Title :
Thickness retrieval using time series electromagnetic measurements of laboratory grown saline ice
Author :
Shih, S.E. ; Ding, K.H. ; Nghiem, S.V. ; Hsu, C.C. ; Kong, J.A. ; Jordan, A.K.
Author_Institution :
Res. Lab. of Electron., MIT, Cambridge, MA, USA
Abstract :
An electromagnetic inverse scattering theory using time-series measured data has been developed to retrieve the thickness of sea ice. The approach is based on a parametric estimation algorithm where the radiative transfer equation is used as the direct scattering model to calculate backscattering signatures from sea ice. The Levenberg-Marquardt optimization method is used as the inversion algorithm to retrieve the sea ice parameters iteratively. Additional information provided by the sea ice thermodynamics is applied to constrain the electromagnetic inverse problem to achieve more accurate reconstruction. This inversion algorithm is illustrated with experimental data from a thin saline ice sheet grown in a cold room at the U.S. Cold Regions Research and Engineering Laboratory in 1993. Based on this inversion method, the evolution of ice thickness is accurately reconstructed
Keywords :
backscatter; electromagnetic wave scattering; inverse problems; oceanographic techniques; radar cross-sections; radar theory; remote sensing by radar; sea ice; thickness measurement; Levenberg-Marquardt optimization method; backscatter; backscattering signature; inverse problem; inverse scattering theory; inversion algorithm; laboratory grown saline ice; measurement technique; ocean; parametric estimation algorithm; radar remote sensing; radar scattering; radiative transfer equation; sea ice; sea ice parameters; sea surface; thickness retrieval; time series electromagnetic measurements; Electromagnetic measurements; Electromagnetic radiation; Electromagnetic scattering; Ice thickness; Information retrieval; Inverse problems; Iterative algorithms; Sea ice; Sea measurements; Thickness measurement;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International
Conference_Location :
Lincoln, NE
Print_ISBN :
0-7803-3068-4
DOI :
10.1109/IGARSS.1996.516617