Hoi-Fung (Ivan) NG

Hoi-Fung (Ivan) NG

PhD student

Publications

3D-mapping-aided PPP-RTK aiming at deep urban canyons

Published in Journal of Geodesy, 2022

This study proposes a 3D-mapping-aided weighting algorithm to enhance the performance of PPP-RTK in complex urban environments

Recommended citation: Xin, S., Geng, J., Zhang, G., Ng, H.-F., Guo, J., & Hsu, L.-T. (2022). 3D-mapping-aided PPP-RTK aiming at deep urban canyons. Journal of Geodesy, 96(10), 78. https://doi.org/10.1007/s00190-022-01666-1. https://link.springer.com/article/10.1007/s00190-022-01666-1

Real-Time Loosely Coupled 3DMA GNSS/Doppler Measurements Integration Using a Graph Optimization and Its Performance Assessments in Urban Canyons of New York

Published in Sensors, 2022

This study developed a real-time 3DMA GNSS-positioning system based on state-of-the-art 3DMA GNSS algorithms and optimized with Doppler measurements using factor graph optimization (FGO) in a loosely-coupled fashion

Recommended citation: Ng, H.-F., Hsu, L.-T., Lee, M. J. L., Feng, J., Naeimi, T., Beheshti, M., & Rizzo, J.-R. (2022). Real-Time Loosely Coupled 3DMA GNSS/Doppler Measurements Integration Using a Graph Optimization and Its Performance Assessments in Urban Canyons of New York. Sensors, 22(17), 6533. https://doi.org/10.3390/s22176533. https://www.mdpi.com/1424-8220/22/17/6533

Urban positioning: 3D mapping-aided GNSS using dual-frequency pseudorange measurements from smartphones

Published in NAVIGATION, 2021

This study integrated the multi-constellation L5-band measurements into 3DMA GNSS to improve the positioning performance in urban canyons, namely the L1-L5 3DMA GNSS.

Recommended citation: Ng, H.-F., Zhang, G., Luo, Y., & Hsu, L.-T. (2021). Urban positioning: 3D mapping-aided GNSS using dual-frequency pseudorange measurements from smartphones. NAVIGATION, Journal of the Institute of Navigation, 68(4), 727-749. https://doi.org/10.1002/navi.448. https://onlinelibrary.wiley.com/doi/full/10.1002/navi.448

Robust GNSS Shadow Matching for Smartphones in Urban Canyons

Published in IEEE Sensors Journal, 2021

This paper introduces a machine learning intelligent classifier with features to distinguish LOS and NLOS. With the NLOS reception classification, the positioning accuracy of shadow matching can be increased

Recommended citation: Ng, H.-F., Zhang, G., & Hsu, L.-T. (2021). Robust GNSS Shadow Matching for Smartphones in Urban Canyons. IEEE Sensors Journal, 21(16), 18307-18317. https://doi.org/10.1109/JSEN.2021.3083801. https://ieeexplore.ieee.org/document/9440901

3D Mapping Database-Aided GNSS RTK and Its Assessments in Urban Canyons

Published in IEEE Transactions on Aerospace and Electronic Systems, 2021

This article compares the position results between 3D mapping-aided GNSS RTK and the GNSS RTK with a fixed elevation angle mask.

Recommended citation: Ng, H.-F., & Hsu, L.-T. (2021). 3D Mapping Database-Aided GNSS RTK and Its Assessments in Urban Canyons. IEEE Transactions on Aerospace and Electronic Systems, 57(5), 3150-3166. https://doi.org/10.1109/TAES.2021.3069271. https://ieeexplore.ieee.org/document/9388876

GNSS RUMS: GNSS Realistic Urban Multiagent Simulator for Collaborative Positioning Research

Published in Remote Sensing, 2021

A GNSS realistic urban measurement simulator is developed to provide measurements for collaborative positioning studies

Recommended citation: Zhang, G., Xu, B., Ng, H.-F., & Hsu, L.-T. (2021). GNSS RUMS: GNSS Realistic Urban Multiagent Simulator for Collaborative Positioning Research. Remote Sensing, 13(4). https://doi.org/10.3390/rs13040544. https://www.mdpi.com/2072-4292/13/4/544

A Computation Effective Range-Based 3D Mapping Aided GNSS with NLOS Correction Method

Published in Journal of Navigation, 2021

A GNSS realistic urban measurement simulator is developed to provide measurements for collaborative positioning studies

Recommended citation: Ng, H.-F., Zhang, G., & Hsu, L.-T. (2020). A Computation Effective Range-based 3D Mapping Aided GNSS with NLOS Correction Method. Journal of Navigation, 73(6), 1202-1222. https://doi.org/10.1017/S037346332000003x. https://www.cambridge.org/core/journals/journal-of-navigation/article/abs/computation-effective-rangebased-3d-mapping-aided-gnss-with-nlos-correction-method/8C84E4AA4FF7DC640BAA7369C7ECFC90

Skymask Matching Aided Positioning Using Sky-Pointing Fisheye Camera and 3D City Models in Urban Canyons

Published in Sensors, 2020

A new skymask matching algorithm is then proposed to match the segmented fisheye images with skymasks generated from a 3D building model.

Recommended citation: Lee, M. J., Lee, S., Ng, H.-F., & Hsu, L.-T. (2020). Skymask Matching Aided Positioning Using Sky-Pointing Fisheye Camera and 3D City Models in Urban Canyons. Sensors, 20(17). https://doi.org/10.3390/s20174728. https://www.mdpi.com/1424-8220/20/17/4728

Improved weighting scheme using consumer-level GNSS L5/E5a/B2a pseudorange measurements in the urban area

Published in Advances in Space Research, 2020

This study developed a GNSS L1/L5 bands integrated positioning algorithm to improve the positioning performance in urban areas

Recommended citation: Ng, H.-F., Zhang, G., Yang, K.-Y., Yang, S.-X., & Hsu, L.-T. (2020). Improved weighting scheme using consumer-level GNSS L5/E5a/B2a pseudorange measurements in the urban area. Advances in Space Research, 66(7), 1647-1658. https://doi.org/10.1016/j.asr.2020.06.002. https://www.sciencedirect.com/science/article/abs/pii/S027311772030404X?via%3Dihub

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

Published in IEEE Transactions on Intelligent Transportation Systems, 2020

This study proposed a novel 3D mapping aided (3DMA) GNSS-based collaborative positioning method that makes use of the available surrounding GNSS receivers’ measurements.

Recommended citation: Zhang, G., Ng, H.-F., Wen, W., & Hsu, L.-T. (2021). 3D Mapping Database Aided GNSS Based Collaborative Positioning Using Factor Graph Optimization. IEEE Transactions on Intelligent Transportation Systems, 22(10), 6175-6187. https://doi.org/10.1109/TITS.2020.2988531. https://ieeexplore.ieee.org/document/9082815