综合定位、导航与授时(PNT)的核心是不过分依赖GNNS,采用一切可以应用的PNT信息源实施全空域目标定位、导航与授时服务。本文分析了综合PNT需求,论述了综合PNT的基本定义和基本概念,分析了综合PNT所涉及的信息源,论述了综合PNT关联的核心技术,包括多源PNT传感器集成技术、多源PNT的数据融合技术。强调指出,综合PNT体系的信息源必须是"基于不同物理原理的多源信息";综合PNT的运控系统应该基于云平台,实现用户志愿者共同测控;用户终端或传感器必须"深度集成、低功耗";PNT服务信息必须是"智能融合或自适应融合"。综合PNT系统应该在统一时空基准下,满足服务的可用性、精确性、可靠性、连续性和稳健性。
The core idea of comprehensive positioning, navigation and time (PNT) is the technique that uses all the available resources to provide PNT services in the whole area, including inside and outside door, air, space, under water and underground, which does not solely rely on the GNSS. The definition and basic concepts of the comprehensive PNT are presented. The possible signal sources are listed. The core technologies related to the comprehensive PNT are analyzed, including the integration of the multiple sensors and adaptive data fusion for multiple PNT signals. It is emphasized that the information of the comprehensive PNT should be from "multiple sources based on different physical principles", the control system should be operated by voluntary users based on cloud platform, the user terminals or sensors should be "deeply integrated" and the PNT information should be "adaptively fused" and serve mode might be based on cloud platform. The comprehensive PNT system should meet the robust availability, continuity, high accuracy and reliability with unified geodetic datum and time datum.
[1] Department of Transportation and Department of Defense of USA. National Positioning, Navigation, and Timing Architecture Implementation Plan[R].[S.l.]: Department of Transportation and Department of Defense of USA,2010.
[2] MCNEFF J. Changing the Game Changer-The Way Ahead for Military PNT[J]. Inside GNSS,2010, 5(8): 44-45.
[3] 李耐和, 张永红, 席欢. 美正在开发的PNT新技术及几点认识[J].卫星应用, 2015(12): 34-37. LI Naihe, ZHANG Yonghong, XI Huan. Some Cognition on the New PNT Technology under Designed by USA[J].Satellite Application, 2015(12): 34-37.
[4] PARKINSON B. Assured PNT for Our Future: PTA. Actions Necessary to Reduce Vulnerability and Ensure Availability[C]//The 25th Anniversary GNSS History Special Supplement.[S.l.]: GPS World staff 2014.
[5] PARKINSON B. A PAT Program and Specific Challenges to PNT, Presentation talk in ICG 10[R].Boulder:[s.n.], 2015.
[6] 杨元喜. 北斗卫星导航系统的进展、贡献与挑战[J].测绘学报, 2010, 39(1): 1-6. YANG Yuanxi.Progress, Contribution and Challenges of Compass/BeiDou Satellite Navigation System[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(1): 1-6.
[7] 杨元喜, 陆明泉, 韩春好. GNSS互操作若干问题[J].测绘学报, 2016, 45(3): 253-259.DOI: 10.11947/j.AGCS.2016.20150653. YANG Yuanxi, LU Mingquan,HAN Chunhao. Some Notes on Interoperability of GNSS[J].Acta Geodaetica et Cartographica Sinica, 2016, 45(3): 253-259. DOI: 10.11947/j.AGCS.2016.20150653.
[8] 吴德伟. 航空无线电导航系统[M].北京: 电子工业出版社, 2010. WU Dewei. Radio Navigation Systems for Aviation[M].Beijing: Publishing House of Electronic Industry, 2010.
[9] 吴富梅. GNSS/INS组合导航误差补偿与自适应滤波理论的拓展[D].郑州:信息工程大学, 2010. WU Fumei. Error Compensation and Extension of Adaptive Filtering Theory in GNSS/INS Integrated Navigation[D].Zhengzhou: Information Engineering University, 2010.
[10] 魏子卿, 刘光明, 吴富梅. 2000中国大地坐标系: 中国大陆速度场[J].测绘学报, 2011, 40(4): 403-410. WEI Ziqing, LIU Guangming,WU Fumei. China Geodetic Coordinate System 2000: Velocity Field in Mainland China[J].Acta Geodaetica et Cartographica Sinica, 2011, 40(4): 403-410.
[11] 杨元喜. 2000中国大地坐标系[J].科学通报, 2009, 54(16): 2271-2276. YANG Yuanxi.Chinese Geodetic Coordinate System 2000[J].Chinese Science Bulletin, 2009, 54(15): 2714-2721.
[12] HAN Chunhao, YANG Yuanxi,CAI Zhiwu. BeiDou Navigation Satellite System and Its Time Scales[J]. Metrologia, 2011, 48(4):S13.
[13] YANG Yuanxi, LI Jinlong, XU Junyi, et al. Generalised DOPs with Consideration of the Influence Function of Signal-in-space Errors[J].The Journal of Navigation, 2011, 64(S1):S3-S18.
[14] 李敏. 多模GNSS融合精密定轨理论及其应用研究[D].武汉:武汉大学, 2011. LI Min. Research on Multi-GNSS Precise Orbit Determination Theory and Application[D]. Wuhan: Wuhan University, 2011.
[15] 吴富梅, 杨元喜. 基于高阶AR模型的陀螺随机漂移模型[J].测绘学报, 2007, 36(4): 389-394. WU Fumei,YANG Yuanxi.Gyroscope Random Drift Model Based on the Higher-order AR Model[J].Acta Geodaetica et Cartographica Sinica, 2007, 36(4): 389-394.
[16] 杨元喜, 徐天河. 基于移动开窗法协方差估计和方差分量估计的自适应滤波[J].武汉大学学报(信息科学版), 2003, 28(6):714-718. YANG Yuanxi,XU Tianhe. An Adaptive Kalman Filter Combining Variance Component Estimation with Covariance Matrix Estimation Based on Moving Window[J].Geomatics and Information Science of Wuhan University, 2003, 28(6): 714-718.
[17] YANG Yuanxi,XU Tianhe. An Adaptive Kalman Filter Based on Sage Windowing Weights and Variance Components[J].The Journal of Navigation, 2003, 56(2):231-240.
[18] 杨元喜, 高为广. 基于多传感器观测信息抗差估计的自适应融合导航[J].武汉大学学报(信息科学版), 2004, 29(10): 885-888. YANG Yuanxi,GAO Weiguang. Integrated Navigation Based on Robust Estimation Outputs of Multi-sensor Measurements and Adaptive Weights of Dynamic Model Information[J].Geomatics and Information Science of Wuhan University,2004, 29(10): 885-888.
[19] CARLSON NA. Federated Filter for Fault-Tolerant Integrated Navigation Systems[C]//Proceedings of IEEE Position Location and Navigation Symposium.Orlando: IEEE, 1988: 110-119.
[20] CARLSON NA. Federated Filter for Computer-Efficient, Near-Optimal GPS Integration[C]//Proceedings of IEEE Position Location and Navigation Symposium.Atlanta: IEEE, 1996: 306-314.
[21] YANG Yuanxi,CUI Xianqiang,GAO Weiguang. Adaptive Integrated Navigation for Multi-sensor Adjustment Outputs[J]. The Journal of Navigation, 2004, 57(2): 287-285.
[22] 杨元喜. 多源传感器动、静态滤波融合导航[J].武汉大学学报(信息科学版), 2003, 28(4): 386-388, 396. YANG Yuanxi.Kinematic and Static Filtering for Multi-Sensor Navigation Systems[J].Geomatics and Information Science of Wuhan University, 2003, 28(4): 386-388, 396.
[23] 高为广, 杨元喜, 张双成. 基于当前加速度模型的抗差自适应Kalman滤波[J].测绘学报, 2006, 35(1): 15-18, 29. GAO Weiguang, YANG Yuanxi, ZHANG Shuangcheng.Adaptive Robust Kalman Filtering Based on the Current Statistical Model[J].Acta Geodaetica et Cartographica Sinica, 2006, 35(1): 15-18, 29.
[24] 杨元喜, 高为广. 基于多传感器观测信息抗差估计的自适应融合导航[J].武汉大学学报(信息科学版), 2004, 29(10): 885-888. YANG Yuanxi, GAO Weiguang.Integrated Navigation Based on Robust Estimation Outputs of Multi-sensor Measurements and Adaptive Weights of Dynamic Model Information[J].Geomatics and Information Science of Wuhan University, 2004, 29(10): 885-888.
[25] YANG Y, HE H, XU G. Adaptively Robust Filtering for Kinematic Geodetic Positioning[J].Journal of Geodesy, 2001, 75(2-3): 109-116.
[26] YANG Yuanxi, GAO Weiguang. An Optimal Adaptive Kalman Filter[J].Journal of Geodesy, 2006, 80(4): 177-183.