Helmert–Wolf blocking


The Helmert–Wolf blocking is a least squares solution method for a sparse canonical block-angular system of linear equations. Helmert reported on the use of such systems for geodesy in 1880. Wolf published his direct semianalytic solution based on ordinary Gaussian elimination in matrix form in 1978.

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 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. The HWB method can be extended to fast Kalman filtering 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 of C. R. Rao.