Least-squares adjustment of large-scale geodetic networks by orthogonal decomposition
Conference
·
OSTI ID:7076783
This article reviews some recent developments in the solution of large sparse least squares problems typical of those arising in geodetic adjustment problems. The new methods are distinguished by their use of orthogonal transformations which tend to improve numerical accuracy over the conventional approach based on the use of the normal equations. The adaptation of these new schemes to allow for the use of auxiliary storage and their extension to rank deficient problems are also described.
- Research Organization:
- Waterloo Univ., Ontario (Canada). Dept. of Computer Science; Stanford Univ., CA (USA). Dept. of Computer Science; Oak Ridge National Lab., TN (USA); North Carolina State Univ., Raleigh (USA)
- DOE Contract Number:
- W-7405-ENG-26
- OSTI ID:
- 7076783
- Report Number(s):
- CONF-8108138-1; ON: DE82020905
- Country of Publication:
- United States
- Language:
- English
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