This paper presents a novel centroiding algorithm for star trackers. The proposed algorithm, which is referred to as the Gaussian Grid algorithm, fits an elliptical Gaussian function to the measured pixel data and derives explicit expressions to determine the centroids of the stars. In tests, the algorithm proved to yield accuracy comparable to that of the most accurate existing algorithms, while being significantly less computationally intensive. Hence, the Gaussian Grid algorithm can deliver high centroiding accuracy to spacecraft with limited computational power. Furthermore, a hybrid algorithm is proposed in which the Gaussian Grid algorithm yields an accurate initial estimate for a least squares fitting method, resulting in a reduced number of iterations and hence reduced computational cost. The low computational cost allows to improve performance by acquiring the attitude estimates at a higher rate or use more stars in the estimation algorithms. It is also a valuable contribution to the expanding field of small satellites, where it could enable low-cost platforms to have highly accurate attitude estimation.

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Context. There is currently a niche for providing high-cadence, high resolution, time-series optical spectroscopy from space, which can be filled by using a low-cost cubesat mission. The Belgian-led ESA/KU Leuven CubeSpec mission is specifically designed to provide space-based, low-cost spectroscopy with specific capabilities that can be optimised for a particular science need. Approved as an ESA in-orbit demonstrator, the CubeSpec satellite’s primary science objective will be to focus on obtaining high-cadence, high resolution optical spectroscopic data to facilitate asteroseismology of pulsating massive stars. Aims. In this first paper, we aim to search for pulsating massive stars suitable for the CubeSpec mission, specifically β Cep stars, which typically require time-series spectroscopy to identify the geometry of their pulsation modes. Methods. Based on the science requirements needed to enable asteroseismology of massive stars with the capabilities of CubeSpec’s spectrograph, we combined a literature study for pulsation with the analysis of recent high-cadence time-series photometry from the Transiting Exoplanet Survey Satellite (TESS) mission to classify the variability for stars brighter than V ≤ 4 mag and between O9 and B3 in spectral type. Results. Among the 90 stars that meet our magnitude and spectral type requirements, we identified 23 promising β Cep stars with high-amplitude (non-)radial pulsation modes with frequencies below 7 d−1. Using further constraints on projected rotational velocities, pulsation amplitudes, and the number of pulsation modes, we devised a prioritised target list for the CubeSpec mission according to its science requirements and the potential of the targets for asteroseismology. The full target catalogue further provides a modern TESS-based review of line profile and photometric variability properties among bright O9–B3 stars.

This paper presents a novel attitude estimation algorithm for spacecraft using a star tracker. The algorithm is based on an efficient approach to match the stars of two images optimally on top of each other, hence the name of the algorithm: AIM (Attitude estimation using Image Matching). AIM proved in tests to be as accurate and robust as the existing robust methods, such as q-Davenport, and faster than the fast iterative methods such as QUEST. While this is an improvement in itself, the greatest merit of AIM lies in the fact that it simplifies and in most cases allows to eliminate a very computationally intensive coordinate conversion which normally precedes the attitude estimation algorithm. The computational cost of this conversion step is several times higher than that of the attitude estimation algorithm itself, so this elimination yields a huge increase in efficiency as compared to the existing algorithms. This significant reduction in computational cost could allow to obtain the attitude estimates at a higher rate, implement more accurate centroiding algorithms or use more stars in the attitude estimation algorithms, all of which improve the performance of the attitude estimation. It could also allow the use of star trackers in the expanding field of small satellite projects, where satellite platforms have limited computational capability.