GPS - derived Geoid Using Artificial Neural Network and Least Squares Collocation

Stopar, Bojan (author), Ambrožič, Tomaž (author), Kuhar, Miran (author), Turk, Goran (author)

The geoidal undulations are needed for determining the orthometric heights from the Global Positioning System GPS-derived ellipsoidal heights. There ore several methods for geoidal undulation determination. The paper presents a method employing the Artificial Neural Network (ANN) approximation together with the Least Squares Collocation (LSC). The surface obtained by the ANN approximation is used as a trend surface in the least squares collocation. In numerical examples four surfaces were compared: the global geopotential model (EGM96), the European gravimetric quasigeoid 1997 (EGG97), the surface approximated with minimum curvature splines in tension algorithm and the ANN surface approximation. The effectiveness of the ANN surface approximation depends on the number of control points. If the number of well-distributed control points is sufficiently large, the results are better than those obtained by the minimum curvature algorithm and comparable to those obtained by the EGG97 model.

• Language: English
• Keywords: geoid, ANN, collocation
• Typology: 1.01 - Original Scientific Article
• Organization: FGG - Faculty of Civil and Geodetic Engineering
• Publisher: Maney Publishing
• Year: 2006
• Number of pages: Str. 513-524
• Numbering: Vol. 38, No. 300
• PID: 20.500.12556/RUL-32119
• UDC: 528
• ISSN on article: 0039-6265
• COBISS.SI-ID: 3080289
• Publication date in RUL: 10.07.2015

Record is a part of a journal

• Title: Survey review
• Shortened title: Surv. rev. - Dir. Overseas Surv.
• Publisher: Directorate of Overseas Surveys of the Ministry of Overseas Development
• ISSN: 0039-6265
• COBISS.SI-ID: 26484224

Secondary language

• Language: English
• Keywords: geoid, ANN, kolokacija