Fei Ye
Southeast University
5 Papers
1 Citations
Fei Ye is an academic researcher from Southeast University. The author has contributed to research in topics: GNSS applications & Computer science. The author has an hindex of 1, co-authored 3 publications.
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Papers
Anomaly Detection for Urban Vehicle GNSS Observation with a Hybrid Machine Learning System
TL;DR: This paper attempts to construct an alternative framework for quality identification of GNSS observations combining clustering-based anomaly detection and supervised classification, in which the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm is used to label the offline dataset as normal and anomalous observations without the aid of 3D building models.
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An Improved Single-Epoch GNSS/INS Positioning Method for Urban Canyon Environment Based on Real-Time DISB Estimation
TL;DR: In this paper, a step-wise ambiguity processing method is introduced to form instantaneous fixed Wide-Lane (WL) observations for calibrating INS measurement, and by estimating the differential inter-system bias (DISB) parameter, the pivot satellite can be shared between different constellations, to increase the number of usable satellites under limited observation conditions and improve the positioning performance.
A Tightly Coupled BDS/INS Integrated Positioning Algorithm Based on Triple-Frequency Single-Epoch Observations
TL;DR: A tightly coupled Beidou Navigation Satellite System (BDS)/INS integration scheme by improving measurement modelling with triple-frequency observations is proposed, which avoids the multiepoch ambiguity searching to fix with conventional carrier-phase processing, thereby improving the positioning stability.
Bayesian Hyperspectral Image Super-Resolution in the Presence of Spectral Variability
TL;DR: In this paper , a novel fusion approach with a Bayesian framework was proposed to solve the spectral variability in high-resolution hyperspectral image (HSI) super-resolution.
Improving GNSS/INS Tightly Coupled Positioning by Using BDS-3 Four-Frequency Observations in Urban Environments
TL;DR: In this article , the performance of GPS/BDS-2/BS-3/INS tightly coupled positioning in urban dynamic environments was evaluated using the GPS-BS-2 and BS-3 four-frequency observations.