Design of a Low Micro Vibration High Precision CubeSat Reaction Wheel

Rolling element bearings are known to generate higher order harmonics. These harmonics can reach up to the 10th or higher engine order [1]. When wheels are used in a wide speed range, these higher order harmonics can pass and excite rotor eigenfrequencies and rotor modes, severely increasing the exported μ-vibrations at these frequencies. The amplification of these frequencies will then be governed by the quality factor (Q-factor) of the rotor. Single piece rotors have several advantages such as affordable tight tolerances, uniform mass and elimination of assembly errors, but such monolithic metallic structure feature high Q-factors. Material choice is a first way to address this [2], but damping will stay limited. To further increase the internal damping and reduce the Q-factor, Constrained layer damping is employed

CubeSpec, A Mission Overview

CubeSpec is an in-orbit demonstration CubeSat mission in the ESA technology programme, developed and funded in Belgium. The goal of the mission is to demonstrate high-spectral-resolution astronomical spectroscopy from a 6-unit CubeSat. The prime science demonstration case for the in-orbit demonstration mission is to unravel the interior of massive stars using asteroseismology by high-cadance monitoring of the variations in spectral line profiles during a few months. The technological challenges are numerous. The 10x20cm aperture telescope and echelle spectrometer have been designed to fit in a 10x10x20cm volume. Under low-Earth orbit thermal variations, maintaining the fast telescope focus and spectrometer alignment is achieved via an athermal design. Straylight rejection and thermal shielding from the Sun and Earth infrared flux is achieved via deploying Earth and Sunshades. The narrow spectrometer slit requires arcsecond-level pointing stability using a performant 3-axis wheel stabilised attitude control system with star tracker augmented with a fine beam steering mechanism controlled in closed loop with a guiding sensor. The high cadence, long-term monitoring requirement of the mission poses specific requirements on the orbit and operational scenarios to enable the required sky visibility. CubeSpec is starting the implementation phase, with a planned launch early 2024

Star Tracker Algorithms and a Low-Cost Attitude Determination and Control System for Space Missions

The attitude determination and control system determines and controls the orientation of the spacecraft. This system is crucial in the majority of space missions to e.g. point a camera to a star or direct an antenna to a ground station. Increasingly complex missions drive the need for higher accuracy, while the growing number of small spacecraft requires high robustness and low computational cost. This work focusses on the star tracker, a sensor that takes an image of the stars and compares it to a database with known star positions to determine the spacecraft attitude. Algorithms are developed with high accuracy, high robustness and low computational cost. A full attitude determination and control system for a class of nanosatellites, called CubeSats, is also presented. The centroiding algorithm determines the centroid of stars in the camera image. The developed algorithm uses closed form expressions to fit a model to the measured star data. The use of model fitting leads to high accuracy, while the closed form expressions keep the computational cost low. The accuracy is in the range of the most accurate algorithms and the computational cost is in the range of the fastest algorithms. The lost-in-space algorithm matches the stars in the camera image to stars in the database. The developed algorithm, which depends on the Shortest Distance transform is very robust to false stars, distortions in the image and missing stars. On top of that, it offers a reliable quality value for the result, which further increases the robustness. The tracking algorithm finds the transformation values between camera and database stars and determines the attitude based on these values. The AIM algorithm developed in this work is the fastest tracking algorithm available. Its novel approach to solving the tracking problem can be exploited to increase the robustness and decrease the computational cost. The algorithms deliver similar accuracy as the most accurate state of the art algorithms. Their computational cost is lower and they have higher robustness. These algorithms and the reaction wheels designed at KU Leuven are enablers for a high accuracy attitude determination and control system for CubeSats. A low-cost high accuracy attitude determination and control system for CubeSats is under development at KU Leuven. The system delivers high pointing accuracy for low volume, weight and power consumption. It opens up potential for small satellite missions that have higher demands on the pointing accuracy. The system is introduced and its performance is analysed in simulations.status: publishe

A Highly Efficient Attitude Estimation Algorithm for Star Trackers Based on Optimal Image Matching

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. © 2012 by Tjorven Delabie.status: publishe

Low-cost Attitude Determination and Control System Using Reaction Wheels and Star Tracker

In this paper, the development of a performant and accurate Attitude Determination and Control System (ADCS) for Cubesats is presented. On top of using magnetometers and gyroscopes, this ADCS will comprise a Star Tracker with novel star tracking algorithms. The Star Tracker will give the CubeSat highly accurate attitude knowledge. The star tracking algorithms are significantly more robust and faster than existing algorithms. To control the attitude, the ADCS uses three reaction wheels with the highest momentum capacity over weight ratio of all existing CubeSat reaction wheels. The characteristics of this ADCS will give the CubeSat high manoeuvrability and will allow to perform a formation flying mission using differential drag.status: publishe

Bringing High-precision Pointing Knowledge to CubeSats: A Compact Star Tracker

status: publishe

Robustness and Efficiency Improvements for Star Tracker Attitude Estimation

In this paper, a star tracker attitude estimation procedure with increased robustness and efficiency, using the AIM algorithm, is presented and validated. The unique approach of the AIM algorithm allows one to introduce a reliable quality check that can be efficiently calculated. Unlike existing validation methods, this quality check not only detects that some of the data are unreliable but it also determines which star measurements are unreliable. These unreliable measurements can be removed from the data set, and a new attitude quaternion can be calculated without having to repeat the entire AIM algorithm. This greatly improves the robustness of the attitude estimation, while limiting the computational expense. Furthermore, the structure of AIM allows one to reuse previously calculated data when the change in attitude between subsequent measurements is small. This way, the efficiency of the entire attitude estimation cycle can be increased significantly. These enhancements are validated with simulated star tracker data. The results show that the improvements significantly improve the robustness and lower the computational cost of the star tracker attitude estimation. As a consequence, the overall performance of the attitude determination and control system greatly increases. The increased efficiency of the attitude estimation could also allow the use of star trackers in smaller satellite projects with smaller budgets.status: publishe

Star Tracker Cost Reduction for Small Satellites

In recent years, the great potential of small satellites has become ever clearer and small satellites are selected to perform increasingly complex missions. With this rise in mission complexity, the requirements on the Attitude Determination and Control System of the satellite increase as well. Of all the attitude determination sensors, the star tracker is by far the most accurate one. The accuracy of this sensor is in the order of arc seconds. The disadvantages of this sensor are that it is expensive, takes a considerable volume, and has a high power consumption. In this paper, we will discuss the star tracker developments that are currently being done at the KU Leuven University. These star tracker developments are part of the development of an ADCS for the SIMBA Mission, which is scheduled to launch within the QB50 campaign. In the first part of this paper we discuss how the novel star tracker algorithms developed at KUL can reduce the cost of the Star Tracker. Both the centroiding algorithm and the tracking algorithm have a significantly reduced computational cost, thanks to analytical solutions of the optimization problem. This can allow to save costs in the electronical hardware and will reduce the strain on the power budget. Furthermore, the star identification algorithm and tracking algorithm are significantly more robust to inaccurate measurements. This allows to yield high accuracy, even with lower cost components. The algorithms will be presented and we will focus on the increased efficiency. In a second part, we discuss the tests that are performed to analyse the performance of the star tracker. For small satellites, testing procedures are often not as standardized as they generally are for satellite missions. As the SIMBA CubeSat is currently being developed as ESA’s first CubeSat through an ESA GSTP project, the test campaign of the KUL star tracker will adhere as strictly as possible to the standards set by ESA. The procedures that are followed will be outlined in this paper and may serve as a guideline for future star tracker test campaigns. This may help to reduce the time and money needed to devise and set up a test campaign for future missions. Since setting up a test campaign is often a serious strain on the manpower and financial budget, this could lead to a serious reduction in cost and lead time. An outlined procedure would also facilitate the comparison between different star trackers on the market and would allow small satellite developers to select the best star tracker for their mission. Both the novel star tracker algorithms and developed testing procedures will allow to make the accurate star tracker more accessible for small satellites. The increased attitude knowledge accuracy that this sensor brings to the satellite platform will allow small satellites to perform even more complex and interesting missions. This will again lead to new opportunities and new developments for this growing group of satellites.status: accepte

Highly Efficient Attitude Estimation Algorithm for Star Trackers Using Optimal Image Matching

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). In tests, AIM proved to be as robust as the most robust existing methods, and faster than the fast iterative methods. On top of this, AIM allows us in a lot of cases to eliminate a 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 allows us to obtain the attitude estimates at a higher rate, implement more accurate centroiding algorithms or use more stars in the attitude estimation algorithm, 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.status: publishe

An Accurate and Efficient Gaussian Fit Centroiding Algorithm for Star Trackers

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. This reduction in 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.status: publishe