Journal
JOURNAL OF GEODESY
Volume 94, Issue 3, Pages -Publisher
SPRINGER
DOI: 10.1007/s00190-020-01351-1
Keywords
Robust estimation; Correlated vector observation; Bifactor equivalent weight; Maximum test statistic
Categories
Funding
- National Natural Science Foundation of China [41731069, 41504022]
Ask authors/readers for more resources
This paper develops a robust M estimation approach applied for three-dimensional (3D) correlated vector observations. A modified bifactor reduction model is constructed, where the weight shrinking factor of the 3D vector observation is determined by a new test statistic that coincides with the estimated direction of the outlier vector and thus is more sensitive to vector-type outliers than the standardized residual used for most conventional robust M methods. With the proposed bifactor reduction model, the outlying vector observation is down-weighted directly along a specific direction, rather than separately at the three components. The new equivalent weight matrix derived from the proposed bifactor model still keeps symmetry, based on which the parameter estimation procedure is developed. A real 3D control network of GNSS vector observations is processed by simulating outliers with different types, sizes and locations. The results show the effectiveness of the proposed approach by comparing with other four conventional robust M method (IGGIII, Danish, Huber and Hampel).
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available