Proceedings ArticleDOI
Navigation with IMU/GPS/digital compass with unscented Kalman filter
P. Zhang,J. Gu,Evangelos E. Milios,P. Huynh +3 more
- Vol. 3, pp 1497-1502
TLDR
In this paper, an autonomous vehicle navigation method by integrating the measurements of IMU, GPS, and digital compass is presented, where two steps are adopted to overcome the low precision of the sensors.Citations
More filters
Journal ArticleDOI
High-Integrity IMM-EKF-Based Road Vehicle Navigation With Low-Cost GPS/SBAS/INS
TL;DR: A set of tests performed in controlled and real scenarios proves the suitability of the proposed IMM-EKF implementation as compared with low-cost GNSS-based solutions, dead reckoning systems, single-model EKF, and other filtering approaches of the current literature.
Proceedings ArticleDOI
MEMS based IMU for tilting measurement: Comparison of complementary and kalman filter based data fusion
TL;DR: In this article, a study on complementary and Kalman filter for real-time tilting measurement using MEMS-based IMU is presented, where the complementary filter algorithm uses low pass filter and high pass filter to deal with the data from accelerometer and gyroscope, while the Kalman Filter takes the tilting angle and gyroscopic bias as system states, combining the angle derived from the accelerometer to estimate the tilts angle.
Journal ArticleDOI
Urban Street Lighting Infrastructure Monitoring Using a Mobile Sensor Platform
TL;DR: A car-mounted sensor platform that enables collection and logging of data on street lights during night-time drive-bys is developed and a framework to improve vehicle location estimates is outlined by combining sensor observations in an extended Kalman filter framework.
Journal ArticleDOI
State of the Art of Automated Buses
Boris Schonfeldt,Ingar Vaskinn,Mauro Bellone,Magdalena Szymanska,Jaagup Ainsalu,Ville Arffman,Maximilian Ellner,Taina Haapamäki,Noora Haavisto,Ebba Josefson,Azat Ismailogullari,Bob Lee,Olav Madland,Raitis Madzulis,Jaanus Müür,Sami Mäkinen,Ville Nousiainen,Eetu Pilli-Sihvola,Eetu Rutanen,Sami Sahala,Piotr Marek Smolnicki,Ralf-Martin Soe,Juha Saaski,Milla Åman +23 more
TL;DR: This work provides a review of the impact of the introduction of driverless electric minibuses, for the first and last mile transportation, in public service with a focus on the Baltic Sea Region.
Journal ArticleDOI
Improving Estimation of Vehicle's Trajectory Using the Latest Global Positioning System With Kalman Filtering
Cesar Barrios,Yuichi Motai +1 more
TL;DR: The goals of this paper are to find a more accurate way to predict the future location of an automobile by 3 s ahead, so that the prediction error can be greatly reduced with the innovative idea of merging global-positioning- system (GPS) data with geographic-information-system (GIS) data.
References
More filters
Proceedings ArticleDOI
New extension of the Kalman filter to nonlinear systems
Simon Julier,Jeffrey Uhlmann +1 more
TL;DR: It is argued that the ease of implementation and more accurate estimation features of the new filter recommend its use over the EKF in virtually all applications.
Proceedings ArticleDOI
The unscented Kalman filter for nonlinear estimation
Eric A. Wan,R. van der Merwe +1 more
TL;DR: The unscented Kalman filter (UKF) as discussed by the authors was proposed by Julier and Uhlman (1997) for nonlinear control problems, including nonlinear system identification, training of neural networks, and dual estimation.
Sigma-Point Kalman Filters for Integrated Navigation
TL;DR: The improved state estimation performance of the SPKF is demonstrated by applying it to the problem of loosely coupled GPS/INS integration and an approximate 30% error reduction in both attitude and position estimates relative to the baseline EKF implementation is demonstrated.
Dissertation
Low Cost, High Integrity, Aided Inertial Navigation Systems for Autonomous Land Vehicles
Journal ArticleDOI
Initial calibration and alignment of low‐cost inertial navigation units for land vehicle applications
Eduardo Nebot,Hugh Durrant-Whyte +1 more
TL;DR: In this paper, an efficient initial calibration and alignment algorithm for a 6-degrees of freedom inertial measurement unit (IMU) to be used in land vehicle applications is presented.