GPS - derived Geoid Using Artificial Neural Network and Least Squares Collocation
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.
2006
2015-07-10 10:12:08
1033
geoid, ANN, collocation
geoid, ANN, kolokacija
Maney Publishing
Bojan
Stopar
70
Tomaž
Ambrožič
70
Miran
Kuhar
70
Goran
Turk
70
UDK
4
528
ISSN pri članku
9
0039-6265
COBISS_ID
3
3080289
OceCobissID
13
26484224
0
Predstavitvena datoteka
2015-07-10 10:12:08
SReview_ANN_n.pdf
989301
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2016-06-15 08:15:02