张克非

基本信息

姓名:张克非

学位:博士

职称:教授

行政职务:资源环境技术研究院院长,空间信息智能感知与创新/太空采矿中心主任,北星空间信息技术研究院院长

研究方向:大地测量、GNSS PNT/极端天气与气候变化/遥感、空间资源开发与利用、城市地下大空间应急安全、空间态势感知、大地测量大数据与人工智能

通讯地址:江苏省徐州市大学路1号中国矿业大学环境与测绘学院,邮政编码:221116

办公地址:文昌校区,综合楼1011B

Email: profkzhang@cumt.edu.cn

个人简介

张克非,中国矿业大学国家特聘教授,校学术委员会常委,博士生导师,资源环境技术研究院院长,空间信息智能感知与创新/太空采矿中心主任,北星空间信息技术研究院院长,国际大地测量协会会士、中国委员。先后担任全球华人定位导航协会主席,副主席,顾问委员会委员,国际大地测量协会专题研究组主席,担任百余次的国际学术会议总会/分会主席、中国科学院海外评审专家,基金委重点项目/国际合作/面上和青年基金等评审专家,科学院青年科学家奖评审专家以及国际上多国基金评委和职称评定专家。

本科、硕士毕业于武汉大学(原武汉测绘科技大学)。1997年博士毕业于澳大利亚科廷大学,1997-1999于英国诺丁汉大学从事博士后研究工作,1999年获得澳大利亚皇家墨尔本理工大学终身教职,并于2009年破格为正教授,先后入选国家高端人才计划和获得江苏省“双创团队”领军人才、“双创个人”人才、紫金山英才(江北明珠计划、外国人才)等称号。主持国家自然科学基金重点项目和面上项目各一项、教育部空间信息科学与技术创新中心(111)引智基地项目、中国矿业大学双一流建设“太空采矿”等。

专注于卫星导航定位、大地测量、空间信息科学与技术、环境与大气科学等领域的理论研究和应用开发工作,系统地建立了 GNSS 大气遥感应用理论体系。成立了南半球第一个北斗、QZSSGalileoGPS 多卫星国际观测中心。在 GNSS 创新应用、矿山灾害监测、大气探测、多传感器智能集成、空间态势感知等方面取得了丰硕的成果并产生了巨大的社会和经济效益。团队研发的基于GPS的多传感器奥林匹克体育竞技智能跟踪系统,是国际上最早、系统地研究基于卫星导航技术的小型化智能型人员跟踪系统,被誉为澳大利亚著名优秀教练员和金牌运动员的国际竞技比赛的“神秘武器”。在国际上率先将大地测量技术运用到GNSS大气探测、空间追踪和太空资源探测与利用等领域的拓荒者。

先后指导了40多名博士后研究人员,指导了近60名博士和硕士研究生。和领导的团队获得了40多项国际重要奖项,研究成果也被国际主流媒体采访与报道。获批专利40余项、在本专业国际一流期刊和国际会议发表论文450余篇(其中180多篇 SCI 论文)和100多次特邀报告和主旨演讲,多篇论文被高引用,引用频次为 6000 多次(自 2010 年以来仅在 RMIT 论文库网站下载量为 6 万多次)。在大地测量和GNSS定位方面享有国际盛誉。论文期刊包括:《Remote Sensing of Environment,影响因子IF=13.85,Progress in Aerospace Sciences IF=8.94,IEEE Transactions on Geoscience and Remote SensingIF=8.12,The Astronomical Journal IF=5.497,Geophysical Research Letters, IF=5.57,Journal of Geophysical Research,Journal of Geodesy,GPS Solutions》,《IEEE,Atmospheric Measurement Techniques》等。

期刊论文

学术论文(近5, IF=影响因子,Q=JCR/科学院分区)

[1]   Shi SS and Zhang KF etc (2022) An investigation of a new artificial neural network-based TEC model using ground-based GPS and COSMIC-2 measurements over low latitudes, Advances in Space Research, S0273-1177(22)00628-7. [SCI, IF=4.6, Q1]

[2]   Shi SS and Zhang KF, Wu SQ, Shi JQ, Hu AD, Wu HJ and Li Y etc (2022) An Investigation of Ionospheric TEC Prediction Maps over China Using Bidirectional Long Short-Term Memory Method, Space Weather, http://dx.doi.org/10.1029/2022SW003103 [SCI, IF=2.4, Q1]

[3]   He QM, Zhang KF, Wu SQ, Lian DJ, Li L, Shen Z, Wan MF, Li LJ, Wang R, Fu EJ, Gao BQ (2022) An investigation of atmospheric temperature and pressure using an improved spatio-temporal Kriging model for sensing GNSS-derived precipitable water vapor, Spatial Statistics, https://doi.org/10.1016/j.spasta.2022.100664. [SCI, IF=2.04, Q4]

[4]   Ban W, Zhang K, Yu K, Zheng N. and Chen S (2022) Detection of Red Tide Over Sea Surface Using GNSS-R Spaceborne Observations, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-11. [SCI, IF=5.187, Q1]

[5]   Bian C, Shi, H, Wu S, Zhang K, Wei M, Zhao Y, Sun Y, Zhuang H, Zhang X and Chen S (2022) Prediction of Field-Scale Wheat Yield Using Machine Learning Method and Multi-Spectral UAV Data. Remote Sens. 2022, 14, 1474 [SCI, IF=5.187, Q1]

[6]   Feng J, Sun Y, Zhang K, Zhao Y, Ren Y, Chen Y, Zhuang H and Chen S (2022) Autonomous Detection of Spodoptera frugiperda by Feeding Symptoms Directly from UAV RGB Imagery. Applied Science. 2022, 12, 2592. https://doi.org/10.3390/app12052592 [SCI IF=2.679, Q2]

[7]   Li W, Zhao D, He C, Hancock CM, Shen Y and Zhang K (2022). Spatial-temporal behaviors of large-scale ionospheric perturbations during severe geomagnetic storms on September 7-8 2017 using the GNSS, SWARM and TIE-GCM techniques. Journal of Geophysical Research (Space Physics), 127. [SCI, IF= 5.30Q1].

[8]   Li W, Zhao DS, He CY, Yi S, Hancock CM and Zhang K (2022) Strong Storm-effect behaviors of topside and bottom-side ionosphere under 1low solar activity: Case study in the geomagnetic storm during 25-27 2August 2018, Space Weather [SCI, IF=2.4, Q1]

[9]   Liu JX, Zhang KF, Wu SQ, Shi HT, Zhao YD, Sun YQ, Zhuang HF and Fu EJ (2022) An Investigation of a Multidimensional CNN Combined with an Attention Mechanism Model to Resolve Small-Sample Problems in Hyperspectral Image Classification, Remote Sens. 2022, 14, 785. [SCI, IF=5.187, Q1]

[10]  Tong LG, Zhang K, Li H, Wang X, Ding N, Shi J, Zhu D and Wu S (2022) An Investigation of Near Real-Time Water Vapor Tomography Modeling Using Multi-Source Data, Atmosphere, 2022, 13, https://doi.org/10.3390/atmos13050752 [SCI, IF =2.68].

[11]  Zhang KF, 李浩博,王晓明,朱丹彤,何琦敏,李龙江,胡安东,郑南山,李怀展 (2022) Recent Progresses and Future Prospectives of Ground-based GNSS Water Vapor Sounding (地基GNSS大气水汽探测遥感研究进展和展望), Acta Geodaetica et Cartographica Sinica (测绘学报), invited paper.

[12]  Zhang XW, Zhang KF, Sun YQ, Zhao YD, Zhuang HF, Ban W, Chen Y, Fu EJ, Chen S, Liu JX, Hao YM (2022) Combining Spectral and Texture Features of UAV-based Multispectral Images for Maize Leaf Area Index Estimation, Remote Sens.14(2), 331; [SCI, IF=5.187, Q1]

[13]  Zhao DS, Li W, Li CD, Tang X, Wang QX, Hancock CM, Roberts GW, and Zhang K (2021) A Phase Scintillation Index Extracted from Each Carrier 1 of 1 Hz GNSS Measurements and Validated Statistically in the Arctic Region Space Weather (accepted April 2022). [SCI, IF=2.4, Q1]

[14]  Zhuang HF, Hao M, Deng KZ, Zhang KF, Wang XS and Yao GB (2022) Change Detection in SAR Images via Ratio-Based Gaussian Kernel and Nonlocal Theory, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022 5210215. [SCI, IF=5.187, Q1]

[15] Duan Y, Li H, Wu, S and Zhang K. (2021) INS Error Estimation Based on an ANFIS and Its Application in Complex and Covert Surroundings. ISPRS Int. J. Geo-Inf. 2021, 10, 388. [SCI, IF=2.127].

[16]  Zhang K (2021) When science fiction comes into reality current status and the future of space mining (当科幻映入现实 浅谈太空找矿的现状与未来),中国测绘 (China Surveying and Mapping), Issue 210, pp-27, December (ISSN1005-6831).

[17]  Li H, Wang X, Zhang K, Wu S, Xu Y, Jiang C, Zhang J, Qiu C and Li L, (2021) A New Cumulative Anomaly-based Model for the Detection of Heavy Precipitation Using GNSS-derived Tropospheric Products, IEEE Transactions on Geoscience and Remote Sensing. 10.1109/TGRS.2021.3137014 [SCI, Q1 TOP, IF=5.6)]

[18]  Li H, Choy S, Jiang C, Wu S, Zhang J, Qiu C, Zhou K, Li L, Fu E and Zhang K (2021) Detecting Heavy Rainfall Using Anomaly-based Percentile Thresholds of Predictors Derived from GNSS-PWV, Atmospheric Research [SCI, Q1, IF=5.369]

[19]  Li H, Wang W, Wu S, Zhang K, Chen X, Zhang J, Qiu C, Zhang S and Li L (2021) An Improved Model for Detecting Heavy Precipitation Using GNSS-derived Zenith Total Delay Measurements. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 5392-5405, [SCI, Q2, IF=3.784]

[20]  Li H.; Xiaoming Wang, Suqin Wu, Kefei Zhang, Erjiang Fu, Ying Xu, Cong Qiu, Jinglei Zhang, Li Li, A New Method for Determining an Optimal Diurnal Threshold of GNSS Precipitable Water Vapor for Precipitation Forecasting. Remote Sensing, 13(7): 1390, [SCI, Q1, IF=4.848]

[21]  Li L, Wu S, Zhang K, Wang X, Li W, Shen Z, Zhu D, He Q, and Wan M (2021) A New ZHD Model for Real-Time Retrievals of GNSS-PWV, AMT 10.5194/amt-2021-113. [SCI, IF=3.9, Q2]

[22]  刘金香,班伟,陈宇,孙亚琴,庄会富,富尔江,张克非 (2021) Multi-Dimensional CNN Fused Algorithm for Hyperspectral Remote Sensing Image Classification (融合多维度CNN的高光谱遥感图像分类算法), Chinese Journal of Lasers (中国激光), 48(16), 153-163.

[23]  Li W, Zhao D, He C, Shen Y, Hu A. and Zhang K. (2021). Application of a multilayer artificial neural network in a 3D global electron density model using the longterm observations of COSMIC, Fengyun3C, and Digisonde. Space Weather, 19, e2020SW002605, [SCI, IF = 3.579, Q1].

[24]  Li W, He C, Hu A, Zhao D, She Y, Zhang K (2021) A new method for improving the performance of an ionospheric model developed by multi-instrument measurements based on artificial neural network, Advances in Space Research, Vol 67, Iss 1, Pages 20-34.

[25]  Shen Z, Zhang K, Zhu D, He Q, Wan M, Li L and Wu S (2021) Assessment of the Homogeneity of Long-Term Multi-Mission RO-Based Temperature Climatologies. Remote Sens. 13, 2278. [SCI, IF=5.187, Q1]

[26]  Shen Z, Zhang K, He Q, Wan M, Li L and Wu S (2021) Quest over the Sampling Error of COSMIC Radio Occultation Temperature Climatologies, Journal of Atmospheric and Oceanic Technology, [SCI, IF = 1.952, Q2].

[27]  Shi S, Li W, Zhang K, Wu S, Shi J, Song F and Sun P (2021) Validation of COSMIC-2-Derived Ionospheric Peak Parameters Using Measurements of Ionosondes. Remote Sens. 2021, 13, 4238. [SCI, IF=5.187, Q1]

[28]  Shi J, Zhang K, Wu S, Shi S and Shen Z (2021) Investigation of the Atmospheric Boundary Layer Height Using Radio Occultation: A Case Study during Twelve Super Typhoons over the Northwest Pacific. Atmosphere 2021, 12, 1457. https://doi.org/10.3390/atmos12111457. [SCI, IF=2.955]

[29]  Sun P, Zhang K, Wu S, Wan M and Lin Y (2021) Retrieving Precipitable Water Vapor from Real-Time Precise Point Positioning Using VMF1/VMF3 Forecasting Products, Remote Sens. 2021, 13(16), 3245; https://doi.org/10.3390/rs13163245 [SCI, Q1, IF=4.848]

[30] Sun P, Zhang K, Wu S, Wang R, and Wan M (2021). An investigation into real-time GPS/Glonass single-frequency precise point positioning and its atmospheric mitigation strategies. Measurement Science and Technology, 32(11), 115018-. [SCI, Q2, IF=2.398]

[31]  Chen S, Zhang KF, Zhao YD, Sun YQ, Ban W, Chen Y, Zhuang HF, Zhang XW, Liu JX, Yang T (2021) An Approach for Rice Bacterial Leaf Streak Disease Segmentation and Disease Severity Estimation, Agriculture, 11(5), 420. [SCI, IF=2.925, Q2]

[32]  Zhu DT, Zhang KF, Yang L, Wu SQ and Li, L. (2021) Evaluation and Calibration of MODIS Near-Infrared Precipitable Water Vapor over China Using GNSS Observations and ERA-5 Reanalysis Dataset. Remote Sens. 2021, 13, 2761. [SCI, Q1, IF=4.848]

[33]  Zhu DT; Zhang KF, Shen Z, Wu S, Liu Z, Tong L (2021) A new adaptive absolute method for homogenizing GNSS-derived precipitable water vapor time series, Earth and Space Science, 10.1029/2021EA001716. [SCI, IF=2.9/Q4]

[34]  Kodikara T, Zhang K, Pedatella NM and Borries C (2020) The Impact of Solar Activity on Forecasting the Upper 1Atmosphere via Assimilation of Electron Density Data, Space Weather, 19, e2020SW00266, [SCI, IF=3.579]

[35]  Li H, Wang X, Wu S, Zhang K, Chen X, Qiu C, Zhang S, Zhang J, Xie M and Li L (2020) Development of an Improved Model for Prediction of Short-term Heavy Precipitation Based on GNSS-derived PWV, Remote Sensing, 12(24):4101. [SCI, IF=5.187, Q1]

[36]  赵东升;李旺;李宸栋;唐旭;张克非 (2020) 低频 GNSS 电离层相位闪烁因子构建新方法及在北极区域的验证, 测绘学报, Acta Geodaetica et Cartographica Sinica, 2021, 50(3): 368-383. (Zhao D , Li W, Li C , et al. Extracting an ionospheric phase scintillation index based on 1 Hz GNSS observations and its verification in the Arctic region[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(3):368-383.)

[37]  Ding N, Yan X, Zhang S, Wu S, Wang X, Zhan Y, Wang Y, Liu X, Zhang W, Holden L and Zhang K (2020) Node-Based Optimization of GNSS Tomography with a Minimum Bounding Box Algorithm, Remote Sensing, 12, 2744; [SCI, IF = 4.061, Q1].

[38]  Sun P, Wu S, Zhang K, Wan M, and Wang R (2020) A new global grid-based weighted mean temperature model considering vertical nonlinear variation, Atmospheric Measurement Techniques (AMT), 14, 2529–2542. [SCI, IF=3.707].

[39]  Ding N, Yan X, Zhang S, Wu S, Wang X, Zhang Y, Wang Y, Liu X, Zhang W, Holden L and Zhang K (2020) Node-Based Optimization of GNSS Tomography with a Minimum Bounding Box Algorithm. Remote Sens. 2020, 12, 2744. https://doi.org/10.3390/rs12172744

[40]  Li W, Zhao D, Shen Y and Zhang K (2020) Modeling Australian TEC Maps Using Long-Term Observations of Australian Regional GPS Network by Artificial Neural Network-Aided Spherical Cap Harmonic Analysis Approach, Remote Sensing, 12, 3851, [SCI, IF = 4.061, Q1].

[41]  Li W, He C, Hu A, Zhao D, Shen Y, Zhang K (2020) A new method for improving the performance of an ionospheric model developed by multi-instrument measurements based on artificial neural network, Advances in Space Research. https://doi.org/10.1016/j.asr.2020.07.032[SCI, 5yrs IF=2.177, Q2].

[42]  Li W, Zhao D, He C, Hu A and Zhang K (2020) Advanced Machine Learning Optimized by The Genetic Algorithm in Ionospheric Models Using Long-Term Multi-Instrument Observations, Remote Sensing 12(5), 866; https://doi.org/10.3390/rs12050866, [SCI, 5Yrs IF 4.740, Q1]

[43]  Xu F, Li Z, Zhang K, Wang N, Wu S, Hu A, Holden L (2020) An Investigation of Optimal Machine Learning Methods for the Prediction of ROTI[J]. J of Geodesy and Geoinformation Science, 2020, 3(2): 1-15.

[44]  Zhang K, Li H, Deng K, Li C, Wang Q, Liu X, Xie Y, Duan Y and Yang Y (2020) Preliminary investigation of space mining – current status, opportunities and challenges, J of China University of Mining and Technology, 50 (5): 840-851.

[45]  Wei J, Li Y, Zhang K, Liao M, Bai W, Liu C, Liu Y, and Wang X (2020) An evaluation of Fengyun-3C radio occultation atmospheric profiles over 2015-2018, Remote Sensing, 12, 2116; [SCI, 5Yrs IF 4.740, Q1]

[46]  He Q, Zhang K, Wu S, Shen Z, Wan M and Li L (2020) GNSS-based Precipitable Water Vapor and ERA5 Datasets for the Monitoring of Tropical Cyclones, IEEE Access (accepted, 18/04/2020), [SCI, IF=4.098, Q1].

[47]  Yu J, Wang W, Holden L, Liu Z, Wu L, Zhang S and Zhang K (2019) Enhancing the Quality of Tomographic Image by Means of Image Reconstruction Based on Hybrid Grids, Advances in Space Research, Volume 66, Issue 3, Pages 591-603. [SCI, 5yrs IF=1.746, Q2].

[48]  Hu A, Carter B, Currie J, Norman R, Wu S and Zhang K (2020) A Deep Neural Network Model of Global Topside Electron Temperature Modeling Using Incoherent Scatter Radars and Its Application to GPS Radio Occultation, Journal of Geophysical Research: Space Physics. [SCI, IF=4.456, Q1].

[49]  Qin K, Xu H, Dong H, Xu J; Xue Y, Loyolab D, Zhou X, Zhang K, Li D and Yuan L (2020) Satellite-based estimation of surface NO2 Concentrations over Eastern China: A Comparison of POMINO and OMNO2d Data, Atmospheric Environment, 224, 117322. [SCI, 5yr IF = 4.459, Q1]

[50]  He Q, Zhang K, Wu S, Zhao Q, Wang X, Shen Z, Wan M, Li L and Liu X (2019) Real-Time GNSS-derived PWV for Typhoon Characterizations: A Case Study for Super Typhoon Mangkhut in Hong Kong. Remote Sensing, 2020, 12, 104. [SCI, IF 4.740, Q1].

[51]  Cai H, Gehly S, Yang Y, Reza Hoseinnezhad, Norman R and Zhang K (2019) Multisensor Tasking Using Analytical Rényi Divergence in Labeled Multi-Bernoulli Filtering, Journal of Guidance, Control, and Dynamics, 42(9):2078-85 [SCI, IF = 4.061, Q1].

[52]  He CY, Yang Y., Carter B, Zhang K, Hu A, Li W, Florent Deleflie, Norman R and Wu S (2019) Impact of thermospheric mass density on the orbit prediction of LEO satellites, Space Weather, 18, DOI:10.1029/2019SW002336, [SCI, IF = 3.9, Q2]. (selected as a featured article for EOS).

[53]  Cai H, Yang Y, Gehly S, Zhang K (2019) Modeling birth for the labeled multi-Bernoulli filter using a boundary value approach, Journal of Guidance, Control, and Dynamics, 43(3):1-8 [SCI, IF = 4.061, Q1].

[54]  Li ZS, Wang NB, Wang L, Liu A, Yuan H and Zhang K (2019) Regional ionospheric TEC modeling based on a two-layer spherical harmonic approximation for real-time single-frequency PPP, J of Geodesy, Volume 93, Issue 9, pp 1659–1671. [SCI, IF = 4.528, Q1].

[55]  Le Marshall J, Norman R, Howard D, Rennie S, Moore M, Kaplon J, Xiao Y, Zhang K, Wang C, Cate A, Lehmann P, Wang X, Steinle P, Tingwell C, Le T, Rohm W and Ren D (2019) Using GNSS Data for Real-time Moisture Analysis and Forecasting over the Australian Region I. The System, Journal of Southern Hemisphere Earth Systems Science, DOI: 10.22499/3.6901.009. [SCI, IF=1.6, Q3]

[56]  Wang Q., Hu Chao, Zhang Kefei (2019) A BDS-2/BDS-3 integrated method for ultra-rapid orbit determination with the aid of precise satellite clock offsets, Remote Sensing, 11(15), 1758. [SCI, IF 4.740, Q1]

[57]  Chen Yu, Kun Tan, Shiyong Yan, Kefei Zhang, Hairong Zhang, Xiaoyang Liu, Huaizhan Li, Yaqin Sun (2019) Monitoring high- precision land surface displacement over Xuzhou, Remote Sensing, 11(12):1494 [SCI, 5Yrs IF 4.740, Q1]

[58] Hu A, Carter BA, Currie J L, Norman R, Wu S, Wang X, and Zhang K(2019). Modeling of topside ionospheric vertical scale height based on ionospheric radio occultation measurements. Journal of Geophysical Research: Space Physics, 124, 4926–4942. [SCI, IF=4.456, Q1].

[59]  孟昊霆, 张克非, 杨震, 刘晓阳 (2019) GPT2/GPT2w+Saastamoinen模型ZTD估计在亚洲地区精度分析, 测绘科技 (Science of Surveying and Mapping).

[60]  Yandong Gao, Shubi Zhang, TaoLi, Shijin Li, Qianfu Chen and Pengfei Meng, Kefei Zhang (2019) Frequency domain filtering SAR interferometric phase noise using the amended matrix pencil model, Computer Science & Engineering, Vol 119 No 2. pp.349-363 [SCI, IF=1.35, Q2]

[61]  Zhao Qingzhi, Kefei Zhang, Yibin Yao and Xin Li (2019) A new troposphere tomography algorithm with a truncation factor model (TFM) for GNSS networks, GPS Solutions, 23-64, 10.1007/2Fs10291-019-0855-x. [SCI, IF = 4.517, Q1]

[62]  Chen Liu, Nanshan Zheng, Kefei Zhang and Junyu Liu (2019) A New Method for Refining the GNSS-Derived Precipitable Water Vapor Map, Sensors, 19, 698; doi:10.3390/s19030698. [SCI, 5yrs IF= 2.475, Q2].

[63]  Hu A., Li Z., Carter B., Wu S., Wang X., Norman R., Zhang K (2019) Helmert-VCE aided Fast-WTLS Approach for Global Ionospheric VTEC Modelling Using Data from GNSS, Satellite Altimetry and Radio Occultation, Journal of Geodesy, Vol 93, Issue 6, pp 877888, [SCI, IF = 4.633, Q1]

[64]  Liu Z., Zhu D., Yu H. and Zhang K. (2019) Least-square variance-covariance component estimation method based on the equivalent conditional adjustment model, Acta Geodaetica et Cartographica Sinica, 等价条件平差模型的方差协方差分量最小二乘估计方法, Journal of Geodesy and Geoinformation Science (测绘学报), Vol.48, No.9, pp1087-1095.

[65]  Wang Q., Zhang K.,Wu S.,Zou Y.,Hu C. (2019) A method for identification of optimal minimum number of multi-GNSS tracking stations for ultra-rapid orbit and ERP determination, Advances in Space Research, Vol 63, Iss 9, Pp 2877-2888 https://doi.org/10.1016/j.asr.2017.12.006 [SCI, 5yr IF = 1.46, Q2].

[66]  Yu K., Wen K., Li Y., Zhang S. and Zhang K. (2019) A Novel NLOS Mitigation Algorithm for UWB Localization in Harsh Indoor Environments, IEEE Transactions On Vehicular Technology, vol 68, No. 1, Pp. 686-699 [SCI, 5yrs IF= 4.432, Q1].

[67]  Zhao Q.Z., Zhang K., and Yao W. (2019) Influence of station density and multi-constellation GNSS observations on troposphere tomography, Annales Geophysicae, 37(1), 15-24, [SCI, 5yrs IF= 1.88, Q3].

[68]  Wenzhi Fan, Kai Qin, Jian Xu, Limei Yuan, Ding Li, Zi Jin, Kefei Zhang (2019) Aerosol vertical distribution and sources estimation site of the Yangtze River Delta region of China, Atmospheric Research, Volume 217, Pp 128-136. [SCI, 5yrs IF= 3.817, Q1]

[69]  Cai H., Yang Y., Gehly S., Wu S., Zhang K. (2018) Improved tracklet association for space objects using short-arc optical measurements, Acta Astronautica, 151:836-847 [SCI, IF=2.227, Q1].

[70]  Carter BA, Tulasi Ram S, Endawoke Yizengaw, Rezy Pradipta, John Retterer, Robert Norman,Julie Currie, Keith Groves, Ronald Caton, Michael Terkildsen, Tatsuhiro Yokoyama and Kefei Zhang (2018) Unseasonal development of post-sunset F-region irregularities over Southeast Asia on28 July 2014: 1. Forcing from above?, Progress in Earth and Planetary Science, 5:10, pp1-12. [SCI, 2 yrs IF=2.481, Q1]

[71]  Chen Y., Zhang K., Tan K., Feng X. and Li H. (2018) Long-term subsidence in lava fields (emplaced between 1998 and 2007) at Piton de la Fournaise volcano measured by InSAR: Characterization and implication for interpretation of the Eastern Flank motion, Remote Sensing, 10 (4), 597 [SCI, IF = 3.244, Q2].

[72]  Ding N., Zhang SB, Wu SQ, Wang XM, Zhang K. (2018) Adaptive node parameterization for dynamic determination of boundaries and nodes of GNSS tomographic models, J. Geophys. Res, Atmospheres, 123, 1990–2003. [SCI, IF=3.380, Q1]

[73]  Ding N., Zhang S., Wu S., Wang X., Kealy A., Zhang K. (2018) A new approach for GNSS tomography from a few GNSS stations, Atmospheric Measurement Techniques, 11, 3511-3522, [SCI, 5yr IF = 3.650, Q1].

[74]  He CY, Yang Y, Carter B, Wu S, Cai H, Deleiec F, Zhang K (2018) Review and comparison of thermospheric mass density models, Progress in Aerospace Sciences, 103:31-51 [SCI, 5yr IF = 6.054, Q1].

[75]  Hu, A. Wu, S. Wang, X. Wang, Y. Norman, R. He, C. Cai, H. and Zhang, K. (2018), ‘Improvement of reflection detection success rate of GNSS RO measurements using artificial neural network’, in IEEE Transactions on Geoscience and Remote Sensing, IEEE, United States, vol. 56, no. 2, pp. 760- 769 [SCI, IF= 4.662, Q1].

[76]  Hu A. and Zhang K (2018) Using Bidirectional Long Short-Term Memory Method for Ionospheric hmF2 Forecasting from Ionosonde Measurements in Australian Region, Remote Sensing, 10(10), 1658; [SCI, 5Yrs IF 3.952]. [Q1]

[77]  Kodikara T., Carter B., Norman R. and Zhang K (2018) Numerical Investigation of the Density-Temperature Synchrony in the Thermosphere, Journal of Geophysical Research, 24(1), 693-699 [SCI, IF=3.380, Q1].

[78]  Kodikara T., Carter B. and Zhang K. (2018) The first comparison between Swarm-C accelerometer-derived thermospheric densities and physical and empirical model estimates, Journal of Geophysical Research-Space Physics, 123, 5068–5086. [SCI, IF=4.456, Q1].

[79]  Li L, Wu S, Wang X, Tian Y, He C, and Zhang K (2018) Modelling of weighted-mean temperature using regional radiosonde observations in Hunan China, Terr. Atmos. Ocean. Sci.,Vol.29, No.2, 187-199 [SCI, IF=0.752, Q2].

[80]  Li W., Yue J., Guo J., Yang Y., Zou B., Shen Y., Zhang K. (2018) Statistical seismo-ionospheric precursors of M7.0+ earthquakes in Circum-Pacific seismic belt by GPS TEC measurements, Advances in Space Research, 61:1206–1219. [SCI, 5yr IF = 1.46, Q2].

[81]  Li W., Yue J., Wu S., Yang Y., Li Z., Bi J. and Zhang K. (2018) Ionospheric responses to typhoons in Australia during 2005-2014 using GNSS and FORMOSAT-3/COSMIC measurements, GPS Solutions, 22: 61. Pp.1-11 [SCI, IF = 4.061, Q1]

[82]  Li W., Yue J., Yang Y., Hu A., He C., Zhang K. (2018) Ionospheric and Thermospheric Responses to the Recent Strong Solar Flares on 6 September 2017, J. of Geophysical Research, 123,8865-8883 [SCI, IF=4.456, Q1].

[83]  Liu, C., Kirchengast, G., Sun, Y., Zhang, K., Norman, R., Schwaerz, M., Bai, W., Du, Q., and Li, Y. (2018) Analysis of ionospheric structure influences on residual ionospheric errors in GNSS radio occultation bending angles based on ray tracing simulations, Atmospheric Measurement Techniques, 11, 2427-2440 [SCI, 5yr IF = 3.650, Q1].

[84]  Norman R., Carter B., Healy S., Culverwell I., von Engeln A., Le Marshall J., Younger J., Cate A. and Zhang K. (2018) Ionospheric Regions Producing Anomalous GNSS Radio Occultation Results, IEEE Transactions on Geoscience and Remote Sensing (TGRS), Vol.56, No.12, PP7350-7358 [SCI, IF= 4.662, Q1].

[85]  Qin K.; Guo J.; Zou J.; Lu M.; Bilal M.; Zhang K.; Ma F.; Zhang Y. (2018) Estimating PM1 concentrations from MODIS over Yangtze River Delta of China during 2014-2017, Atmospheric Environment, 195:149-158 [SCI, 5yrs IF 4.042, Q1]

[86]  Qin K., Wang L., Xu J., Husi L., Zhang K., Li D., Zou J., Fan W. (2018) Haze optical properties from long-term ground-based remote sensing over Beijing and Xuzhou, China, Remote Sensing, 10, 518; pp.1-17 [SCI, 5Yrs IF 3.952, Q1].

[87]  Wang X., Zhang K., Wu S., Li Z., Cheng Y., Li L. and Yuan H. (2018) The correlation between GNSS-derived precipitable water vapor and sea surface temperature and its responses to El Niño–Southern Oscillation, Remote Sensing of Environment, Vol 216, Pp.1–12 [SCI, 5yrs IF=7.737, Q1].

[88]  Hu Andong, Suqin Wu, Xiaoming Wang, Yan Wang, Robert Norman, Changyong He, Han Cai, Kefei Zhang (2017) Improvement of reflection detection success rate of GNSS RO measurements using artificial neural network, IEEE TGARS, 56(2): 760-769. [SCI, IF=4.662, Q1].

[89]  Wang Li, Jianping Yue, Yang, Zhen Li, Jinyun Guo, Yi Pan, Kefei Zhang (2017) Analysis of ionospheric disturbances associated with powerful cyclones in East Asia and North America, Journal of Atmospheric and Solar-Terrestrial Physics,161 (2017) 43–54.[SCI, 5yr IF = 1.46, Q1].

[90]  Wang, X., Zhang, K., Wu, S., He, C., Cheng, Y., and Li, X. (2017) Determination of zenith hydrostatic delay and its impact on GNSS- derived integrated water vapor, Atmos. Meas. Tech., 10, 2807-2820, [SCI, 5yr IF = 3.650, Q1].

[91]  Changyong HE, Suqin Wu, Xiaoming Wang, Andong Hu, and Kefei Zhang (2017) A new voxel-based model for the determination of atmospheric-weighted-mean temperature in GPS atmospheric sounding, Atmospheric Measurement Techniques, 10(6):2045-2060 [SCI, 5yr IF = 3.650, Q1].

[92]  Li L, Wu S, Wang X, Tian Y., He C. and Zhang K. (2017). Seasonal multifactor modelling of weighted-mean temperature for ground-based GNSS meteorology in Hunan, china. Advances in Meteorology, 2017, 1-13. [SCI, IF=1.15, Q3].

专家学者

李瑞林

2022-7-10 13:04:07

专家学者

席迅

2022-7-21 13:26:03

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