Algorithm-Hardware Co-Design of Real-Time Edge Detection for Deep-Space Autonomous Optical Navigation

Hao XIAO  Yanming FAN  Fen GE  Zhang ZHANG  Xin CHENG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E103-D   No.10   pp.2047-2058
Publication Date: 2020/10/01
Publicized: 2020/06/15
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2020PCP0002
Type of Manuscript: Special Section PAPER (Special Section on Picture Coding and Image Media Processing)
Category: 
Keyword: 
edge detection,  autonomous optical navigation,  star centroid estimation,  real-time processing,  

Full Text: PDF>>
Buy this Article



Summary: 
Optical navigation (OPNAV) is the use of the on-board imaging data to provide a direct measurement of the image coordinates of the target as navigation information. Among the optical observables in deep-space, the edge of the celestial body is an important feature that can be utilized for locating the planet centroid. However, traditional edge detection algorithms like Canny algorithm cannot be applied directly for OPNAV due to the noise edges caused by surface markings. Moreover, due to the constrained computation and energy capacity on-board, light-weight image-processing algorithms with less computational complexity are desirable for real-time processing. Thus, to fast and accurately extract the edge of the celestial body from high-resolution satellite imageries, this paper presents an algorithm-hardware co-design of real-time edge detection for OPNAV. First, a light-weight edge detection algorithm is proposed to efficiently detect the edge of the celestial body while suppressing the noise edges caused by surface markings. Then, we further present an FPGA implementation of the proposed algorithm with an optimized real-time performance and resource efficiency. Experimental results show that, compared with the traditional edge detection algorithms, our proposed one enables more accurate celestial body edge detection, while simplifying the hardware implementation.