Weighted Total Least Squares Algorithm with Inequality Constraints

doi:10.13485/j.cnki.11-2089.2014.0173

Abstract

Abstract:

Since the inequality-constrained total least squares (ICTLS) is strongly limited due to the combinational difficulty, we investigate to adjust the partial errors-in-variables

(EIV) model which is equipped with inequality constraints. In this paper, we reconfigure the original ICTLS problem to a standard optimization problem, which can be

solved by existing methods such as penalty based methods. The novel ICWTLS (inequality-constrained Weighted TLS) algorithm can deal with the ICTLS problem with a

structure coefficient matrix and a general weight matrix, and successfully avoid the combinatorial difficulty. The examples illustrate that the new algorithm proposed in this 　

paper is efficient and simple, which can be used in a general case in practice.

Key words: total least squares, errors-in-variables model, inequality constraints, nonlinear program

CLC Number:

p207

ZENG Wenxian FANG Xing LIU Jingnan. Weighted Total Least Squares Algorithm with Inequality Constraints[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(10): 1013-1018.

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Weighted Total Least Squares Algorithm with Inequality Constraints

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