The Helmert–Wolf blocking (HWB) is a least squares solution method for the solution of a sparse block system of linear equations.[1] It was first reported by F. R. Helmert for use in geodesy problems in 1880;[2] H. Wolf (1910–1994) published his direct semianalytic solution in 1978.[3][4] It is based on ordinary Gaussian elimination in matrix form[5] or partial minimization form.[6]
Description
Limitations
The HWB solution is very fast to compute but it is optimal only if observational errors do not correlate between the data blocks. The generalized canonical correlation analysis (gCCA) is the statistical method of choice for making those harmful cross-covariances vanish. This may, however, become quite tedious depending on the nature of the problem.
Applications
The HWB method is critical to satellite geodesy and similar large problems.[citation needed] The HWB method can be extended to fast Kalman filtering (FKF) by augmenting its linear regression equation system to take into account information from numerical forecasts, physical constraints and other ancillary data sources that are available in realtime. Operational accuracies can then be computed reliably from the theory of minimum-norm quadratic unbiased estimation (Minque) of C. R. Rao.
See also
Notes
- ^ Dillinger, Bill (4 March 1999). "Making Combined Adjustments". Retrieved 6 June 2017.
- ^ Helmert, Friedrich Robert (1880). Die mathematischen und physikalischen Theorien der höheren Geodäsie, 1. Teil. Leipzig.
{{cite book}}: CS1 maint: location missing publisher (link) - ^ "The Wolf formulas". 9 June 2004. Retrieved 6 June 2017.
- ^ Wolf, Helmut (April 1978). "The Helmert block method—its origins and development". Proceedings of the second International Symposium on Problems Related to the Redefinition of North American Geodetic Networks. International Symposium on Problems Related to the Redefinition of North American Geodetic Networks. Arlington, Virginia: U.S. Dept. of Commerce. pp. 319–326.
- ^ Strang, Gilbert; Borre, Kai (1997). Linear algebra, geodesy, and GPS. Wellesley: Wellesley-Cambridge Press. pp. 507-508. ISBN 9780961408862.
- ^ Leick, A.; Rapoport, L.; Tatarnikov, D. (2015). GPS Satellite Surveying. Wiley. p. 673. ISBN 978-1-119-01828-5. Retrieved 2022-01-30.
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