NDLI: Analysis on the kalman filter performance in GPS/INS integration at different noise levels, sampling periods and curvatures

Content Provider	IEEE Xplore Digital Library
Author	Ojha, U. Mo-Yuen Chow Chang, T. Daniel, J.
Copyright Year	2009
Description	Author affiliation: New Jersey Institute of Technology (Chang, T.; Daniel, J.) \|\| North Carolina State University (Ojha, U.; Mo-Yuen Chow)
Abstract	Kalman filters (KF) have been extensively used in the integration of Global Positioning System (GPS) and Inertial Navigation System (INS) data. Often, the GPS data is used as a benchmark to update the INS data. In this study, an analysis of integration of GPS data with INS data using an Extended Kalman filter is performed in terms of the filter's performance with respect to the amount of noise in the GPS data and the sampling time of the vehicle position. The study further analyzes and compares the pattern of error at varying sampling periods in vehicle trajectories with high curvature path segments and low curvature path segments. Simulation results are presented at the end. The results show that the performance of the KF depends linearly on the amount of noise and sampling times. The relationship between the curvature of the road and the performance of the KF was found to be quadratic.
Starting Page	2975
Ending Page	2980
File Size	450186
Page Count	6
File Format	PDF
ISBN	9781424446483
ISSN	1553572X
e-ISBN	9781424446506
DOI	10.1109/IECON.2009.5415281
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-11-03
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance analysis Global Positioning System Noise level Sampling methods Vehicles Roads Filters Inertial navigation Intelligent transportation systems Fuses
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Constrained unscented Kalman filter based fusion of GPS/INS/digital map for vehicle localization

Autonomous navigation of a small boat using IMU/GPS/digital compass integration

Tightly Coupled GPS/INS Integrated Navigation Algorithm Based on Kalman Filter

Improving INS/GPS Navigation Accuracy through Compensation of Kalman Filter Errors

The research and implementation of intelligent vehicle based on differential GPS and inertial navigation system

Application of extended kalman filter to unmanned helicopter navigation

Compensation of selected availability using a GPS/INS extended Kalman filter

A Kalman Filter based information fusion method for traffic speed estimation

Adaptive Kalman filtering based navigation: An IMU/GPS integration approach

Analysis on the kalman filter performance in GPS/INS integration at different noise levels, sampling periods and curvatures

Similar Documents

Constrained unscented Kalman filter based fusion of GPS/INS/digital map for vehicle localization

Autonomous navigation of a small boat using IMU/GPS/digital compass integration

Tightly Coupled GPS/INS Integrated Navigation Algorithm Based on Kalman Filter

Improving INS/GPS Navigation Accuracy through Compensation of Kalman Filter Errors

The research and implementation of intelligent vehicle based on differential GPS and inertial navigation system

Application of extended kalman filter to unmanned helicopter navigation

Compensation of selected availability using a GPS/INS extended Kalman filter

A Kalman Filter based information fusion method for traffic speed estimation

Adaptive Kalman filtering based navigation: An IMU/GPS integration approach

Analysis on the kalman filter performance in GPS/INS integration at different noise levels, sampling periods and curvatures