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

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

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.

• Jezik: Angleški jezik
• Ključne besede: geoid, ANN, collocation
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FGG - Fakulteta za gradbeništvo in geodezijo
• Založnik: Maney Publishing
• Leto izida: 2006
• Št. strani: Str. 513-524
• Številčenje: Vol. 38, No. 300
• PID: 20.500.12556/RUL-32119
• UDK: 528
• ISSN pri članku: 0039-6265
• COBISS.SI-ID: 3080289
• Datum objave v RUL: 10.07.2015

Gradivo je del revije

• Naslov: Survey review
• Skrajšan naslov: Surv. rev. - Dir. Overseas Surv.
• Založnik: Directorate of Overseas Surveys of the Ministry of Overseas Development
• ISSN: 0039-6265
• COBISS.SI-ID: 26484224

Sekundarni jezik

• Jezik: Angleški jezik
• Ključne besede: geoid, ANN, kolokacija