Lichti, Derek DPexman, KateTredoux, Wynand2022-02-032022-02-032021-07-01Lichti, D. D., Pexman, K., Tredoux, W. (2021). New method for first-order network design applied to TLS self-calibration networks. ISPRS Journal of Photogrammetry and Remote Sensing, 177, 306-318. https://doi.org/10.1016/j.isprsjprs.2021.05.0140924-2716http://hdl.handle.net/1880/11437810.11575/PRISM/46040Terrestrial laser scanning (TLS) is established as a viable means for precision measurement and the need for systematic error modelling and instrument self-calibration is well recognized. While additional parameter (AP) models and procedures for their estimation from signalized target fields have been developed, the first-order design (FOD) of TLS self-calibration networks remains an active area of research aiming to improve AP quality. The conventional FOD approach of numerical simulation carries a heavy computational burden. This paper reports a new method for TLS self-calibration FOD that avoids the high computational effort and can predict AP precision in closed form. Its basis is a relatively simple analytical model of the distribution of spherical coordinate observations, specifically the elevation angle. The accuracy of predicted AP precision is quantified by comparison of precision estimates from a more complex and detailed observation distribution model and from self-calibration. Results from 25 datasets demonstrate the high accuracy (arc second or better) of the closed-form approach. A new observation distribution model is then developed to optimize the geometric design of TLS self-calibration networks. An ideal observation distribution based on the versine function and a corresponding target field configuration that enhance AP precision are established. Testing was performed on five additional, very dense TLS self-calibration datasets. Each dataset was subsampled so as to replicate the observation distributions corresponding to conventional network design and the proposed design. The results show that up to 55% improvement in AP precision, obtained from self-calibration, can be achieved with the new design and these results agree with versine-distribution model predictions within 14% to 16%.engUnless otherwise indicated, this material is protected by copyright and has been made available with authorization from the copyright owner. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.https://creativecommons.org/licenses/by-nc-nd/4.0Terrestrial laser scanningCalibrationFirst-order designGeometric network designjournal articleRGPIN-2018-03775https://doi.org/10.1016/j.isprsjprs.2021.05.014