Modeling and analysis of pointing error for non-landing vehicle-mounted photoelectric theodolite

Gao, Qingjia; Wang, Chong; Liu, Yanjun; Wang, Xiaoming; Wu, Tongbang; Zhang, Haoyuan

doi:10.1007/s11801-024-3159-5

Cited by 1 publication

(1 citation statement)

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“…The azimuth range of a VSRT is 0 to 360 • , which requires pointing error correction to cover the entire operating range, unlike optical communication terminals, aerial cameras, and space optical cameras with limited azimuth. The distribution of pointing error varies in different quadrants and includes mechanical errors of the tracking frame itself as well as dynamic tracking errors, graphics processing errors, vehicle platform shaking errors, attitude sensor measurement errors, positioning and orientation instrument errors, and other sources for VSRTs [24,25]. Currently, there is a lack of reports addressing the correction of pointing error across the entire operational range of a VSRT, and a comprehensive investigation into the impacts of ranging and imaging systems on pointing error is needed.…”

Section: Introductionmentioning

confidence: 99%

Pointing Error Correction for Vehicle-Mounted Single-Photon Ranging Theodolite Using a Piecewise Linear Regression Model

Gao,

Wang,

Wang

et al. 2024

Sensors

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Pointing error is a critical performance metric for vehicle-mounted single-photon ranging theodolites (VSRTs). Achieving high-precision pointing through processing and adjustment can incur significant costs. In this study, we propose a cost-effective digital correction method based on a piecewise linear regression model to mitigate this issue. Firstly, we introduce the structure of a VSRT and conduct a comprehensive analysis of the factors influencing its pointing error. Subsequently, we develop a physically meaningful piecewise linear regression model that is both physically meaningful and capable of accurately estimating the pointing error. We then calculate and evaluate the regression equation to ensure its effectiveness. Finally, we successfully apply the proposed method to correct the pointing error. The efficacy of our approach has been substantiated through dynamic accuracy testing of a 450 mm optical aperture VSRT. The findings illustrate that our regression model diminishes the root mean square (RMS) value of VSRT’s pointing error from 17″ to below 5″. Following correction utilizing this regression model, the pointing error of VSRT can be notably enhanced to the arc-second precision level.

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Section: Introductionmentioning

confidence: 99%