Journal ArticleDOI
Performance enhancement of low-cost, high-accuracy, state estimation for vehicle collision prevention system using ANFIS
TLDR
In this article, a low-cost navigation system that fuses the measurements of the inertial navigation system (INS) and the global positioning system (GPS) receiver is developed.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2013-12-01. It has received 25 citations till now. The article focuses on the topics: GPS/INS & Sensor fusion.read more
Citations
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Journal ArticleDOI
An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles
TL;DR: In this article, a navigation technology based on Adaptive Kalman Filter with attenuation factor is proposed to restrain noise in order to improve the precision of navigation information, and the accuracy of the integrated navigation can be improved due to the reduction of the influence of environment noise.
Journal ArticleDOI
Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review.
TL;DR: This article provides a comprehensive review of the state-of-the-art methods utilized to improve the performance of AV systems in short-range or local vehicle environments and focuses on recent studies that use deep learning sensor fusion algorithms for perception, localization, and mapping.
Journal ArticleDOI
Vehicle sideslip angle measurement based on sensor data fusion using an integrated ANFIS and an Unscented Kalman Filter algorithm
TL;DR: In this article, an observer based on ANFIS combined with Kalman filters is proposed to estimate the sideslip angle, which in turn is used to control the vehicle dynamics and improve its behavior.
Journal ArticleDOI
On the vehicle sideslip angle estimation: a literature review of methods, models and innovations
TL;DR: In this article, the authors provide a comprehensive literature review on the side-slip angle estimation problem, focusing on the most effective and innovative approaches, as well as the advantages and limitations of each technique.
Journal ArticleDOI
Fuzzy adaptive integration scheme for low-cost SINS/GPS navigation system
TL;DR: This paper aims to enhance long-term performance of conventional SINS/GPS navigation systems using a fuzzy adaptive integration scheme using a knowledge-based fuzzy inference system for decision-making between the AHRS and the SINS according to vehicle maneuvering conditions.
References
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Book
Applied Optimal Estimation
TL;DR: This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation, and the theory and practice of optimal estimation is presented.
Book
introduction to random signals and applied kalman filtering
TL;DR: In this paper, the Discrete Kalman Filter (DFL) is used for smoothing and prediction linearization in the Global Positioning System (GPS) and a case study is presented.
Journal ArticleDOI
Performance Enhancement of MEMS-Based INS/GPS Integration for Low-Cost Navigation Applications
TL;DR: A two-tier approach is proposed for improving the stochastic modeling of MEMS-based inertial sensor errors using autoregressive processes at the raw measurement level and enhancing the positioning accuracy during GPS outages by nonlinear modeling of INS position errors at the information fusion level using neuro-fuzzy modules, which are augmented in the Kalman filtering INS/GPS integration.
Journal ArticleDOI
GPS/INS integration utilizing dynamic neural networks for vehicular navigation
TL;DR: This study suggests the use of Input-Delayed Neural Networks (IDNN) to model both the INS position and velocity errors based on current and some past samples of INS location and velocity, respectively, which results in a more reliable positioning solution during long GPS outages.