Tähtede identifitseerimisalgoritmide kasutamine ESTCube-2 tähejälgimiskaameral

This thesis estimates the feasibility and determines the expected performance characteristics of a star tracker for ESTCube-2 student satellite. It measures limiting magnitude for the ESTCube- 2 star tracker hardware and estimates the decrease in signal-to-noise ratio due to the spacecraft’s rotational motion using geometric modelling. The acquired limiting magnitude is used to determine the optimal parameters to use with the pattern recognition algorithms for star identification purposes. The work also develops a way of creating and structuring a reference database in an effective way. Test results indicate that using the acquired parameters, the star tracker will be able to determine spacecraft’s attitude for cases of slow rotation up to 5 degrees per second. Results also indicate capability of attitude determination up to 10 times per second. The spacecraft’s mission also contains a phase of fast rotation, during which the star tracker will no longer be able to produce accurate attitude estimates at all times. With the algorithm configurations recommended in the thesis the ESTCube-2 star tracker could still provide a valuable contribution to the attitude and orbital control subsystem while experiencing angular velocities greater than 5 degrees per second. Thus it may outperform state-of-the-art commercial nanosatellite star trackers in that particular situation

Optimization of star research algorithm for esmo star tracker

This paper explains in detail the design and the development of a software research star algorithm, embedded on a star tracker, by the ISAE/SUPAERO team. This research algorithm is inspired by musical techniques. This work will be carried out as part of the ESMO (European Student Moon Orbiter) project by different teams of students and professors from ISAE/SUPAERO (Institut Supe ́rieur de l’Ae ́ronautique et de l’Espace). Till today, the system engineering studies have been completed and the work that will be presented will concern the algorithmic and the embedded software development. The physical architecture of the sensor relies on APS 750 developed by the CIMI laboratory of ISAE/SUPAERO. First, a star research algorithm based on the image acquired in lost-in-space mode (one of the star tracker opera- tional modes) will be presented; it is inspired by techniques of musical recognition with the help of the correlation of digital signature (hash) with those stored in databases. The musical recognition principle is based on finger- printing, i.e. the extraction of points of interest in the studied signal. In the musical context, the signal spectrogram is used to identify these points. Applying this technique in image processing domain requires an equivalent tool to spectrogram. Those points of interest create a hash and are used to efficiently search within the database pre- viously sorted in order to be compared. The main goals of this research algorithm are to minimise the number of steps in the computations in order to deliver information at a higher frequency and to increase the computation robustness against the different possible disturbances

Application of advanced technology to space automation

Automated operations in space provide the key to optimized mission design and data acquisition at minimum cost for the future. The results of this study strongly accentuate this statement and should provide further incentive for immediate development of specific automtion technology as defined herein. Essential automation technology requirements were identified for future programs. The study was undertaken to address the future role of automation in the space program, the potential benefits to be derived, and the technology efforts that should be directed toward obtaining these benefits

Development of a Star Tracker-Based Reference System for Accurate Attitude Determination of a Simulated Spacecraft

The goal of this research effort is to investigate the analysis, design, integration, testing, and validation of a complete star tracker and star field simulator system concept for AFIT\u27s satellite simulator, SimSat. Previous research has shown that while laboratory-based satellite simulators benefit from star trackers, the approach of designing the star field can contribute significant error if the star field is generated on a flat surface. To facilitate a star pattern that better represents a celestial sky, a partially hemispherical dome surface is suspended above SimSat and populated with a system of light emitting diodes of various intensities and angles of separation. Test results show that the spherical star pattern surface is effective in minimizing the effects of parallax when imaging in a finite conjugate mode and that more reliable attitude information within 1 degree of accuracy can be attained. The added capability to research star pattern recognition and attitude determination algorithms in the future is also significant

Space infrared telescope pointing control system. Automated star pattern recognition

The Space Infrared Telescope Facility (SIRTF) is a free flying spacecraft carrying a 1 meter class cryogenically cooled infrared telescope nearly three oders of magnitude most sensitive than the current generation of infrared telescopes. Three automatic target acquisition methods will be presented that are based on the use of an imaging star tracker. The methods are distinguished by the number of guidestars that are required per target, the amount of computational capability necessary, and the time required for the complete acquisition process. Each method is described in detail

Development and Initial On-orbit Performance of Multi-Functional Attitude Sensor using Image Recognition

This paper describes a multi-functional attitude sensor mounted on the “Innovative Satellite 1st” led by Japan Aerospace Exploration Agency which was launched in January 2019. In order to achieve the high accuracy determination in low cost, we developed a novel attitude sensor utilizing real-time image recognition technology, named “Deep Learning Attitude Sensor (DLAS)”. DLAS has two type of attitude sensors: Star Tracker(STT) and Earth Camera (ECAM). For the low-cost development, we adopted commercial off-the-shelf cameras. DLAS uses real-time image recognition technology and a new attitude determination algorithm. In this paper, we present the missions, methods and system configuration of DLAS and initial results of on-orbit experiment that was conducted after the middle of February 2019, and it is confirmed that attitude determinations using ECAM and STT are performed correctly

Autonomous navigation for artificial satellites

An autonomous navigation system is considered that provides a satellite with sufficient numbers and types of sensors, as well as computational hardware and software, to enable it to track itself. Considered are attitude type sensors, meteorological cameras and scanners, one way Doppler, and image correlator