Abstract

AbstractThe integration of multi‐source earth observation data has become one of the most important developments in photogrammetry. A combined adjustment with linear array and frame array imagery (CALFI) is established in this paper. The mathematical model of CALFI is based on the conventional single‐source bundle adjustment. A revised recursive partitioning technique is utilised to solve the large normal matrix of CALFI; the orientation parameters of the linear array imagery are arranged at the border of the reduced normal matrix to save both memory and computation time. The experimental results on simulated data show that both the accuracy and the condition index of the CALFI model are superior to the conventional bundle adjustment model with either linear array or frame array imagery separately due to the higher redundancy.

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