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For all common satellite attitude determination sensors, star trackers provide the most accurate measurement. However, these devices can be both large and expensive, and for some CubeSat applications it would not be suitable. Star trackers have in the past been successfully made for CubeSats. This paper investigates star tracker algorithms, implemented with a smartphone, so it may be used for testing attitude determination on a CubeSat. By testing through a proposed implementation, star centroids should be found by the moment method, stars should be identified by planar triangles, and QUEST should be used for attitude estimation. Smeared star images should be avoided and blurred images provide greater accuracy. Using these techniques, a star tracker using a smartphone may be constructed for attitude determination testing and software development, applied in the lost-in-space situation. This may be applied to QKD CubeSats, which require an attitude precision below 0.01°.

The literature since Apollo contains exhaustive material on attitude filtering, usually treating the problem of two sensors, a combination of state measuring and inertial devices. More recently, it has become popular for a sole attitude determination device to be considered. This is especially the case for a star tracker given its unbiased stellar measurement and recent improvements in optical sensor performance. The state device indirectly estimates the attitude rate using a known dynamic model. In estimation theory, two main attitude filtering approaches are classified, the additive and the multiplicative. Each refers to the nature of the quaternion update in the filter. In this article, these two techniques are implemented for the case of a sole star tracker, using simulated and real night sky image data. Both sets of results are presented and compared with each other, with a baseline established through a basic linear least square estimate. The state approach is more accurate and precise for measuring angular velocity than using the error-based filter. However, no discernible difference is observed between each technique for determining pointing. These results are important not only for sole device attitude determination systems, but also for space situational awareness object localisation, where attitude and rate estimate accuracy are highly important.

The power system is one of the most important subsystems for a successful space mission. Any failure in this subsystem leads to a direct loss of a satellite. This creates a need for a power schedule to be effectively and efficiently produced, especially if requirements are constantly changing. This paper presents the application of linear programming techniques to solving the power schedule problem, with the more specific usage of mixed-integer linear programming (MILP). The illustration of the approach is applied to a Swedish student satellite, which consists of the necessary subsystems and eight separate experiments. Two programs are developed, one studying the satellite lifetime in terms of orbital cycles and the other studying the individual orbit cycle. Simulating the lifetime of the satellite over 5000 orbit cycles, the battery level did not decline below 76.35%. Using a computer with an Intel i4 processor, this simulation took 3.2 hrs, with individual orbits taking 2.3 s each. Further work includes developing the program to be completed on-aboard the satellite, adapting to new scenarios, and incorporating a model for the decline of battery performance over time.

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This paper discusses FLAMINGO, an initiative that will provide a high accuracy positioning service to be used by mass market applications. The status and future for the initiative are discussed, the required accuracies and other location parameters are described, and the target applications are identified. Finally, the currently achieved accuracies from today's Smartphones are assessed and presented. FLAMINGO (Fulfilling enhanced Location Accuracy in the Mass-market through Initial GalileO services), part funded through the European GNSS Agency, is a collaborative venture comprising NSL (as lead organization),

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