Print Email Facebook Twitter Efficient GOCE satellite gravity field recovery based on least-squares using QR decomposition Title Efficient GOCE satellite gravity field recovery based on least-squares using QR decomposition Author Baur, O. Austen, G. Kusche, J. Faculty Aerospace Engineering Department Delft Institute of Earth Observation and Space Systems Date 2007-06-30 Abstract We develop and apply an efficient strategy for Earth gravity field recovery from satellite gravity gradiometry data. Our approach is based upon the Paige-Saunders iterative least-squares method using QR decomposition (LSQR). We modify the original algorithm for space-geodetic applications: firstly, we investigate how convergence can be accelerated by means of both subspace and block-diagonal preconditioning. The efficiency of the latter dominates if the design matrix exhibits block-dominant structure. Secondly, we address Tikhonov-Phillips regularization in general. Thirdly, we demonstrate an effective implementation of the algorithm in a high-performance computing environment. In this context, an important issue is to avoid the twofold computation of the design matrix in each iteration. The computational platform is a 64-processor shared-memory supercomputer. The runtime results prove the successful parallelization of the LSQR solver. The numerical examples are chosen in view of the forthcoming satellite mission GOCE (Gravity field and steady-state Ocean Circulation Explorer). The closed-loop scenario covers 1 month of simulated data with 5 s sampling. We focus exclusively on the analysis of radial components of satellite accelerations and gravity gradients. Our extensions to the basic algorithm enable the method to be competitive with well-established inversion strategies in satellite geodesy, such as conjugate gradient methods or the brute-force approach. In its current development stage, the LSQR method appears ready to deal with real-data applications. Subject Least-squaresIterative solversQR decompositionPreconditioningGravity field recoveryGOCEParallel computing To reference this document use: http://resolver.tudelft.nl/uuid:04d092e0-d8a1-4a91-95f1-153daf71a8dd Publisher Springer ISSN 1432-1394 Source Journal of Geodesy, 82 (4-5) Part of collection Institutional Repository Document type journal article Rights (c) 2007 Springer Files PDF baur_2008.pdf 432.07 KB Close viewer /islandora/object/uuid:04d092e0-d8a1-4a91-95f1-153daf71a8dd/datastream/OBJ/view