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Error analysis of satellite attitude determination using a vision-based approach
Institution:1. ARCES – University of Bologna, Via Toffano 2/2, 40125 Bologna, Italy;2. DISI (Department of Computer Science and Engineering), University of Bologna, Viale Risorgimento, 2, 40136 Bologna, Italy;1. Max Planck Institute for Solar System Research, Justus-von-Liebig-Weg 3, 37077 Göttingen, Germany;2. Planetary Science Institute, Tuscon, AZ 85719, USA;1. Dipartimento di Scienza e Alta Tecnologia, Università dell’Insubria, Como 22100, Italy;2. Department of Mathematical Sciences, Kent State University, Kent, OH 44242, USA;1. Universidad de Valladolid, Spain;2. Applied Physics Department, Architecture School, Universidad de Valladolid, Spain;3. Applied Physics Department, Industrial Engineers School, Universidad de Valladolid, Spain;4. Institute for Sustainable Construction, Edinburgh Napier University, Edinburgh, Scotland, UK;1. Department of Remote Sensing and Geoinformation Engineering, Southwest Jiaotong University, Chengdu, China;2. College of Communication Engineering, Chongqing University, Chongqing, China
Abstract:Improvements in communication and processing technologies have opened the doors to exploit on-board cameras to compute objects’ spatial attitude using only the visual information from sequences of remote sensed images. The strategies and the algorithmic approach used to extract such information affect the estimation accuracy of the three-axis orientation of the object.This work presents a method for analyzing the most relevant error sources, including numerical ones, possible drift effects and their influence on the overall accuracy, referring to vision-based approaches. The method in particular focuses on the analysis of the image registration algorithm, carried out through on-purpose simulations. The overall accuracy has been assessed on a challenging case study, for which accuracy represents the fundamental requirement. In particular, attitude determination has been analyzed for small satellites, by comparing theoretical findings to metric results from simulations on realistic ground-truth data. Significant laboratory experiments, using a numerical control unit, have further confirmed the outcome.We believe that our analysis approach, as well as our findings in terms of error characterization, can be useful at proof-of-concept design and planning levels, since they emphasize the main sources of error for visual based approaches employed for satellite attitude estimation. Nevertheless, the approach we present is also of general interest for all the affine applicative domains which require an accurate estimation of three-dimensional orientation parameters (i.e., robotics, airborne stabilization).
Keywords:Vision  Image registration  Error analysis  Accuracy analysis  Satellite  Feature tracking
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