Assessment of Automatic Target Recognition Against Manual Aiming in Conventional Establishment of Survey Control

Lazarevic, Aleksandar (2019) Assessment of Automatic Target Recognition Against Manual Aiming in Conventional Establishment of Survey Control. [USQ Project]

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Abstract

The purpose of this project is to definitively test the aiming precision of automatic target recognition systems and the manual sighting of surveyor. To date there has been no scientific evidence found to justify the use of one method over another. This experiment aims to proves which method is more accurate and would be better suited for the establishment of survey control using a conventional total station.

The project tests the different methods of aiming to a target under various conditions, including the use of an assortment of simulated obstructions to replicate conditions often encountered during day-to-day field operations by surveyors using conventional total stations during the establishment of survey control. The project further analyses these results by the variation of observed horizontal and vertical angles from each experimental scenario. These results provided the evidence for a definitive answer as to whether the use of automatic target recognition or manual sighting is better suited for survey tasks where optimum accuracy is needed.

This project scientifically established that Trimble FineLock was the most accurate method of aiming closely followed by Manual Aiming the total station. Both of these methods produced significantly better results than what was attainable with Trimble AutoLock and should be used where possible.


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Item Type: USQ Project
Item Status: Live Archive
Additional Information: Bachelor of Spatial Science (Honours)(Surveying)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 -)
Supervisors: Smith, Jessica
Date Deposited: 11 Aug 2021 02:32
Last Modified: 11 Aug 2021 02:32
URI: http://eprints.usq.edu.au/id/eprint/43100

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