Intelligent remote sensing satellite and remote sensing image real-time service

doi:10.11947/j.AGCS.2019.20190454

Abstract

Abstract: The traditional data acquisition, processing and application mode of satellite remote sensing system can't meet the application requirements of satellite remote sensing image popularization and real-time, and it is urgent to develop intelligent remote sensing satellite system to solve the problem of on-orbit processing and intelligent service of remote sensing image. This paper first expounded the development of intelligent remote sensing satellite, and introduced the characteristics of intelligent remote sensing satellite. Then the article gave a detailed introduction to the intelligent remote sensing satellite on-orbit processing architecture, service mode and key algorithms involved in on-orbit processing. Finally, the paper explored the service scenario and service mode of Luojia-3-01 satellite based on the design and development of Luojia-3-01,and prospected the development of intelligent remote sensing satellite under the background of 5G, 6G, and artificial intelligence era.

Key words: intelligent remote sensing satellite, space-air information network, on-orbit processing, real-time service

CLC Number:

P231
TP701

WANG Mi, YANG Fang. Intelligent remote sensing satellite and remote sensing image real-time service[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(12): 1586-1594.

References

[1] 张兵. 智能遥感卫星系统[J] 遥感学报, 2011, 15(3):415-431. ZHANG Bing. Intelligent remote sensing satellite system[J] Journal of Remote Sensing, 2011, 15(3):415-431.
[2] HAYDEN S C, SWEET A J, CHRISTA S E, et al. Advanced diagnostic system on earth observing one[C]//Proceedings of American Institute of Aeronautics and Astronautics. San Diego:AIAA, 2004.
[3] STRAIGHT S D, DOOLITTLE C, COOLEY T, et al. Tactical satellite-3 mission overview and initial lessons learned[C]//Proceedings of Annual AIAA/USU Conference on Small Satellites.[S.l.]:AIAA, 2010.
[4] SULLIVAN G J, OHM J R, HAN W J, et al. Overview of the high efficiency video coding (HEVC) standard[J] IEEE Transactions on Circuits and Systems for Video Technology, 2012, 22(12):1649-1668.
[5] 肖学敏. JPEG2000卫星图像压缩方法的研究与实现[D]. 长沙:国防科学技术大学, 2007. XIAO Xuemin. Research and implementation of JPEG2000 satellite image compression[D].Changsha:National University of Defense Technology, 2007.
[6] 肖化超, 周诠, 张建华. 遥感卫星在轨机场变化检测方法[J]. 测绘通报, 2015(1):22-25. XIAO Huachao, ZHOU Quan, ZHANG Jianhua. An airport change onboard detection method for remote sensing satellite[J]. Bulletin of Surveying and Mapping, 2015(1):22-25.
[7] 李德仁, 沈欣, 龚健雅, 等. 论我国空间信息网络的构建[J] 武汉大学学报(信息科学版), 2015, 40(6):711-715, 766. LI Deren, SHEN Xin, GONG Jianya, et al. On construction of China's space information network[J] Geomatics and Information Science of Wuhan University, 2015, 40(6):711-715, 766.
[8] 李德仁. 论空天地一体化对地观测网络[J] 地球信息科学学报, 2012, 14(4):419-425. LI Deren. On space-air-ground integrated earth observation network[J] Journal of Geo-Information Science, 2012, 14(4):419-425.
[9] YOUNES B A, SCHIER J S. Space communications and navigation (SCaN) integrated network architecture definition document (ADD). Volume 1:Executive Summary[R] Washington, D. C:Space Communications and Navigation Office, 2010.
[10] TAI W, WRIGHT N, PRIOR M, et al. NASA integrated space communications network[C]//Proceedings of SpaceOps 2012 Conference. Stockholm, Sweden:American Institute of Aeronautics and Astronautics, 2012.
[11] BHASIN K, HAYDEN J L. Space internet architectures and technologies for NASA enterprises[J] International Journal of Satellite Communications, 2002, 20(5):311-332.
[12] CRISP N, SMITH K, HOLLINGSWORTH P. Small satellite launch to LEO:a review of current and future launch system[J] Transactions of the Japan Society for Aeronautical and Space Sciences, 2014, 12(29):39-47.
[13] VANCE L, WOIDA R, STALLINGS J. Responsive imaging surveillance using CubeSat technologies derived from the DARPA SeeMe project[C]//Proceedings of the 28th Annual AIAA/USU Conference on Small Satellites.[S.l.]:AIAA, 2014.
[14] SCARDERA M, BAKER M, REYNOLDS R, et al. ALTAIR:millennium's DARPA SeeMe satellite Solution technical (R) evolution[C]//Proceedings of the 28th Annual AIAA/USU Conference on Small Satellites.[S.l.]:AIAA, 2014.
[15] 罗雪山, 黄光奇, 袁卫卫. 天地一体化信息支持系统概念研究[J]. 军事运筹与系统工程, 2002(1):52-54. LUO Xueshan, HUANG Guangqi, YUAN Weiwei. Research on the concept of integrated information support system[J]. Military Operations Research and Systems Engineering, 2002(1):52-54.
[16] 李德仁, 沈欣. 论智能化对地观测系统[J] 测绘科学, 2005, 30(4):9-11. LI Deren, SHEN Xin. On intelligent earth observation systems[J]. Science of Surveying and Mapping, 2005, 30(4):9-11.
[17] 沈荣骏. 我国天地一体化航天互联网构想[J] 中国工程科学, 2006, 8(10):19-30. SHEN Rongjun. Some thoughts of Chinese integrated space-ground network system[J] Engineering Science, 2006, 8(10):19-30.
[18] 李德仁. 从测绘学到地球空间信息智能服务科学[J]. 测绘学报,2017,46(10):1207-1212. LI Deren. From geomatics to geospatial intelligent service science[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10):1207-1212.
[19] 李德仁, 王密, 沈欣, 等. 从对地观测卫星到对地观测脑[J] 武汉大学学报(信息科学版), 2017, 42(2):143-149. LI Deren, WANG Mi, SHEN Xin, et al. From earth observation satellite to earth observation brain[J] Geomatics and Information Science of Wuhan University, 2017, 42(2):143-149.
[20] 王斌, 范冬林. 深度学习在遥感影像分类与识别中的研究进展综述[J] 测绘通报, 2019(2):99-102, 136. DOI:10.13474/j.cnki.11-2246.2019.0052. WANG Bin, FAN Donglin. Research progress of deep learning in classification and recognition of remote sensing images[J] Bulletin of Surveying and Mapping, 2019(2):99-102, 136. DOI:10.13474/j.cnki.11-2246.2019.0052.
[21] 马建文, 陈雪. 遥感数据处理中的现代人工智能方法[J]. 遥感学报, 2009, 13(s1):237-244. MA Jianwen, CHEN Xue. Modern artificial intelligence method in remote sensing data processing[J]. Journal of Remote Sensing, 2009,13(s1):237-244.
[22] XIAO Zhifeng, LONG Yang, LI Deren, et al. High-resolution remote sensing image retrieval based on CNNs from a dimensional perspective[J]. Remote Sensing, 2017, 9(7):725.
[23] MAGGIORI E, TARABALKA Y, CHARPIAT G, et al. Fully convolutional neural networks for remote sensing image classification[C]//Proceedings of 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Beijing, China:IEEE, 2016.
[24] WANG Hongzhen, WANG Ying, ZHANG Qian, et al. Gated convolutional neural network for semantic segmentation in high-resolution images[J]. Remote Sensing, 2017, 9(5):446.
[25] XIAO Zhifeng, LONG Yang, LI Deren, et al. High-resolution remote sensing image retrieval based on CNNs from a dimensional perspective[J]. Remote Sensing, 2017, 9(7):725.