Approximations of the GOCE error variance-covariance matrix for least-squares estimation of height datum offsets
نویسندگان
چکیده
منابع مشابه
Approximations of the GOCE error variance-covariance matrix for least-squares estimation of height datum offsets
One main geodetic objective of the European Space Agency’s satellite mission GOCE (gravity eld and steady-state ocean circulation explorer) is the contribution to global height system uni cation. This can be achieved by applying the Geodetic Boundary Value Problem (GBVP) approach. Thereby one estimates the unknown datum offsets between different height networks (datum zones) by comparing the ph...
متن کاملLeast-Squares Covariance Matrix Adjustment
We consider the problem of finding the smallest adjustment to a given symmetric n × n matrix, as measured by the Euclidean or Frobenius norm, so that it satisfies some given linear equalities and inequalities, and in addition is positive semidefinite. This least-squares covariance adjustment problem is a convex optimization problem, and can be efficiently solved using standard methods when the ...
متن کاملRange Image Sequence Analysis by 2.5-d Least Squares Tracking with Variance Component Estimation and Robust Variance Covariance Matrix Estimation
In this article, a range image sequence tracking approach is proposed, which combines 3-D camera intensity and range observations in an integrated geometric transformation model. Based on 2-D least squares matching, a closed solution for intensity and range observations has been developed. By combining complementary information, an increase in accuracy and reliability can be achieved. The weigh...
متن کاملCovariance shaping least-squares estimation
A new linear estimator is proposed, which we refer to as the covariance shaping least-squares (CSLS) estimator, for estimating a set of unknown deterministic parameters x observed through a known linear transformation H and corrupted by additive noise. The CSLS estimator is a biased estimator directed at improving the performance of the traditional least-squares (LS) estimator by choosing the e...
متن کاملLeast-squares variance component estimation
Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a userdefined weight matrix; and it is attractive because it allows one to directly apply the existing body of knowledge of L...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Geodetic Science
سال: 2012
ISSN: 2081-9943
DOI: 10.2478/v10156-011-0049-0