Next Article in Journal
Monocular Vision System for Fixed Altitude Flight of Unmanned Aerial Vehicles
Previous Article in Journal
Addendum: Pinto, M.; Gámez, N.; Fuentes, L.; Amor, M.; Horcas, J.M.; Ayala, I. Dynamic Reconfiguration of Security Policies in Wireless Sensor Networks. Sensors 2015, 15, 5251–5280
Open AccessArticle

Performance Evaluation and Requirements Assessment for Gravity Gradient Referenced Navigation

Department of Geoinformatics, University of Seoul, Seoul 130-743, Korea
Department of Civil, Environmental and Geodetic Engineering, Ohio State University, Columbus, OH 43210, USA
Agency for Defense Development, Daejeon 151-742, Korea
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Sensors 2015, 15(7), 16833-16847;
Received: 5 June 2015 / Revised: 1 July 2015 / Accepted: 8 July 2015 / Published: 13 July 2015
(This article belongs to the Section Physical Sensors)
In this study, simulation tests for gravity gradient referenced navigation (GGRN) are conducted to verify the effects of various factors such as database (DB) and sensor errors, flight altitude, DB resolution, initial errors, and measurement update rates on the navigation performance. Based on the simulation results, requirements for GGRN are established for position determination with certain target accuracies. It is found that DB and sensor errors and flight altitude have strong effects on the navigation performance. In particular, a DB and sensor with accuracies of 0.1 E and 0.01 E, respectively, are required to determine the position more accurately than or at a level similar to the navigation performance of terrain referenced navigation (TRN). In most cases, the horizontal position error of GGRN is less than 100 m. However, the navigation performance of GGRN is similar to or worse than that of a pure inertial navigation system when the DB and sensor errors are 3 E or 5 E each and the flight altitude is 3000 m. Considering that the accuracy of currently available gradiometers is about 3 E or 5 E, GGRN does not show much advantage over TRN at present. However, GGRN is expected to exhibit much better performance in the near future when accurate DBs and gravity gradiometer are available. View Full-Text
Keywords: gravity gradient; GGRN; EKF; requirements analysis gravity gradient; GGRN; EKF; requirements analysis
Show Figures

Figure 1

MDPI and ACS Style

Lee, J.; Kwon, J.H.; Yu, M. Performance Evaluation and Requirements Assessment for Gravity Gradient Referenced Navigation. Sensors 2015, 15, 16833-16847.

Show more citation formats Show less citations formats

Article Access Map by Country/Region

Only visits after 24 November 2015 are recorded.
Back to TopTop