A systematic review of machine learning techniques for GNSS use cases
A Siemuri, K Selvan, H Kuusniemi… - … on Aerospace and …, 2022 - ieeexplore.ieee.org
In terms of the availability and accuracy of positioning, navigation, and timing (PNT), the
traditional Global Navigation Satellite System (GNSS) algorithms and models perform well …
traditional Global Navigation Satellite System (GNSS) algorithms and models perform well …
Prediction of compressive strength of rice husk ash concrete based on stacking ensemble learning model
Q Li, Z Song - Journal of Cleaner Production, 2023 - Elsevier
By replacing cement in concrete production with rice husk ash (RHA), the amount of cement
used and its environmental impact can be reduced. The objective of this study is to …
used and its environmental impact can be reduced. The objective of this study is to …
A hybrid genetic-fuzzy ant colony optimization algorithm for automatic K-means clustering in urban global positioning system
X Ran, N Suyaroj, W Tepsan, J Ma, X Zhou… - … Applications of Artificial …, 2024 - Elsevier
This paper introduces an innovative automatic K-means clustering algorithm, namely HGA-
FACO, which seamlessly integrates the noise algorithm, Genetic Algorithm (GA), Ant Colony …
FACO, which seamlessly integrates the noise algorithm, Genetic Algorithm (GA), Ant Colony …
New time-differenced carrier phase approach to GNSS/INS integration
The accuracy of navigation information is essential for modern transport systems. Such
information includes position, velocity and attitude. Because of the physical characteristics of …
information includes position, velocity and attitude. Because of the physical characteristics of …
Application of machine learning in electromagnetics: Mini-review
As an integral part of the electromagnetic system, antennas are becoming more advanced
and versatile than ever before, thus making it necessary to adopt new techniques to …
and versatile than ever before, thus making it necessary to adopt new techniques to …
An adaptive weighting strategy for multisensor integrated navigation in urban areas
Integration of global navigation satellite systems (GNSS) with other sensors, such as inertial
measurement units (IMU) and visual sensors, has been widely used to improve the …
measurement units (IMU) and visual sensors, has been widely used to improve the …
Prediction on the urban GNSS measurement uncertainty based on deep learning networks with long short-term memory
The GNSS performance could be significantly degraded by the interferences in an urban
canyon, such as the blockage of the direct signal and the measurement error due to …
canyon, such as the blockage of the direct signal and the measurement error due to …
Resilient pseudorange error prediction and correction for GNSS positioning in urban areas
Positioning, navigation, and timing (PNT) is essential for Internet of Things (IoT)
communications and location-based services. Although global navigation satellite system …
communications and location-based services. Although global navigation satellite system …
Pseudorange error prediction for adaptive tightly coupled GNSS/IMU navigation in urban areas
The integration of global navigation satellite systems (GNSS) and inertial measurement unit
(IMU) with the Kalman filter is widely used to enhance the availability of positioning in urban …
(IMU) with the Kalman filter is widely used to enhance the availability of positioning in urban …
Machine learning-based short-term GPS TEC forecasting during high solar activity and magnetic storm periods
Precise ionospheric total electron content (TEC) is critical for many aerospace applications,
and forecasting ionospheric TEC is of great significance to it. Besides, short-term prediction …
and forecasting ionospheric TEC is of great significance to it. Besides, short-term prediction …