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Copernical Team
One-third of galaxy's most common planets could be in habitable zone
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![](https://www.spxdaily.com/images-bg/kepler-186f-habitable-zone-bg.jpg)
New study provides novel insights into the cosmic evolution of amino acids
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![](https://www.spxdaily.com/images-bg/protein-structures-hyperpolarisation-makes-amino-acids-building-blocks-bg.jpg)
Quest for alien signals in the heart of the Milky Way takes off
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![](https://www.spxdaily.com/images-bg/technosignatures-breakthrough-listen-investigation-for-periodic-spectral-signals-blipss-bg.jpg)
AFRL helps NASA test equipment for Artemis II Mission
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![](https://www.spxdaily.com/images-bg/artemis-ii-2-mission-trajectory-profile-bg.jpg)
SpaceX Dragon carrying Axiom crew splashes down off coast of Florida
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![](https://www.spxdaily.com/images-bg/axiom-space-crew-mission-ax-2-team-photo-bg.jpg)
BeetleSat conducts two-way data communication using proprietary expandable antenna
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![](https://www.spxdaily.com/images-bg/beetlesat-nslcomm-fully-deployed-shape-memory-ka-antenna-factory-bg.jpg)
China aims to make manned moon landing before 2030
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![](https://www.spxdaily.com/images-bg/chang-e-5-robotic-probe-plants-china-national-flag-moon-lunar-surface-bg.jpg)
Launch signals wider-opening space sector for China
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![](https://www.spxdaily.com/images-bg/china-long-march-2f-carrier-rocket-shenzhou-xii-field-flowers-flags-bg.jpg)
Register for ESA’s first Earth observation commercialisation event
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![Earth Observation Commercialisation Forum](https://www.esa.int/var/esa/storage/images/esa_multimedia/images/2023/05/earth_observation_commercialisation_forum/24902062-1-eng-GB/Earth_Observation_Commercialisation_Forum_card_full.jpg)
Registration is now open for ESA’s first-ever Earth Observation Commercialisation Forum. Taking place at ESA Headquarters in Paris from 30 to 31 October 2023, investors, institutions, entrepreneurs and companies of any size from the Earth observation sector will now be able to come together and discuss the commercial potential and challenges of Earth observation, together with the technical, industrial and risk-capital support available to European companies.
Researchers propose a deep neural network-based 4-quadrant analog sun sensor calibration
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![The calibration and testing platform of the sun sensor. Credit: Space: Science & Technology Researchers proposed a deep neural network-based 4-quadrant analog sun sensor calibration](https://scx1.b-cdn.net/csz/news/800a/2023/researchers-proposed-a.jpg)
A spacecraft can estimate the attitude state by comparing external measurements from attitude sensors with reference information. CubeSats tend to use 4-quadrant analog solar sensors which have the advantages of extremely low power consumption, minimal volume, low complexity, low cost, and high reliability as attitude sensors, considering the limitation of satellite volume and payload. The performance of the sensor can be importantly improved by the calibration procedure and compensation model.
However, the various error sources affecting the calibration of the 4-quadrant sun sensor lead to a complicated process of compensation model establishment. Deep learning, which is widely used in the aerospace field in recent years, is able to approximate any continuous function on a bounded closed set, providing new ideas for solving the traditional problem.
In a research paper recently published in Space: Science & Technology, authors from Northwestern Polytechnical University, German Aerospace Center, and Dalian University of Technology together propose a method to calibrate sun sensors by deep learning, which not only is able to integrate the influence of various errors but also avoids the need of analyzing and modeling every single error.