Optimisation of Least Squares Algorithm: A Study of Frame Based Programming Techniques in Horizontal Networks

TL;DR

This paper explores optimizing least squares algorithms using frame-based programming techniques within horizontal networks, aiming to improve efficiency and automation in dynamic Geomatics Engineering environments.

Contribution

It introduces a novel one-step automated least squares approach utilizing frames and object-oriented programming for better error handling and adaptability.

Findings

Enhanced automation in least squares estimation

Improved error analysis through frame-based methods

Potential for application in dynamic Geomatics environments

Abstract

Least squares estimation, a regression technique based on minimisation of residuals, has been invaluable in bringing the best fit solutions to parameters in science and engineering. However, in dynamic environments such as in Geomatics Engineering, formation of these equations can be very challenging. And these constraints are ported and apparent in most program models, requiring users at ease with the subject matter. This paper reviews the methods of least squares approximation and examines a one-step automated approach, with error analysis, through the instrumentality of frames, object oriented programming.