Title :
A Hybrid Reconstruction Algorithm for 3-D Ionospheric Tomography
Author :
Wen, Debao ; Yuan, Yunbin ; Ou, Jikun ; Zhang, Kefei ; Liu, Kai
Author_Institution :
Inst. of Geodesy & Geophys., Chinese Acad. of Sci., Wuhan
fDate :
6/1/2008 12:00:00 AM
Abstract :
In this paper, a hybrid reconstruction algorithm (HRA) is presented to solve the ill-posed inverse problem associated with 3-D ionospheric stochastic tomography. In this new method, the ionospheric electron density (IED) can be inverted by using two steps. First, a truncated singular value decomposition (TSVD) method, whose value is independent on any initial estimation, is used to resolve the ill-posed problem of the tomography system. Second, taking into account the "approximation" of its solution, an iterative improvement process of the solution is then implemented by utilizing the conventional algebraic reconstruction algorithm (ART). The HRA, therefore, offers a more reasonable approach to choose an initial approximate for the ART and to improve the quality of the final reconstructed image. A simulated experiment demonstrates that the HRA method is superior to the TSVD or the ART alone for the tomographic inversion of IED. Finally, the HRA is used to perform GPS-based tomographic reconstruction of the IED at mid- and low-latitude regions.
Keywords :
atmospheric electron precipitation; geophysical signal processing; image reconstruction; inverse problems; ionospheric techniques; singular value decomposition; stochastic processes; tomography; 3D ionospheric stochastic tomography; ART; GPS based tomographic reconstruction; IED inversion; TSVD method; algebraic reconstruction algorithm; hybrid reconstruction algorithm; ill posed inverse problem; image reconstruction; ionospheric electron density; truncated singular value decomposition method; Delay effects; Electrons; Image reconstruction; Ionosphere; Receivers; Reconstruction algorithms; Satellite broadcasting; Satellite navigation systems; Subspace constraints; Tomography; Inverse problem; ionosphere; tomography;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2008.916466