title: Bundle block adjustment of airborne three-line array imagery based on rotation angles.
abstract: In the midst of the rapid developments in electronic instruments and remote sensing technologies, airborne three-line array sensors and their applications are being widely promoted and plentiful research related to data processing and high precision geo-referencing technologies is under way. The exterior orientation parameters (EOPs), which are measured by the integrated positioning and orientation system (POS) of airborne three-line sensors, however, have inevitable systematic errors, so the level of precision of direct geo-referencing is not sufficiently accurate for surveying and mapping applications. Consequently, a few ground control points are necessary to refine the exterior orientation parameters, and this paper will discuss bundle block adjustment models based on the systematic error compensation and the orientation image, considering the principle of an image sensor and the characteristics of the integrated POS. Unlike the models available in the literature, which mainly use a quaternion to represent the rotation matrix of exterior orientation, three rotation angles are directly used in order to effectively model and eliminate the systematic errors of the POS observations. Very good experimental results have been achieved with several real datasets that verify the correctness and effectiveness of the proposed adjustment models.
authors.affiliation: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China. zhangyj@whu.edu.cn.
authors.forename: Yongjun
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China. tengve@whu.edu.cn.
authors.forename: Maoteng
authors.initials: M
authors.lastname: Zheng
authors.affiliation: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China. huangxu.chess@163.com.
authors.forename: Xu
authors.initials: X
authors.lastname: Huang
authors.affiliation: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China. xalson2014@gmail.com.
authors.forename: Jinxin
authors.initials: J
authors.lastname: Xiong