Basic concepts of L(1) norm minimization for surveying applications

被引：41

作者：

Marshall, J

Bethel, J

机构：

[1] Surv. Engrg. Area, School of Civ. Engrg., Purdue Univ., West Lafayette

[2] Dept. of Civ. Engrg., Surv. Engrg. Area/Sch. Civ. Engrg., Purdue Univ., West Lafayette, IN

来源：

JOURNAL OF SURVEYING ENGINEERING-ASCE | 1996年 / 122卷 / 04期

关键词：

D O I：

10.1061/(ASCE)0733-9453(1996)122:4(168)

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

L(1) norm minimization is a powerful mathematical tool used in surveying to detect gross errors in survey data. We describe the basic theory underlying L(1) norm estimation and its implementation through linear programming and the simplex method. Two numerical examples describe linear and nonlinear L(1) estimation. The first example illustrates the process of computing the L(1) norm parameter estimate (median) of a quantity observed directly three times. The second example describes L(1) norm estimation for a typical survey network with distances, angles, and weights.

引用

页码：168 / 179

页数：12

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