雾定位及其应用研究

施闯; 辜声峰; 景贵飞; 耿江辉; 楼益栋; 唐卫明

doi:DOI:10.13442/j.gnss.1008-9268.2019.05.001

雾定位及其应用研究

doi: DOI:10.13442/j.gnss.1008-9268.2019.05.001

1.
北京航空航天大学电子信息工程学院,北京 100083
2.
卫星导航与移动通信融合技术工信部重点实验室, 北京 100083
3.
武汉大学卫星导航定位技术研究中心,湖北武汉 430079
4.
北京航空航天大学前沿科学技术创新研究院,北京 100083

详细信息

作者简介:
施闯（1968—）,男，博士，北京航空航天大学电子信息工程学院教授，主要从事数据平差、GNSS与低轨卫星定轨以及实时精密定位等方面科研、教学等工作.

通讯作者:
施闯 E-mail：shichuang@buaa.edu.cn

计量
- 文章访问数: 1491
- HTML全文浏览量: 145
- PDF下载量: 974
- 被引次数: 0
出版历程
- 刊出日期: 2019-10-15

Fog positioning and its applications

1.
School of Electronic and Information Engineering, Beihang University, Beijing 100083,China
2.
Laboratory of Navigation and Communication Fusion Technology, Ministry of Industry and Information Technology, Beijing 100083,China
3.
GNSS Research Center, Wuhan University, Wuhan 430079,China
4.
Research Institute of Frontier Science, Beihang University, Beijing 100083,China

摘要

摘要: 全球卫星导航系统（GNSS）的发展促进了基于位置服务(LBS)的迅速普及,人们对高可靠、高可信、高精度定位、导航、授时（PNT）服务需求日益迫切．PNT是一个融合多类技术、包括多级系统的体系架构．围绕PNT服务体系优化,国内外学者相继提出了全源导航定位(All source positioning and navigation)、弹性PNT(Resilient PNT)、云定位(Cloud Positioning)等新的架构和技术体系．本文提出以具备通信、计算、存储、定位、感知等能力的异构定位资源为基础设施,通过智能管理与调度分布在不同地理位置的异构定位资源实现用户高可靠、高可信、高精度的PNT信息服务．并由此给出了雾定位(Fog Positioning)与泛源导航定位(Omnipresent Positioning and Navigation)的定义,指出雾定位的定义由分布式计算架构演化而来,强调构成PNT服务体系的架构;而泛源导航定位的概念是从定位技术的发展演化而来,强调利用可获取的泛在导航定位数据源进行协同融合处理,实现泛在定位的能力．在此基础上,通过与云定位比较,指出雾定位是云定位向用户端的延伸,是定位资源的泛在化实现,同时雾是一种动态的、弹性的云,因此雾定位是一种具备“弹性”性能的PNT架构．而泛在定位是PNT信息服务发展重要目标,雾定位给出了实现这一目标的潜在手段,即泛源导航定位．最后,结合城市环境、室内环境等复杂场景,研究了雾定位／泛源导航定位的基本服务模式．
- 雾定位 /
- 云定位 /
- 弹性PNT /
- 泛在定位 /
- 泛源导航定位
Abstract: With the development of GNSS, the LBS (Location Based Service) has been popularized rapidly. Meanwhile, people’s demand for PNT service with high reliability, high credibility and high precision is increasingly urgent. PNT is a system which integrates multi-technology and multilevel systems. Focusing on the optimization of PNT service, domestic and overseas scholars have put forward several new architectures and technical systems such as All Source Positioning and Navigation, Resilient PNT and Cloud Positioning. This study states, that with heterogeneous positioning resources which are capable in communication, calculation, storing, positioning and sensing as infrastructure construction, PNT service with high reliability, high credibility and high precision can be realized by intelligent management and scheduling of heterogeneous positioning resources distributed in different geolocations. Further, the definitions of Fog Positioning and Omnipresent Positioning and Navigation are given. It is argued that the definition of Fog Positioning is evolved from distributed computing architecture and emphasizes the architecture for PNT service. While the definition of Omnipresent Positioning and Navigation is evolved from the development of positioning technology and emphasizes the ability to realize omnipresent positioning by collaborative fusion processing of omnipresent positioning resources. On this basis, by comparing Fog Positioning with Cloud Positioning, this study points out that Fog Positioning is the extension of Cloud Positioning towards the user side and the omnipresent realization of positioning resources. Meanwhile, Fog Positioning is one kind of dynamic and elastic cloud, so Fog Positioning can be seen as a PNT architecture with the property of elasticity. Omnipresent positioning is an important target of PNT architecture, and Fog Positioning gives the potential means for this target, e.g., Omnipresent Positioning and Navigation. At last, this contribution analysis the basic service mode for Fog Positioning or Omnipresent Positioning and Navigation under the city environment and indoor environment.
- fog positioning /
- cloud positioning /
- resilient PNT /
- ubiquitous positioning /
- omnipresent positioning and navigation

HTML全文

参考文献(27)

[1]	WOODMAN O J, WOODMAN C O J. An introduction to inertial navigation［J］. Journal of Navigation, 1956, 9(3):249-259.
[2]	邓正隆. 惯性导航原理［M］. 哈尔滨：哈尔滨工业大学出版社, 1994.
[3]	王力. 影像／GNSS／INS 组合精密定位定姿方法研究［D］.武汉:武汉大学博士毕业论文,2015.
[4]	朱锋. GNSS／SINS／视觉多传感器融合的精密定位定姿方法与关键技术［D］.武汉:武汉大学博士毕业论文,2019. ［5 ] 黄显林, 姜肖楠, 卢鸿谦,等. 自主视觉导航方法综述［J］. 吉林大学学报(信息科学版), 2010, 28(2):158-165.
[5]	WOLCOTT R W, EUSTICE R M. Visual localization within LIDAR maps for automated urban driving［C］／／IEEE／RSJ International Conference on Intelligent Robots and Systems. 2014.
[6]	GROVES P D. The complexity problem in future multisensor navigation and positioning systems: A modular solution［J］. The Journal of Navigation, 2014, 67(2): 311-326.
[7]	GREJNER-BRZEZINSKA D A, TOTH C K, MOORE T,et al. Multisensor navigation systems: A remedy for GNSS vulnerabilities［J］. Proceedings of the IEEE, 2016,104(6): 1339-1353. http:／／doi.org／10-1109／JPROC.2016-2528538.
[8]	SCHWARZ K P, CHAPMAN M A, CANNON M W, et al. An integrated INS／GPS approach to the georeferencing of remotely sensed data［J］. Photogrammetric engineering and remote sensing, 1993, 59(11): 1667-1674.
[9]	EL-SHEIMY N. The development of VISAT: a mobile survey system for GIS applications［M］. Calgary, 1996.
[10]	BUCK T M, WILMOT J, COOK M J. A high G, MEMS based, deeply integrated, INS／GPS, guidance, navigation and control flight management unit［C］／／2006 IEEE／ION Position, Location, And Navigation Symposium. IEEE, 2006: 772-794.
[11]	QIN T, LI P L, SHEN S J. SHEN S. VINS-mono: [JP]A robust and versatile monocular visual-Inertial state Estimator［J］. IEEE Transactions on Robotics, 2017, PP(99):1-17.
[12]	徐兴柱, 赵然, 危志英, 等. 嵌入式微惯导／GPS／磁力计组合导航系统设计［J］. 战术导弹技术, 2012 (3): 111-114.
[13]	GEORGY J, NOURELDIN A, KORENBERG M J, [JP]et al. Low-cost three-dimensional navigation solution for RISS／GPS integration using mixture particle filter［J］. IEEE Transactions on Vehicular Technology, 2010, 59(2):599-615.
[14]	ZHANG L, XIONG Z, LAI J, et al. Research of optical flow aided MEMS navigation based on convex optimization and ROF denoising［J］. Optik, 2018, 158: 1575-1583.
[15]	FISCHER J, OCONNOR M., SCHUE C. A holistic approach to trusted, resilient PNT: GNSS, STL and eLoran.［P/OL］. https:／／www.orolia.com／sites／default／files／document-files／Holistic-Approach-to-Trusted-Resilient-PNT_0.pdf.
[16]	NARINS M.The benefits of alternative positioning, [JP]navigation, and timing (APNT) to aviation and other users: The need for robust radio navigation, inintegrated communications ［C］// Navigation and Surveilance Conference. Herndon, VA, USA:IEEE, 2012:1-37.
[17]	PARKINSON B. Assured PNT for our future: PTA [JP]actions necessary to reduce vulnerability and ensure availability ［C］// Proceedings of the 25th Anniversary GNSS History Special Supplement: GPS World Staff,2014.
[18]	BURKE J. DARPA positioning, navigation, and [JP]timing (PNT) technology and their impacts on GPS users［P/OL］.2018［2019-09-30］. https:／／www.gps. gov／governance／advisory／meetings／2019-06／burke.pdf.
[19]	HAMILTON B A. More resilient positioning, navigation and timing (PNT) through open architecture and analytics viewpoint. ［P/OL］. 2019［2019-09-30］.2019. https:／／www.govexec.com／media／more-resilient-positioning-navigation-and-timing-pnt-through-open-architecture-and-analytics_(1).pdf
[20]	杨元喜. 综合PNT体系及其关键技术［J］. 测绘学报,2016,45(5):505-510. DOI: 10.11947／j.AGCS.2016.20160127.
[21]	杨元喜.弹性PNT基本架构. 测绘学报［J］, 2018, 47(7)： 893-898. DOI: j.AGCS.2018.20180149.
[22]	施闯,章红平,辜声峰,等. 云定位技术及云定位服务平台［J］. 武汉大学学报(信息科学版), 2015, 40(8): 995-999.
[23]	施巍松, 孙辉, 曹杰, 等.边缘计算:万物互联时代新型计算模型［J］. 计算机研究与发展,2017, 54(5): 907-924.
[24]	BONOMI F, MILITO R, ZHU J, et al. Fog computing and its role in the internet of things［C］／／Proceedings of the first edition of the MCC Workshop on Mobile Cloud Computing. ACM, 2012: 13-16.
[25]	YI S, LI C, LI Q. A survey of fog computing: concepts, applications and issues［C］／／Proceedings of the 2015 Workshop on Mobile Big Data. ACM, 2015: 37-42.
[26]	刘经南. 泛在测绘与泛在定位的概念与发展［J］. 数字通信世界,2011(s1):28-30.
[27]	PETER T, OLIVER M. Springer handbook of global [JP]navigation satellite systems［M］. Springer, 2017.