绝对空间定位到相对空间感知的行人导航研究趋势
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  • 英文篇名:Pedestrian Navigation Research Trend: From Absolute Space to Relative Space-Based Approach
  • 作者:方志祥 ; 徐虹 ; 萧世伦 ; 李清泉 ; 袁淑君 ; 李灵
  • 英文作者:FANG Zhixiang;XU Hong;SHAW Shih-Lung;LI Qingquan;YUAN Shujun;LI Ling;State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University;School of Urban Construction, Wuhan University of Science and Technology;Department of Geography, The University of Tennessee;Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University;
  • 关键词:行人导航 ; 相对空间 ; 绝对定位 ; 地图导航 ; 街景导航 ; 空间感知
  • 英文关键词:pedestrian navigation;;relative space;;absolute locating;;map-based navigation;;scene-based navigation;;spatial sensing
  • 中文刊名:WHCH
  • 英文刊名:Geomatics and Information Science of Wuhan University
  • 机构:武汉大学测绘遥感信息工程国家重点实验室;武汉科技大学城市建设学院;美国田纳西大学地理系;深圳大学深圳市空间信息智能感知与服务重点实验室;
  • 出版日期:2018-12-05
  • 出版单位:武汉大学学报(信息科学版)
  • 年:2018
  • 期:v.43
  • 基金:国家自然科学基金(41771473);; 国家重点研发计划(2017YFC1405302,2017YFB0503802);; 中央高校基本科研业务费专项资金~~
  • 语种:中文;
  • 页:WHCH201812048
  • 页数:10
  • CN:12
  • ISSN:42-1676/TN
  • 分类号:420-429
摘要
相对空间比绝对空间更易于被人理解。行人导航本质是以相对于人的导航环境视觉与空间等相对语义来动态引导行人的过程,即相对导航。目前,GIS导航理论以绝对定位与空间建模为基础,没有充分理解人对相对语义的认知差异,缺乏基于相对语义的导航理论模型。首先,总结了以绝对空间定位与表达为基础的行人导航研究,提出了相对空间感知的行人导航研究新方向。然后,剖析了相对导航研究的理论研究需求,如:行人相对导航数据采集与建模、行人导航环境相对语义的提取、行人导航行为的自动感知分析、行人导航的多感官交互机制、行人导航路径选择与确认机制等。最后,展望了未来行人导航研究与重要创新的3个阶段。
        Relative space is easier to be understood and used in navigation service by pedestrians. The basic characteristic of pedestrian navigation process is the relative space-based guidance by visual and spatial semantics within outdoor and indoor environment. It could be called relative pedestrian navigation. Current pedestrian navigation theory and technique are built upon the locating and modeling within the absolute space. It could not understand the difference of recognition ability of different pedestrians, especially on the relative visual and spatial semantics. The research community of pedestrian navigation doesn't have a relative space-based pedestrian navigation theory framework and technology, which makes the pedestrian services not friendly. This paper reviews the related studies on pedestrian navigation, such as the outdoor/indoor positioning, data collecting and organizing, route planning and guiding. Then, this paper concludes the potential research problems of pedestrian navigation, for example, the relative data collecting and modeling, relative semantic attracting, pedestrian navigation behavior sensing, multisensory interaction, and route choice and confirming mechanism. Finally, this paper introduces a three-stage divisions for the future pedestrian navigation studies.
引文
[1] Li Deren. Opportunities for Geoma- tics[J]. Geomatics and Information Science of Wuhan University, 2004, 29(9): 753-756(李德仁.地球空间信息学的机遇[J].武汉大学学报\5信息科学版,2004, 29(9): 753-756)
    [2] Fang Z, Li Q, Shaw S L. What About People in Pedestrian Navigation?[J]. Geo-spatial Information Science, 2015, 18(4):135-150
    [3] Bi Jingxue, Zhen Jie, Guo Ying. Accuracy of GPS and A-GPS Positioning on Android Phone[J]. Bulletin of Surveying and Mapping, 2016(7):10-13(毕京学,甄杰,郭英.Android手机GPS和A-GPS定位精度分析[J]. 测绘通报,2016(7):10-13)
    [4] Kuusniemi H, Chen Y, Chen L. Multi-sensor Multi-network Positioning[M]//Chen R. Ubiquitous Positioning and Mobile Location-Based Services in Smart Phones. Hershey, PA: IGI Global, 2012
    [5] Bojja J, Kirkko-Jaakkola M, Collin J, et al. Indoor Localization Methods Using Dead Reckoning and 3D Map Matching[J].Journal of Signal Processing Systems, 2014, 76(3):301-312
    [6] Lauro O, Johann B. Non-GPS Navigation for Security Personnel and First Responders[J].Journal of Navigation, 2007, 60(3):391-407
    [7] Saarinen J. A Sensor-Based Personal Navigation System and Its Application for Incorporating Humans into a Human-Robot Team[EB/OL].https://core.ac.uk/download/pdf/80703610.pdf, 2009
    [8] Pei L, Liu J, Guinness R, et al. Using LS-SVM Based Motion Recognition for Smartphone Indoor Wireless Positioning[J].Sensors, 2012, 12(5):6 155-6 175
    [9] Chen R, Pei L, Chen Y. A Smart Phone Based PDR Solution for Indoor Navigation[C]. The 24th International Technical Meeting of the Satellite Division of the Institute of Navigation, Portland, USA, 2011
    [10] Gu Y, Lo A, Niemegeers I. A Survey of Indoor Positioning Systems for Wireless Personal Networks[J]. IEEE Communications Surveys & Tutorials, 2009, 11(1):13-32
    [11] Jiao J, Deng Z, Xu L, et al. A Hybrid of Smartphone Camera and Basestation Wide-Area Indoor Positioning Method[J]. Ksii Transactions on Internet & Information Systems, 2016,10(2):723-743
    [12] Shu Hua, Song Ci, Pei Tao. Progress of Studies on Indoor Positioning Data Analysis and Application [J]. Progress in Geography, 2016, 35(5):580-588(舒华,宋辞,裴韬.室内定位数据分析与应用研究进展[J].地理科学进展,2016,35(5):580-588)
    [13] Deng Z,Yu Y, Xie Y, et al. Situation and Development Tendency of Indoor Positioning[J]. China Communications, 2013, 10(3):42-55
    [14] Barnes J, Rizos C, Wang J, et al. Locata: A New Positioning Technology for High Precision Indoor and Outdoor Positioning[J].Journal of Chemical Physics, 2004,118(15):6 717-6 719
    [15] Mok E, Yuen K Y. A Study on the Use of Wi-Fi Positioning Technology for Wayfinding in Large Shopping Centers[J].Asian Geographer, 2013,30(1):55-64
    [16] Chang Y J, Wang T Y. Indoor Wayfinding Based on Wireless Sensor Networks for Individuals with Multiple Special Needs[J]. Journal of Cybernetics,2010,41(4):317-333
    [17] Liu J, Chen R, Ling P, et al. A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS[J].Sensors, 2012, 12(12):17 208-17 233
    [18] Bekkali A, Sanson H, Matsumoto M. RFID Indoor Positioning Based on Probabilistic RFID Map and Kalman Filtering[C]. 3rd IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2007), New York, USA, 2007
    [19] Pei L, Chen R, Liu J, et al. Using Inquiry-Based Bluetooth RSSI Probability Distributions for Indoor Positioning[J].Journal of Global Positioning Systems, 2010, 9(2):122-130
    [20] Muòoz-Organero M, Muòoz-Merino P J, Kloos C D. Using Bluetooth to Implement a Pervasive Indoor Positioning System with Minimal Requirements at the Application Level[J]. Mobile Information Systems, 2012, 8(1):73-82
    [21] Chóliz J, Hernández-Solana Á, Valdovinos A. Strategies for Optimizing Latency and Resource Utilization in Multiple Target UWB-Based Tracking[C]. IEEE Wireless Communications and Networking Conference, Cancun, Mexico, 2011
    [22] Kuhn M J, Mahfouz M R, Rowe N, et al. Ultra Wideband 3-D Tracking of Multiple Tags for Indoor Positioning in Medical Applications Requiring Millimeter Accuracy[C]. IEEE Topical Conference on Biomedical Wireless Technologies Networks & Sensing Systems, Santa Clara, CA, USA, 2012
    [23] Liu Xiaokang, Guo Hang. Fingerprint Database Optimization Algorithm Based on ZigBee Indoor Positioning System [J]. Computer Engineering, 2014, 40(2):193-198(刘小康,郭杭.基于ZigBee室内定位系统的指纹库优化算法[J].计算机工程,2014,40(2):193-198)
    [24] Kaemarungsi K, Krishnamurthy P. Properties of Indoor Received Signal Strength for WLAN Location Fingerprinting[C]. The 1st Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, New York,USA, 2004
    [25] Zhou Rui, Yuan Xingzhong, Huang Yiming. WiFi-PDR Fused Indoor Positioning Based on Kalman Filtering [J]. Journal of University of Electronic Science and Technology of China,2016,45(3):399-404 (周瑞,袁兴中,黄一鸣.基于卡尔曼滤波的WiFi-PDR融合室内定位[J].电子科技大学学报,2016,45(3):399-404)
    [26] Zhang Peng, Zhao Qile, Li You, et al. PDR/WiFi Fingerprinting/Magnetic Matching-Based Indoor Navigation Method for Smartphones [J]. Journal of Geomatics, 2016,41(3):29-32 (张鹏,赵齐乐,李由,等.基于PDR、WiFi指纹识别、磁场匹配组合的室内行人导航定位[J].测绘地理信息,2016,41(3):29-32)
    [27] Cheng J, Yang L, Li Y, et al. Seamless Outdoor/Indoor Navigation with WiFi/GPS Aided Low Cost Inertial Navigation System[J].Physical Communication, 2014, 13(PA):31-43
    [28] Li Y, Zhuang Y, Zhang P, et al. An Improved Inertial/WiFi/Magnetic Fusion Structure for Indoor Navigation[J]. Information Fusion, 2017,34(C):101-119
    [29] Chen L H, Wu H K, Jin M H, et al. Intelligent Fusion of Wi-Fi and Inertial Sensor-Based Positioning Systems for Indoor Pedestrian Navigation[J].Sensors Journal IEEE, 2014,14(11):4 034-4 042
    [30] Rigelsford J. Panoramic Vision: Sensors, Theory and Applications[M].New York:Springer-Verlag, 2001
    [31] Chen L, Kuusniemi H, Chen Y, et al. Constraint Kalman Filter for Indoor Bluetooth Localization[C]. Signal Processing Conference, 23rd European, Nice, France,2015
    [32] Agarwal P, Burgard W, Spinello L. Metric Localization Using Google Street View[C]. 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),Hamburg,Germany,2015
    [33] Lowe D G. Distinctive Image Features from Scale-Invariant Keypoints[J]. International Journal of Computer Vision, 2004, 60(2):91-110
    [34] Majdik A L, Albers-Schoenberg Y, Scaramuzza D. MAV Urban Localization from Google Street View Data[C]. 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo,Japan,2013
    [35] Salarian M, Manavella A, Ansari R. Accurate Localization in Dense Urban Area Using Google Street View Images[C]. SAI Intelligent Systems Confe- rence (Intelli Sys), London,UK,2014
    [36] Sonka M, Hlavac V, Ceng R B D M. Image Processing, Analysis and Machine Vision[J].Journal of Electronic Imaging, 2014,19(82):685-686
    [37] Klein G S W,Drummond T.A Single-Frame Visual Gyroscope[C]. The British Machine Vision Confe-rence, Oxford, UK,2005
    [38] Ruotsalainen L, Kuusniemi H, Chen R. Visual-Aided Two-Dimensional Pedestrian Indoor Navigation with a Smartphone[J]. Journal of Global Positioning Systems, 2011,10(1):11-18
    [39] Hong D, Lee H, Cho H, et al. Visual Gyroscope: Integration of Visual Information with Gyroscope for Attitude Measurement of Mobile Platform[C]. International Conference on Control, Automation and Systems, Seoul, South Korea,2008
    [40] Ruotsalainen L, Bancroft J, Kuusniemi H, et al. Utilizing Visual Measurements for Obtaining Robust Attitude and Positioning for Pedestrians[C]. ION GNSS12 Conference, Nashville, TN, USA, 2012
    [41] Kerl C, Sturm J, Cremers D. Robust Odometry Estimation for RGB-D Cameras [C]. IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 2013
    [42] Newcombe R A, Izadi S, Hilliges O, et al. KinectFusion: Real-Time Dense Surface Mapping and Tracking[C]. IEEE International Symposium on Mixed and Augmented Reality(ISMAR), Basel, Switzerland, 2012
    [43] Chen C, Chai W, Zhang Y, et al. A RGB and D Vision Aided Multi-sensor System for Indoor Mobile Robot and Pedestrian Seamless Navigation[C]. Position, Location and Navigation Symposium-PLANS2014, 2014 IEEE/ION, Monterey, CA, USA, 2014
    [44] Pei L, Chen R, Chen Y, et al. Indoor/Outdoor Seamless Positioning Technologies Integrated on Smart Phone[C]. 1st International Conference on Advances in Satellite and Space Communications, Colmar, France, 2009
    [45] Puyol M G, Robertson P, Heirich O. Complexity-Reduced Foot SLAM for Indoor Pedestrian Navigation Using a Geographic Tree-Based Data Structure[J]. Journal of Location Based Services,2013,7(3):182-208
    [46] Bi Jingxue, Wang Yunjia, Zhen Jie. A Method of Indoor and Outdoor Scene Recognition Based on Mobile Phone and Its Preliminary Experiment[J]. Geography and Geo-Information Science, 2017, 33(3): 48-51 (毕京学,汪云甲,甄杰.一种基于手机端的室内外场景识别方法及其初步实验[J].地理与地理信息科学,2017,33(3):48-51)
    [47] Tian Hui, Xia Linyuan, Mo Zhiming, et al. Signals of Opportunity Assisted Ubiquitous Positioning and Its Key Elements for Outdoor /Indoor Environment [J]. Geomatics and Information Science of Wuhan University, 2009,34(11):1 372-1 376 (田辉,夏林元,莫志明,等.泛在无线信号辅助的室内外无缝定位方法与关键技术[J].武汉大学学报·信息科学版,2009,34(11):1 372-1 376)
    [48] Hu Xuke, Shang Jian’ga, Gu Fuqiang, et al. Deve- lopment of Indoor/Outdoor Seamless Positioning Prototype System Fusing GPS and Wi-Fi[J]. Journal of Chinese Computer Systems,2014,35(2):428-432 (胡旭科,尚建嘎,古富强,等.融合GPS与Wi-Fi的室内外无缝定位原型系统研制[J].小型微型计算机系统,2014,35(2):428-432)
    [49] Liu T, Zhang X, Li Q, et al. A Visual-Based Approach for Indoor Radio Map Construction Using Smartphone[J]. Sensors, 2017, 17(8):1 790
    [50] Han Q, Curtin K M , Rice M T . Pedestrian Network Repair with Spatial Optimization Models and Geocrowdsourced Data[J]. GeoJournal, 2018, 83(2):347-364
    [51] Van Essen R, Hiestermann V. “X-GDF”―The ISO Model of Geographic Information for ITS[C]. ISPRS Workshop on Service and Application of Spatial Data Infrastructure, Hangzhou, China, 2005
    [52] ISO/TC204/WG3. ISO14825-2004. Intenlligent Transportation Systems-Geographic Data Files(GDF)-Overall Data Specification[S]. EN: International Standards Organization, 2005
    [53] Kiwi-w Consortium.Input for ISO Physical Storage Format[EB/OL].http://kiwi-w.mapmaster.co.jp/ format_english/ format kihon.html,2006
    [54] Kiwi-w Consortium. Kiwi Format, Version 1.22[EB/OL]. http://www.kiwi-w.mapmaster.co.jp/documents_eng.html,2017
    [55] Li Qingquan, Zuo Xiaoqing, Xie Zhiying. Progress and Trend of Research on GIS-T Linear Data Model [J]. Geography and Geo-information Science, 2004, 20(3):31-35 (李清泉,左小清,谢智颖.GIS-T线性数据模型研究现状与趋势[J].地理与地理信息科学,2004,20(3):31-35)
    [56] Li Qingquan, Xu Jinghai, Li Mingfeng. Progress and Trend of Research on Navigable Digital Map Data Mode [J]. Journal of Geomatics,2007,32(6):22-25(李清泉,徐敬海,李明峰.导航地图数据模型研究现状与趋势[J].测绘地理信息,2007,32(6):22-25)
    [57] Lu Feng, Zhou Chenghu, Wan Qing. A Feature-Based Non-planar Data Model for Urban Traffic Networks[J]. Acta Geodaetica et Cartographic Sinica, 2000, 29(4):334-341(陆锋, 周成虎,万庆. 基于特征的城市交通网络非平面数据模型[J]. 测绘学报, 2000, 29(4):334-341)
    [58] Liu Y, Zheng J, Lei Y, et al. Study on the Real Time Navigation Data Model for Dynamic Navigation[C]. 2005 IEEE International Geoscience and Remote Sensing Symposium (IGARSS’05), Seoul, South Korea, 2005
    [59] Xia K, Wei C. Study on Real-Time Navigation Data Model Based on ESRI Shapefile[C]. International Conference on Embedded Software & Systems Symposia, New York,USA, 2008
    [60] Wang Zhao. Autonomous Incremental Updating of Vehicle Navigation Digital Map[D]. Beijing: Tsinghua University,2012(王钊. 车辆导航电子地图的自增量更新[D]. 北京:清华大学, 2012)
    [61] Fang Z, Li Q, Zhang X, et al. A GIS Data Model for Landmark-Based Pedestrian Navigation[J].International Journal of Geographical Information Science, 2012, 26(5): 817-838
    [62] Zhang Huabing, Fang Zhixiang, Guo Yihan, et al. A Saliency-Based Pedestrian Navigation Data Model[J]. Journal of Geomatics, 2015, 40(3): 57-59(张华兵,方志祥,郭翌寒,等. 基于实景显著性的行人导航数据模型[J]., 测绘地理信息,2015, 40(3): 57-59)
    [63] Dijkstra E W. A Note on Two Problems in Conne- xion with Graphs[J]. Numerische Mathematik, 1959, 1(1) :269-271
    [64] Hart P E, Nilsson N J, Raphael B. A Formal Basis for the Heuristic Determination of Minimum Cost Paths[J]. IEEE Transactions on Systems Science and Cybernetics, 1968, 4(2):100-107
    [65] Li Yinzhen, Guo Yaohuang. Bound Searching Algorithm for Shortest Path in a Network[J]. Journal of Southwest Jiaotong University, 2004,39(5):561-564(李引珍,郭耀煌. 网络最短路径定界搜索算法[J]. 西南交通大学学报,2004,39(5):561-564)
    [66] Delling D, Goldberg A V, Pajor T, et al. Customizable Route Planning in Road Networks[J].Transportation Science, 2017, 51(2): 566-591
    [67] Zheng Nianbo, Li Qingquan, Xu Jinghai,et al. A Bidirectional Heuristic Shortest Path Algorithm with Turn Prohibitions and Delays[J]. Geomatics and Information Science of Wuhan University, 2006, 31(3): 256-259(郑年波,李清泉,徐敬海,等. 基于转向限制和延误的双向启发式最短路径算法[J]. 武汉大学学报·信息科学版, 2006, 31(3): 256-259)
    [68] Tomko M, Winter S, Claramunt C. Experiential Hierarchies of Streets[J]. Computers Environment and Urban Systems, 2008, 32(1): 41-52
    [69] Zhang Xing, Li Qingquan, Fang Zhixiang, et al. Landmark and Branch-Based Pedestrian Route Complexity and Selection Algorithm[J]. Geomatics and Information Science of Wuhan University, 2013, 38(10):1 239-1 242(张星, 李清泉, 方志祥,等.顾及地标与道路分支的行人导航路径选择算法[J].武汉大学学报·信息科学版,2013,38(10):1 239-1 242)
    [70] Liu Tao, Zhang Xing, Li Qingquan, et al. An Indoor Pedestrian Route Planning Algorithm Based Landmark Visibility[J]. Geomatics and Information Science of Wuhan University, 2017,42(1):43-48 (刘涛,张星,李清泉,等.顾及地标可视性的室内导航路径优化算法[J].武汉大学学报\5信息科学版, 2017,42(1):43-48)
    [71] Fang Z, Li Q, Zhang X. A Multiobjective Model for Generating Optimal Landmark Sequences in Pedestrian Navigation Applications[J].International Journal of Geographical Information Science, 2011, 25(5):785-805
    [72] Fang Z, Li L,Li B, et al. An Artificial Bee Colony-Based Multi-objective Route Planning Algorithm for Use in Pedestrian Navigation at Night[J]. International Journal of Geographical Information Science, 2017, 31(10): 2 020-2 044
    [73] Zhao Weifeng, Li Qingquan, Li Bijun. Spatial Cognition Driven Context-Adaptive Route Directions[J]. Journal of Remote Sensing, 2011,15(6):1 171-1 188(赵卫锋,李清泉,李必军. 空间认知驱动的自适应路径引导[J]. 遥感学报,2011,15(6): 1 171-1 188)
    [74] Zhu Haihong, Wen Ya, Mao Kai, et al. A Quantitative POI Salience Model for Indoor Landmark Extraction[J]. Geomatics and Information Science of Wuhan University, 2018, 43(3): 336-341(朱海红, 温雅, 毛凯, 等.室内地标提取的POI显著度定量评价模型[J]. 武汉大学学报\5信息科学版, 2018, 43(3): 336-341)
    [75] Yang Jie, Yang Nai, Huang Ting, et al. Cognitive Rules of People Choosing Routes in Large Stores[J]. Geomatics and Information Science of Wuhan University, 2017, 42(3): 414-420(杨洁, 杨乃, 黄婷, 等. 大型商场内人群择路行为认知规律的研究[J]. 武汉大学学报·信息科学版, 2017, 42(3): 414-420)
    [76] Li Lin, Mao Kai, Tan Yongbin. Hierarchy Landmarks Multi-granularity Description Method for Route Guidance[J]. Acta Geodaetica et Cartographica Sinica, 2014 43(1):105-110(李霖,毛凯,谭永滨. 地标分层多粒度路径导引描述方法[J]. 测绘学报,2014, 43(1):105-110)
    [77] Bernardini G, Santarelli S, Quagliarini E, et al. Dynamic Guidance Tool for a Safer Earthquake Pedestrian Evacuation in Urban Systems[J]. Computers, Environment and Urban Systems, 2017,65:150-161
    [78] Chaudary B, Paajala I, Keino E, et al. Tele-guidance Based Navigation System for the Visually Impaired and Blind Persons[C]. International Summit on eHealth (eHealth360), Budapest, Hungary, 2016
    [79] Vanclooster A, van de Weghe N, de Maeyer P. Integrating Indoor and Outdoor Spaces for Pedestrian Navigation Guidance: A Review[J]. Transactions in GIS,2016, 20(4): 491-525
    [80] Albrech R, Vaananen R, Lokki T. Guided by Music: Pedestrian and Cyclist Navigation with Route and Beacon Guidance[J]. Personal and Ubiquitous Computing, 2016, 20(1):121-145
    [81] Balata J, Mikovec Z, Bures P, et al. Automatically Generated Landmark-Enhanced Navigation Instructions for Blind Pedestrians[C]. Federated Confe- rence on Computer Science and Information Systems (FedCSIS), Gdansk, Poland, 2016
    [82] Gonnot T, Saniie J. Integrated Machine Vision and Communication System for Blind Navigation and Guidance[C]. IEEE International Conference on Electro Information Technology (EIT), Univ N Dakota, Grand Forks, ND, 2016
    [83] Spiers A J, Dollar A M. Outdoor Pedestrian Navigation Assistance with a Shape-Changing Haptic Interface and Comparison with a Vibrotactile Device[C]. 24th IEEE Haptics Symposium, Philadelphia, PA, 2016
    [84] Zhao Wenye, Gao Jingxiang, Li Zengke, et al. An Indoor Positioning System Based on Map-Aided KF-PF Module[J]. Geomatics and Information Science of Wuhan University, 2018, 43(5): 806-812(赵文晔, 高井祥, 李增科, 等. 地图匹配辅助的KF-PF室内定位算法模型[J]. 武汉大学学报\5信息科学版, 2018, 43(5): 806-812)
    [85] Wan Wenhui, Li Yu, Hu Wenmin, et al. Mobile Platform Localization by Integration of Stereo Came- ras, IMU and Wheel Qdometer Based on Federated Filter[J]. Geomatics and Information Science of Wuhan University, 2018, 43(1): 101-106(万文辉, 李宇, 胡文敏, 等. 基于联邦滤波进行立体相机/IMU/里程计运动平台组合导航定位[J]. 武汉大学学报·信息科学版, 2018, 43(1): 101-106)
    [86] Zhou Baoding,Li Qingquan,Mao Qingzhou,et al. User Activity Awareness Assisted Indoor Pedestrian Localization[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6): 719-723(周宝定,李清泉,毛庆洲,等. 用户行为感知辅助的室内行人定位[J]. 武汉大学学报·信息科学版, 2014, 39(6): 719-723)
    [87] Huang Zhiyong, Zhao Dongqing, Zhang Shuangna, et al. A-GNSS Indoor Positioning Based on Coarse-Time Navigation and RAIM Algorithm[J]. Geomatics and Information Science of Wuhan University, 2017, 42(3): 321-327(黄志勇, 赵冬青, 张爽娜, 等. 基于粗时段导航与RAIM算法的A-GNSS室内定位[J]. 武汉大学学报·信息科学版, 2017, 42(3): 321-327)
    [88] Hu Xuemin, Zheng Hong, Guo Lin, et al. Crowd Motion Estimation Using a Fisheye Camera[J]. Geomatics and Information Science of Wuhan University, 2017, 42(4): 537-542(胡学敏, 郑宏, 郭琳, 等. 利用鱼眼相机对人群进行运动估计[J]. 武汉大学学报·信息科学版, 2017, 42(4): 537-542)

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