High-Resolution Millimeter-Wave Ground-Based SAR Imaging via Compressed Sensing
| Autor: | Rae-Seoung Park, Jong-mann Kim, Sang-Hoon Jung, Hyun-Kyo Jung, Yong-Sun Cho, Young-Seek Chung |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Iterative method
Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies 020206 networking & telecommunications 02 engineering and technology Iterative reconstruction Discrete Fourier transform Electronic Optical and Magnetic Materials Image (mathematics) Compressed sensing Extremely high frequency 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Greedy algorithm Algorithm 021101 geological & geomatics engineering Sparse matrix |
| Zdroj: | IEEE Transactions on Magnetics. 54:1-4 |
| ISSN: | 1941-0069 0018-9464 |
| DOI: | 10.1109/tmag.2017.2764949 |
| Popis: | Compressed sensing (CS) is a technique which reconstructs an approximated full image using reduced samples. With the CS technique, the measurement time is reduced and high-resolution reconstructed data are obtained. On the other hand, the computational time is increased because the CS algorithm requires slightly more time than conventional reconstruction algorithms. Therefore, reducing the computational time is a critical issue. In this paper, an improved CS algorithm is proposed. The proposed algorithm is based on a greedy algorithm which solves CS problems using an iteration method. By reducing the number of iterations, the computational time of the proposed algorithm is reduced. The proposed CS algorithm is applied to a simple discrete Fourier transform problem and to millimeter-wave ground-based synthetic aperture radar imaging for verification. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|