World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
43
Citations
6618
World Ranking
6243
National Ranking
1176

Li-Ta Hsu publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Li-Ta Hsu sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 288 publications — 74th percentile

74% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Li-Ta Hsu D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Li-Ta Hsu sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 43 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Li-Ta Hsu is affiliated with the Hong Kong Polytechnic University in China and has contributed extensively to the field of engineering, with a particular focus on aerospace engineering, electrical and electronic engineering, environmental engineering, computer vision and pattern recognition, and artificial intelligence.

Their research primarily addresses topics in localization technologies, GNSS positioning and interference, inertial sensor and navigation systems, robotics and sensor-based localization, as well as remote sensing and LiDAR applications. Additional topics include 3D surveying and cultural heritage, and target tracking and data fusion in sensor networks.

Recent publications by Li-Ta Hsu illustrate a broad range of interests and impacts. Notable papers include:

  • Factor graph optimization for GNSS/INS integration: A comparison with the extended Kalman filter, 2021, NAVIGATION Journal of the Institute of Navigation
  • UrbanNav:An Open-Sourced Multisensory Dataset for Benchmarking Positioning Algorithms Designed for Urban Areas, 2021, Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
  • Improving GPS Code Phase Positioning Accuracy in Urban Environments Using Machine Learning, 2020, IEEE Internet of Things Journal
  • Machine learning based LOS/NLOS classifier and robust estimator for GNSS shadow matching, 2020, Satellite Navigation
  • Prediction on the Urban GNSS Measurement Uncertainty Based on Deep Learning Networks With Long Short-Term Memory, 2021, IEEE Sensors Journal

Li-Ta Hsu frequently collaborates with researchers such as Weisong Wen, Guohao Zhang, Hoi-Fung Ng, Bing Xu, and Feng Huang, reflecting ongoing partnerships in their research community.

They often publish in venues such as the Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM), arXiv, NAVIGATION Journal of the Institute of Navigation, IEEE Transactions on Intelligent Vehicles, and Proceedings of the Institute of Navigation International Technical Meeting. These venues represent a consistent engagement with both conference proceedings and journal publications related to navigation and intelligent systems.

Best Publications

  • 3D building model-based pedestrian positioning method using GPS/GLONASS/QZSS and its reliability calculation

    Li-Ta Hsu;Yanlei Gu;Shunsuke Kamijo

  • Analysis and modeling GPS NLOS effect in highly urbanized area

    Li Ta Hsu

  • Factor graph optimization for GNSS/INS integration: A comparison with the extended Kalman filter

    Weisong Wen;Tim Pfeifer;Xiwei Bai;Li Ta Hsu

  • GNSS multipath detection using a machine learning approach

    Li-Ta Hsu

  • A gradient boosting decision tree based GPS signal reception classification algorithm

    Rui Sun;Rui Sun;Guanyu Wang;Wenyu Zhang;Li-Ta Hsu

  • Tightly Coupled GNSS/INS Integration via Factor Graph and Aided by Fish-Eye Camera

    Weisong Wen;Xiwei Bai;Yin Chiu Kan;Li-Ta Hsu

  • GPS Error Correction With Pseudorange Evaluation Using Three-Dimensional Maps

    Shunsuke Miura;Li-Ta Hsu;Feiyu Chen;Shunsuke Kamijo

  • Multipath mitigation and NLOS detection using vector tracking in urban environments

    Li-Ta Hsu;Shau-Shiun Jan;Paul D. Groves;Nobuaki Kubo

  • Intelligent GNSS/INS integrated navigation system for a commercial UAV flight control system

    Guohao Zhang;Li Ta Hsu

  • UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes

    Weisong Wen;Yiyang Zhou;Guohao Zhang;Saman Fahandezh-Saadi

  • GNSS/Onboard Inertial Sensor Integration With the Aid of 3-D Building Map for Lane-Level Vehicle Self-Localization in Urban Canyon

    Yanlei Gu;Li-Ta Hsu;Shunsuke Kamijo

  • Multiple Faulty GNSS Measurement Exclusion Based on Consistency Check in Urban Canyons

    Li-Ta Hsu;Hiroko Tokura;Nobuaki Kubo;Yanlei Gu

  • NLOS Correction/Exclusion for GNSS Measurement Using RAIM and City Building Models.

    Li Ta Hsu;Yanlei Gu;Shunsuke Kamijo

  • UrbanNav:An Open-Sourced Multisensory Dataset for Benchmarking Positioning Algorithms Designed for Urban Areas

    Li-Ta Hsu;Nobuaki Kubo;Weisong Wen;Wu Chen

  • Urban Pedestrian Navigation Using Smartphone-Based Dead Reckoning and 3-D Map-Aided GNSS

    Li-Ta Hsu;Yanlei Gu;Yuyang Huang;Shunsuke Kamijo

  • Towards Robust GNSS Positioning and Real-time Kinematic Using Factor Graph Optimization

    Weisong Wen;Li-Ta Hsu

  • Improving GPS Code Phase Positioning Accuracy in Urban Environments Using Machine Learning

    Rui Sun;Guanyu Wang;Qi Cheng;Linxia Fu

  • GNSS NLOS Exclusion Based on Dynamic Object Detection Using LiDAR Point Cloud

    Weisong Weisong Wen;Guohao Zhang;Li-Ta Hsu

  • Prediction on the Urban GNSS Measurement Uncertainty Based on Deep Learning Networks With Long Short-Term Memory

    Guohao Zhang;Penghui Xu;Haosheng Xu;Li-Ta Hsu

  • Machine learning based LOS/NLOS classifier and robust estimator for GNSS shadow matching

    Haosheng Xu;Antonio Angrisano;Salvatore Gaglione;Li-Ta Hsu

  • A New Path Planning Algorithm Using a GNSS Localization Error Map for UAVs in an Urban Area

    Guohao Zhang;Li Ta Hsu

  • Passive Sensor Integration for Vehicle Self-Localization in Urban Traffic Environment

    Yanlei Gu;Li Ta Hsu;Shunsuke Kamijo

  • Vector Tracking Loop-Based GNSS NLOS Detection and Correction: Algorithm Design and Performance Analysis

    Bing Xu;Qiongqiong Jia;Li-Ta Hsu

  • Human-like motion planning model for driving in signalized intersections

    Yanlei Gu;Yoriyoshi Hashimoto;Li-Ta Hsu;Miho Iryo-Asano

  • 3D Mapping Database Aided GNSS Based Collaborative Positioning Using Factor Graph Optimization

    Guohao Zhang;Hoi-Fung Ng;Weisong Wen;Li-Ta Hsu

  • Intelligent GPS L1 LOS/Multipath/NLOS Classifiers Based on Correlator-, RINEX- and NMEA-Level Measurements

    Bing Xu;Qiongqiong Jia;Qiongqiong Jia;Yiran Luo;Yiran Luo;Li Ta Hsu

  • GPS signal reception classification using adaptive neuro-fuzzy inference system

    Rui Sun;Li-Ta Hsu;Dabin Xue;Guohao Zhang

  • Extending Shadow Matching to Tightly-Coupled GNSS/INS Integration System

    Guohao Zhang;Weisong Wen;Bing Xu;Li-Ta Hsu

  • Performance Comparison of GNSS/INS Integrations Based on EKF and Factor Graph Optimization

    Weisong Wen;Yin Chiu Kan;Li Ta Hsu

  • Time-correlated Window Carrier-phase Aided GNSS Positioning Using Factor Graph Optimization for Urban Positioning.

    Xiwei Bai;Weisong Wen;Li-Ta Hsu

  • A GPS spoofing generator using an open sourced vector tracking-based receiver

    Qian Meng;Li Ta Hsu;Bing Xu;Xiapu Luo

Frequent Co-Authors

Washington Y. Ochieng
Washington Y. Ochieng Imperial College London
Masayoshi Tomizuka
Masayoshi Tomizuka University of California, Berkeley
Naser El-Sheimy
Naser El-Sheimy University of Calgary

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