Title
Fast high-quality three-dimensional reconstruction from compressive observation of phased array weather radar.
Abstract
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.
Year
Venue
Field
2017
Asia-Pacific Signal and Information Processing Association Annual Summit and Conference
Frequency domain,Weather radar,Computer science,Phased array,Algorithm,Convex function,Acceleration,PAWR,Convex optimization,Compressed sensing
DocType
ISSN
Citations 
Conference
2309-9402
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Ryosuke Kawami100.68
Hidetomo Kataoka201.01
Daichi Kitahara3106.43
Akira Hirabayashi41615.38
Takashi Ijiri524218.34
Shigeharu Shimamura611.75
Hiroshi Kikuchi744.62
Tomoo Ushio88326.04