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http://dx.doi.org/10.7848/ksgpc.2015.33.6.569

The Evaluation of the Various Update Conditions on the Performance of Gravity Gradient Referenced Navigation  

Lee, Jisun (Dept. of Geoinformatics, University of Seoul, Dept. of Civil, Environmental and Geodetic Engineering, The Ohio State University)
Kwon, Jay Hyoun (Dept. of Geoinformatics, University of Seoul)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.33, no.6, 2015 , pp. 569-577 More about this Journal
Abstract
The navigation algorithm developed based on the extended Kalman filter (EKF) sometimes diverges when the linearity between the measurements and the states is not preserved. In this study, new update conditions together with two conditions from previous study for gravity gradient referenced navigation (GGRN) were deduced for the filter performance. Also, the effect of each update conditions was evaluated imposing the various magnitudes of the database (DB) and the sensor errors. In case the DB and the sensor errors were supposed to 0.1 Eo and 0.01 Eo, the navigation performance was improved in the eight trajectories by using part of gravity gradient components that independently estimate states located within trust boundary. When applying only the components showing larger variation, around 200% of improvement was found. Even the DB and sensor error were supposed to 3 Eo, six update conditions improved performance in at least seven trajectories. More than five trajectories generated better results with 5 Eo error of the DB and the sensor. Especially, two update conditions successfully control divergence, and bounded the navigation error to the 1/10 level. However, these update conditions could not be generalized for all trajectories so that it is recommended to apply update conditions at the stage of planning, or as an index of precision of GGRN when combine with various types of geophysical data and algorithm.
Keywords
GGRN; EKF; Update Conditions; Stabilization of the Filter;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Li, D., Yang, C., and Hu, C. (1996), On the selection criterion for a terrain matching field, Journal-Huazhong University of Science and Technology Chinese Edition, Vol. 24, pp. 7-8.
2 Liu, F., Qian, D., Zhang, Y., and Li, Y. (2010), A computer simulation of the influence of GGI and inertial sensors on gravity gradient aided navigation, Proceedings of 2010 International Symposium on Systems and Control in Aeronautics and Astronautics, ISSCAA, 8-10 June, Harbin, China, pp. 793-797.
3 Richeson, J.A. (2008), Gravity Gradiometer Aided Inertial Navigation Within Non-GNSS Environments, Ph. D. dissertation, University of Maryland, College Park, MD, USA, 405p.
4 Rogers, M. M. (2009), An Investigation into the Feasibility of Using a Modern Gravity Gradient Instrument for Passive Aircraft Navigation and Terrain Avoidance, Master's thesis, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH, USA, 164p.
5 DeGregoria, A. (2010), Gravity Gradiometry and Map Matching: An Aid to Aircraft Inertial Navigation Systems, Master's thesis, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH, USA, 130p.
6 Lee, J.S. and Kwon, J.H. (2014), Performance analysis of a gravity gradient referenced navigation system, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 32, No. 3, pp. 271-279.   DOI
7 Titterton, D. and John L. (2004), Strapdown Inertial Navigation Technology. 2nd edition, Institution of Engineering and Technology, London, UK.