NDLI: An analysis of observability-constrained Kalman Filtering for vision-aided navigation

Content Provider	IEEE Xplore Digital Library
Author	Taylor, C.N.
Copyright Year	2012
Description	Author affiliation: Sensors Directorate, The United States Air Force Research Laboratory, USA (Taylor, C.N.)
Abstract	Significant improvements in the accuracy of navigation state estimation have been previously demonstrated through the fusion of inertial measurement unit (IMU) and visual sensor data in both GPS-denied and GPS-enabled scenarios. Despite this improved navigation state accuracy, several significant hurdles remain before widespread acceptance of vision-aided navigation can be achieved. One significant bottleneck is the lack of accurate information about the performance of the vision-aided navigation algorithms. Many vision-aided navigation algorithms are implemented using some form of the Kalman Filter, thereby returning a covariance estimate that should correspond with the accuracy of the current navigation estimate. Unfortunately, a well known problem with the Kalman Filter is that its covariance estimates are inconsistent, i.e. the Kalman Filter estimates of uncertainty are significantly smaller than the true uncertainty achieved by the Kalman Filter. Recently a set of papers has introduced the concept of “observability-constrained” Kalman filtering that helps solve the consistency problem. In this paper, we apply the observability-constrained Kalman Filter to a vision-aided navigation problem and analyze its results. Significantly more accurate state and uncertainty estimates are achieved using the observability-constrained Kalman Filter. Unfortunately, the it is still not consistent, so a comparison with a batch, bundle adjustment approach is also performed to verify the possibility of consistent uncertainty estimation.
Starting Page	1240
Ending Page	1246
File Size	1311426
Page Count	7
File Format	PDF
ISBN	9781467303859
ISSN	21533598
e-ISBN	9781467303873
DOI	10.1109/PLANS.2012.6236980
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Navigation Lead Kalman filters
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
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