Urban Geospatial Information Acquisition Mobile Mapping System based on close-range photogrammetry and IGS site calibration. Issue 4 (2nd October 2021)

• Record Type: Journal Article
• Authors: Guo, Ming; Zhou, Yuquan; Zhao, Jianghong; Zhou, Tengfei; Yan, Bingnan; Huang, Xianfeng
• Is Part Of: Geo-spatial information science. Volume 24:Issue 4(2021)
• Page Start: 558
• Page End: 579
• Publication Date: 2021-10-02
• Subjects: Mobile Mapping System (MMS) -- close-range photogrammetry -- International GNSS Service (IGS) -- MMS calibration -- accuracy evaluation; Geographic information systems -- Periodicals; Cartography -- Data processing -- Periodicals; Surveying -- Data processing -- Periodicals; Remote sensing -- Periodicals; 526.0285
• DOI: 10.1080/10095020.2021.1924084
• Languages: English
• ISSNs: 1009-5020

Abstract

ABSTRACT: The measurement accuracy of the Mobile Mapping System (MMS) is the main problem, which restricts its development and application, so how to calibrate the MMS to improve its measurement accuracy has always been a research hotspot in the industry. This paper proposes a position and attitude calibration method with error correction based on the combination of the feature point and feature surface. First, the initial value of the spatial position relationship between each sensor of MMS is obtained by close-range photogrammetry. Second, the optimal solution for error correction is calculated by feature points in global coordinates jointly measured with International GNSS Service (IGS) stations. Then, the final transformation parameters are solved by combining the initial values obtained originally, thereby realizing the rapid calibration of the MMS. Finally, it analyzed the RMSE of MMS point cloud after calibration, and the results demonstrate the feasibility of the calibration approach proposed by this method. Under the condition of a single measurement sensor accuracy is low, the plane and elevation absolute accuracy of the point cloud after calibration can reach 0.043 m and 0.072 m, respectively, and the relative accuracy is smaller than 0.02 m. It meets the precision requirements of data acquisition for MMS. It is of great significance for promoting the development of MMS technology and the application of some novel techniques in the future, such as autonomous driving, digital twin city, urban brain et al.