A High-accuracy Extraction Algorithm of Planet Centroid Image in Deep-space Autonomous Optical Navigation. (23rd December 2015)

• Record Type: Journal Article
• Authors: Du, Siliang; Wang, Mi; Chen, Xiao; Fang, Shenghui; Su, Hongbo
• Is Part Of: Journal of navigation. Volume 69:Number 4(2016)
• Page Start: 828
• Page End: 844
• Publication Date: 2015-12-23
• Subjects: Autonomous optical navigation, -- Planet segmentation, -- Zernike moments, -- Planet centroid; Navigation -- Periodicals; 623.8905
• DOI: 10.1017/S0373463315000910
• Languages: English
• ISSNs: 0373-4633

Abstract

Abstract : A planet centroid is an important observable object in autonomous optical navigation. A high-accuracy algorithm is presented to extract the planet centroid from its raw image. First, we proposed a planet segmentation algorithm to segment the planet image block to eliminate noise and to reduce the computation load. Second, we developed an effective algorithm based on Prewitt-Zernike moments to detect sub-pixel real edges by determining possible edges with the Prewitt operator, removing pseudo-edges in backlit shady areas, and relocating real edges to a sub-pixel accuracy in the Zernike moments. Third, we proposed an elliptical model to fit sub-pixel edge points. Finally, we verified the performance of this algorithm against real images from the Cassini-Huygens mission and against synthetic simulated images. Simulation results showed that the accuracy of the planet centroid is up to 0·3 pixels and that of the line-of-sight vector is at 2·1 × 10 −5 rad.