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Advanced sun-sensor processing and design for super-resolution performance

We analyze the performance of conventional and parametric super-resolution algorithms for estimating sun position in a spacecraft sun-sensor. Widely employed in other applications, we examine whether parametric algorithms can increase sensor performance without affecting the cost of the sensor system. Using a simplified model of detector illumination our simulations provide quantitative comparisons of algorithm performance and assess how simple sensor redesigns will further improve the net system performance. The first set of tests evaluates the effect of increased noise on the performance of each algorithm for both narrow-or wide-pattern, and one- or two-slit detector illumination patterns. Our findings show that parametric algorithms display very good performance throughout the test regime, particularly when using wide-pattern illumination. Better than two-fold resolution improvements over high-accuracy traditional algorithms are observed in the presence of realistic system noise. Further tests establish that multiple-peak illumination patterns enhance resolution, while wide peaks generally are impairment. These mask-dependent improvements are observed in both of the parametric algorithms and one of the traditional algorithms