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基于分段线性回归模型的车载单光子测距经纬仪指向误差校正

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

作者信息

Gao Qingjia, Wang Chong, Wang Xiaoming, Liu Zhenyu, Liu Yanjun, Wang Qianglong, Niu Wenda

机构信息

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

出版信息

Sensors (Basel). 2024 May 17;24(10):3192. doi: 10.3390/s24103192.

Abstract

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.

摘要

指向误差是车载单光子测距经纬仪(VSRT)的一项关键性能指标。通过处理和调整实现高精度指向会产生高昂成本。在本研究中,我们提出一种基于分段线性回归模型的经济高效的数字校正方法来缓解这一问题。首先,我们介绍了VSRT的结构,并对影响其指向误差的因素进行了全面分析。随后,我们建立了一个具有物理意义且能够准确估计指向误差的分段线性回归模型。然后,我们计算并评估回归方程以确保其有效性。最后,我们成功应用所提出的方法来校正指向误差。通过对一个450毫米光学孔径VSRT的动态精度测试,证实了我们方法的有效性。研究结果表明,我们的回归模型将VSRT指向误差的均方根(RMS)值从17″降低到了5″以下。利用该回归模型进行校正后,VSRT的指向误差可显著提高到弧秒精度水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a9f/11125017/52ae5c434b49/sensors-24-03192-g001.jpg

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