title: Performance Evaluation and Requirements Assessment for Gravity Gradient Referenced Navigation.
abstract: 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.
authors.affiliation: Department of Geoinformatics, University of Seoul, Seoul 130-743, Korea. leejs@uos.ac.kr.|Department of Civil, Environmental and Geodetic Engineering, Ohio State University, Columbus, OH 43210, USA. leejs@uos.ac.kr.
authors.forename: Jisun
authors.initials: J
authors.lastname: Lee
authors.affiliation: Department of Geoinformatics, University of Seoul, Seoul 130-743, Korea. jkwon@uos.ac.kr.
authors.forename: Jay Hyoun
authors.initials: JH
authors.lastname: Kwon
authors.affiliation: Agency for Defense Development, Daejeon 151-742, Korea. mjyu@add.re.kr.
authors.forename: Myeongjong
authors.initials: M
authors.lastname: Yu
keywords: EKF; GGRN; gravity gradient; requirements analysis