Efficient GOCE satellite gravity field recovery based on least-squares using QR decomposition |
| |
Authors: | Oliver Baur Gerrit Austen Jürgen Kusche |
| |
Institution: | 1. Institute of Geodesy, Universit?t Stuttgart, Geschwister-Scholl-Str. 24D, 70174, Stuttgart, Germany 2. Delft Institute of Earth Observation and Space Systems (DEOS), Delft University of Technology, Kluyverweg 1, 2629 HS, Delft, The Netherlands 3. Department of Geodesy and Remote Sensing, GFZ Potsdam, Telegrafenberg, Germany
|
| |
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. |
| |
Keywords: | Least-squares Iterative solvers QR decomposition Preconditioning Gravity field recovery GOCE Parallel computing |
本文献已被 SpringerLink 等数据库收录! |
|