| Title: | GS3-5 A Data Estimation Technique for Incomplete Telemetry Data based on a Genetic Algorithm with Data' Statistical Properties |
|---|---|
| Publication: | ICAROB2018 |
| Volume: | 23 |
| Pages: | 100-104 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2018.GS3-5 |
| Author(s): | Masahiro Tokumitsu, Kaito Mikami, Fumio Asai, Taku Takada, Wakabayashi Makoto, Yoshiteru Ishida |
| Publication Date: | February 2, 2018 |
| Keywords: | social diversity, intelligent information processing, telemetry data, data estimation, genetic algorithm |
| Abstract: | Satellite in the space transmits their own mission data (so-called "telemetry data") to ground stations. The telemetry data contain a sort of data such as observations, experiments, and satellites' health status. However, the data received by the ground stations may contain errors by effects through the transmissions. This paper proposes a data estimation technique for incomplete telemetry data to attain a high availability of the received telemetry data. The proposed technique is based on a genetic algorithm with data' statistical properties. This paper firstly demonstrates the proposed technique with simple examples, and then it simulates our technique with actual telemetry data obtained by the satellite. |
| PDF File: | https://alife-robotics.co.jp/members2018/icarob/data/html/data/GS_pdf/GS3/GS3-5.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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