Abstract
Exterior orientation parameters’ (EOP) estimation using space resection plays an important role in topographic reconstruction for push broom scanners. However, existing models of space resection are highly sensitive to errors in data. Unfortunately, for lunar imagery, the altitude data at the ground control points (GCPs) for space resection are error-prone. Thus, existing models fail to produce reliable EOPs. Motivated by a finding that for push broom scanners, angular rotations of EOPs can be estimated independent of the altitude data and only involving the geographic data at the GCPs, which are already provided, hence, we divide the modeling of space resection into two phases. Firstly, we estimate the angular rotations based on the reliable geographic data using our proposed mathematical model. Then, with the accurate angular rotations, the collinear equations for space resection are simplified into a linear problem, and the global optimal solution for the spatial position of EOPs can always be achieved. Moreover, a certainty term is integrated to penalize the unreliable altitude data for increasing the error tolerance. Experimental results evidence that our model can obtain more accurate EOPs and topographic maps not only for the simulated data, but also for the real data from Chang’E-1, compared to the existing space resection model.
Highlights
Acquiring lunar topographic data is an important mission for lunar exploration, and the push broom scanner is one of the critical optical devices carried by orbiters for acquiring stereo lunarCCD images (e.g., Chang’E-1 [1] and Chang’E-2 [2])
We mainly focus on the lunar topographic reconstruction, and existing laser altimeter measurements (LAM) data would be used to interpolate the altitude data of the ground control points
The existing space resection model [5] estimates the Exterior orientation parameters’ (EOP) by applying collinear equations, which are formulated based on the 3D coordinates of the ground control points (GCPs)
Summary
Xuemiao Xu 1, *, Huaidong Zhang 1,† , Guoqiang Han 1, *, Kin Chung Kwan 2,† , Wai-Man Pang 2 , Jiaming Fang 1 and Gansen Zhao 3.
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