| Citation: | WU Bei-chen, LIU Song-hao, ZHANG Xing-xiang, LI Guo-ning, Fu Tian-jiao. Information matrix-based optimal configuration and fusion attitude determination for multi-fov star sensors[J]. Chinese Optics. doi: 10.37188/CO.2026-0099
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Narrow-FOV, long-focal-length star sensors suffer from roll-axis degradation and ill-conditioned observation geometry. This paper builds a weighted global Fisher information matrix model. A-, D-, and E-optimality criteria are used to derive optimal multi-FOV pointing relations. A multi-sensor Wahba fusion (MSWF) method is then developed. The analysis shows that orthogonal two-FOV and three-FOV configurations, and a tetrahedral four-FOV configuration, improve three-axis information distribution under equal weights. Simulations with a dual-FOV off-axis TMA star sensor show that the ill-conditioned-axis error of a single FOV is about 38 times that of the other axes. The orthogonal dual-FOV configuration with MSWF reduces the total attitude error by 95.4% relative to a single FOV and by 29.2% relative to simple averaging. It also maintains balanced three-axis performance under sparse-star, random-loss, and motion-blur conditions. The results show that optimized multi-FOV geometry and weighted star-vector fusion can mitigate the geometric limitation of a single FOV.
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