电信科学 ›› 2022, Vol. 38 ›› Issue (4): 59-69.doi: 10.11959/j.issn.1000-0801.2022075
常晓宇1,2, 张伟嘉1, 李旭东1, 张晓男1,2, 王港1,2, 贾钢1
修回日期:
2022-04-10
出版日期:
2022-04-20
发布日期:
2022-04-01
作者简介:
常晓宇(1994− ),男,中国电子科技集团公司第五十四研究所助理工程师,主要研究方向为遥感信息智能提取及应用基金资助:
Xiaoyu CHANG1,2, Weijia ZHANG1, Xudong1 LI1, Xiaonan ZHANG1,2, Gang WANG1,2, Gang JIA1
Revised:
2022-04-10
Online:
2022-04-20
Published:
2022-04-01
Supported by:
摘要:
低轨互联网星座是当前全球研究和发展的热点,互联网星座支持随遇接入遥感卫星和信息在轨直接处理的应用前景备受期待,但由于轨道高度不同会产生双向高动态异构星座的接入互联问题。首先,通过设定低轨卫星互联网星座在不同轨道特性、不同卫星数量情况下的随遇接入仿真场景,重点探讨了时空非连续可视性和多普勒频移问题对遥感卫星接入性能的影响;其次,基于遥感卫星随遇接入互联网星座场景的特点,分析了不同时延性在轨处理任务的流程及其星地功能分配;最后,对当前在轨智能处理算法存在的问题和未来研究重点进行阐述,为未来低轨互联网星座及遥感卫星的发展和联合组网应用提供可靠的理论支撑。
中图分类号:
常晓宇, 张伟嘉, 李旭东, 张晓男, 王港, 贾钢. 遥感卫星随遇接入互联网星座和在轨智能处理[J]. 电信科学, 2022, 38(4): 59-69.
Xiaoyu CHANG, Weijia ZHANG, Xudong1 LI, Xiaonan ZHANG, Gang WANG, Gang JIA. Study on remote sensing satellites random access to internet constellation and on-orbit intelligent processing[J]. Telecommunications Science, 2022, 38(4): 59-69.
表5
卫星在轨处理算法及产品生产星地分配表"
在轨算法 | 结果产品 | |
遥感卫星及互联网星座 | ● 预处理算法:辐射校正、系统几何校正、粗正射校正、图像切片 | 时效性要求高、精度要求低的任务:L1 级产品、L2 级产品、目标结果产品、关键信息产品 |
● 目标检测:YOLOv3-tiny、YOLOv4-tiny、YOLOS、mobilenet_ssd、MobileNet、NanoDet等轻量化模型 | ||
● 语义分割:轻量级 Deeplab-v3、LU-Net、CBR-ENet、SKASNet、LRUNet、MUNet等轻量化模型 | ||
● 后处理:图像拼接算法、栅格矢量转化算法 | ||
地面中心 | ● 预处理算法:精确几何校正、精确正射校正、影像相对配准、图像切片 | 精度要求高的任务:L2 级产品、目标结果产品、关键信息产品、精确专题产品 |
● 目标检测:YOLOv4、YOLOv5、FasterR-CNN、SSD等模型 | ||
● 语义分割:Deeplab-v3、HRNetv3、UNet、PSPNet、RefineNet等模型 | ||
● 变化检测:SECDNet、ESCNet、DTCDSCN、STANet等模型 | ||
● 后处理:图像拼接算法、栅格矢量转化算法 |
[1] | 李新桐, 张亚生 . 一种适用于低轨卫星的SDN网络人工智能路由方法[J]. 电子测量技术, 2020,43(22): 109-114. |
LI X T , ZHANG Y S . Artificial intelligence routing method for SDN network suitable for LEO satellites[J]. Electronic Mea-surement Technology, 2020,43(22): 109-114. | |
[2] | 肖永伟, 孙晨华, 赵伟松 . 低轨通信星座发展的思考[J]. 国际太空, 2018(11): 24-32. |
XIAO Y W , SUN C H , ZHAO W S . Discussion on the problem of LEO communication constellation system design[J]. Space International, 2018(11): 24-32. | |
[3] | LORETI P , LUGLIO M , KAPOOR R ,et al. Throughput and delay performance of mobile internet applications using LEO satellite access[C]// Proceedings of International Symposium on 3G Infrastructure & Services.[S.l.:s.n.], 2001. |
[4] | 孙晨华, 肖永伟, 赵伟松 ,等. 天地一体化信息网络低轨移动及宽带通信星座发展设想[J]. 电信科学, 2017,33(12): 43-52. |
SUN C H , XIAO Y W , ZHAO W S ,et al. Development concep-tion of space-ground inteyrated information network LEO mo-bile and broadband Internet constellation[J]. Telecommunica-tions Science, 2017,33(12): 43-52. | |
[5] | EDWARDS B L , ISRAEL D , WILSON K E ,et al. An optical communications pathfinder for the next generation tracking and data relay satellite[C]// Proceedings of SpaceOps 2014 Conference. Reston,Virginia:AIAA, 2014. |
[6] | SUN C , YIN B , LI X D ,et al. Adaptability analysis of IP routing protocol in broadband LEO constellation systems[J]. ZTE Communications, 2020. |
[7] | 孙晨华 . 天基传输网络和天地一体化信息网络发展现状与问题思考[J]. 无线电工程, 2017,47(1): 1-6. |
SUN C H . Research status and problems for space-based trans-mission network and space-ground integrated information net-work[J]. Radio Engineering, 2017,47(1): 1-6. | |
[8] | 吴雪, 宋晓茹, 高嵩 ,等. 基于深度学习的目标检测算法综述[J]. 传感器与微系统, 2021,40(2): 4-7,18. |
WU X , SONG X R , GAO S ,et al. Review of target detection algorithms based on deep learning[J]. Transducer and Micro-system Technologies, 2021,40(2): 4-7,18. | |
[9] | 朱均安 . 基于深度学习的视觉目标跟踪算法研究[D]. 长春:中国科学院大学(中国科学院长春光学精密机械与物理研究所), 2021. |
ZHU J A . Research on visual object tracking algorithm based on deep learning[D]. Changchun:Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences, 2021. | |
[10] | 姚群力, 胡显, 雷宏 . 基于多尺度卷积神经网络的遥感目标检测研究[J]. 光学学报, 2019,39(11): 1128002. |
YAO Q L , HU X , LEI H . Object detection in remote sensing images using multiscale convolutional neural networks[J]. Acta Optica Sinica, 2019,39(11): 1128002. | |
[11] | GIRSHICK R , DONAHUE J , DARRELL T ,et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]// Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2014: 580-587. |
[12] | GIRSHICK R , . Fast R-CNN[C]// Proceedings of 2015 IEEE International Conference on Computer Vision. Piscataway:IEEE Press, 2015: 1440-1448. |
[13] | REN S Q , HE K M , GIRSHICK R ,et al. Faster R-CNN:towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017,39(6): 1137-1149. |
[14] | HE K M , GKIOXARI G , DOLLáR P ,et al. Mask R-CNN[C]// Proceedings of 2017 IEEE International Conference on Computer Vision. Piscataway:IEEE Press, 2017: 2980-2988. |
[15] | DAI J F , LI Y , HE K M ,et al. R-FCN:object detection via region-based fully convolutional networks[EB]. 2016:arXiv:1605.06409[cs.CV]. |
[16] | LIU L , OUYANG W L , WANG X G ,et al. Deep learning for generic object detection:a survey[J]. International Journal of Computer Vision, 2020,128(2): 261-318. |
[17] | REDMON J , DIVVALA S , GIRSHICK R ,et al. You only look once:unified,real-time object detection[C]// Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2016: 779-788. |
[18] | 赵会盼, 乔任重, 张学军 . 一种基于嵌入式平台的轻量化目标检测识别方法[J]. 计算机与网络, 2021,47(15): 55-60. |
ZHAO H P , QIAO R Z , ZHANG X J . A lightweight object de-tection method based on embedded platform[J]. Computer &Network, 2021,47(15): 55-60. | |
[19] | LIU W , ANGUELOV D , ERHAN D ,et al. SSD:Singleshot multibox detector[C]// Proceedings of European Conference on Computer Vision.[S.l.:s.n.], 2016. |
[20] | REDMON J , FARHADI A . YOLO9000:better,faster,stronger[C]// Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2017: 6517-6525. |
[21] | REDMON J , FARHADI A . YOLOv3:an incremental improvement[EB]. 2018:arXiv:1804.02767[cs.CV]. |
[22] | 公明, 刘妍妍, 李国宁 . 改进YOLO-v3的遥感图像舰船检测方法[J]. 电光与控制, 2020,27(5): 102-107. |
GONG M , LIU Y Y , LI G N . A ship detection method for re-mote-sensing images based on improved YOLO-v3[J]. Elec-tronics Optics & Control, 2020,27(5): 102-107. | |
[23] | 王玺坤, 姜宏旭, 林珂玉 . 基于改进型 YOLO 算法的遥感图像舰船检测[J]. 北京航空航天大学学报, 2020,46(6): 1184-1191. |
WANG X K , JIANG H X , LIN K Y . Remote sensing image ship detection based on modified YOLO algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020,46(6): 1184-1191. | |
[24] | 王晓青, 王向军 . 应用于嵌入式图形处理器的实时目标检测方法[J]. 光学学报, 2019,39(3): 0315005. |
WANG X Q , WANG X J . Real-time target detection method applied to embedded graphic processing unit[J]. Acta Optica Sinica, 2019,39(3): 0315005. | |
[25] | 农元君, 王俊杰 . 基于嵌入式的遥感目标实时检测方法[J]. 光学学报, 2021,41(10): 1028001. |
NONG Y J , WANG J J . Real-time object detection in remote sensing images based on embedded system[J]. Acta Optica Si-nica, 2021,41(10): 1028001. | |
[26] | HPE. HPE spaceborne computer[EB]. 2022. |
[27] | PETRICK D , GEIST A , ALBAIJES D ,et al. SpaceCube v2.0 space flight hybrid reconfigurable data processing system[C]// Proceedings of 2014 IEEE Aerospace Conference. Piscataway:IEEE Press, 2014: 1-20. |
[28] | GEIST A , BREWER C , DAVIS M ,et al. Spacecube v3.0 NASA next-generation high-performance processor for science applications[C]// Proceedings of Small Satellite Conference.[S.l.:s.n.], 2019. |
[29] | 颜军, 唐芳福, 张志国 ,等. 异构多核人工智能 SoC 芯片的低功耗设计[J]. 航天控制, 2020,38(2): 62-68. |
YAN J , TANG F F , ZHANG Z G ,et al. Low-power design for heterogeneous multi-core AI SoC chip[J]. Aerospace Control, 2020,38(2): 62-68. | |
[30] | 何友, 姚力波, 李刚 ,等. 多源卫星信息在轨融合处理分析与展望[J]. 宇航学报, 2021,42(1): 1-10. |
HE Y , YAO L B , LI G ,et al. Summary and future development of on-board information fusion for multi-satellite collaborative observation[J]. Journal of Astronautics, 2021,42(1): 1-10. | |
[31] | 刘晓敏, 孙进, 张帅 ,等. 遥感卫星智能操控技术发展研究[J]. 航天器工程, 2021,30(4): 107-116. |
LIU X M , SUN J , ZHANG S ,et al. Research on development of remote sensing satellite intelligent manipulation Technolo-gy[J]. Spacecraft Engineering, 2021,30(4): 107-116. | |
[32] | 赵军锁, 李丹, 潘晏涛 ,等. 天智星云应用开发者平台设计与实现[J]. 软件定义卫星高峰论坛论文集. 2018. |
ZHAO J S , LI D , PAN Y T ,et al. The design and implementa-tion of developers’ platform TianZhiXingYun for smart satel lite[C]// Proceedings of the Forum of Software-defined Satellite. 2018. | |
[33] | 于野 . 基于人工智能的光学遥感在轨船舶检测技术研究[D]. 长春:中国科学院大学(中国科学院长春光学精密机械与物理研究所), 2020. |
YU Y . Research on on-orbit ship detection technology of optical satellite based on artificial intelligence[D]. Changchun:Chang-chun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences, 2020. | |
[34] | 何辞, 张亚生, 孙晨华 ,等. 低轨星座组网及地面 IP 路由技术适应性分析[J]. 天地一体化信息网络, 2020,1(1): 36-41. |
HE C , ZHANG Y S , SUN C H ,et al. Analysis on low-earth-orbit constellation networking and adaptability of ground IP routing technology[J]. Space-Integrated-Ground In-formation Networks, 2020,1(1): 36-41. |
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