Session

Session XII: Advanced Technologies II

Location

Utah State University, Logan, UT

Abstract

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.

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Aug 8th, 11:15 AM

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

Utah State University, Logan, UT

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.