Fast high-quality three-dimensional reconstruction from compressive observation of phased array weather radar

Ryosuke Kawami, Hidetomo Kataoka, Daichi Kitahara, Akira Hirabayashi, Takashi Ijiri, Shigeharu Shimamura, Hiroshi Kikuchi, Tomoo Ushio

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Phased array weather radar (PAWR) is capable of spatially and temporally high resolution observation. This means that a PAWR generates a huge amount of observation data, say 500 megabytes in every 30 seconds. To transfer this big data in a public internet line, this paper proposes a fast 3D compressive sensing method for PAWR. The proposed method reconstructs the original data, from compressed data, as the minimizer of a convex function which evaluates the local similarity in the spatial domain and the sparsity in the frequency domain. By combining blockwise optimization with Nesterov's acceleration, we obtain an approximate solution of the above convex optimization problem at high speed. Numerical simulations show that the proposed method outperforms conventional reconstruction methods.

本文言語English
ホスト出版物のタイトルProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ44-49
ページ数6
2018-February
ISBN(電子版)9781538615423
DOI
出版ステータスPublished - 2018 2 5
イベント9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 - Kuala Lumpur, Malaysia
継続期間: 2017 12 122017 12 15

Other

Other9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
CountryMalaysia
CityKuala Lumpur
Period17/12/1217/12/15

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Information Systems
  • Signal Processing

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