish high-quality, peer-reviewed research papers that are preferably original and have not been published before. These papers can cover scientific/research, technological development, or application/practical aspects. Additionally, the journal welcomes papers that are based on presentations from ISPRS meetings, as long as they are considered significant contributions to the aforementioned fields.
In particular, P&RS encourages the submission of papers that are of broad scientific interest, showcase innovative applications (especially in emerging fields), have an interdisciplinary focus, discuss topics that have received limited attention in P&RS or related journals, or explore new directions in scientific or professional realms. It is preferred that theoretical papers include practical applications, while papers focusing on systems and applications should include a theoretical background.