Adaptive phase‐singular‐unit restoration with entire‐spectrum‐processing complex‐valued neural networks in interferometric SAR | Zendy

Oyama K. | Zendy; Hirose A. | Zendy

Open Access

Adaptive phase‐singular‐unit restoration with entire‐spectrum‐processing complex‐valued neural networks in interferometric SAR

Author(s) -

Oyama K.,

Hirose A.

Publication year - 2018

Publication title -

electronics letters

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.375

H-Index - 146

eISSN - 1350-911X

pISSN - 0013-5194

DOI - 10.1049/el.2017.2680

Subject(s) - interferometry , phase (matter) , artificial neural network , computer science , synthetic aperture radar , singular spectrum analysis , spectrum (functional analysis) , unit (ring theory) , electronic engineering , physics , artificial intelligence , control theory (sociology) , algorithm , optics , mathematics , engineering , singular value decomposition , quantum mechanics , mathematics education , control (management)

A singular‐unit restoration filter based on complex‐valued neural networks that deal with spatial spectrum in interferometric synthetic aperture radar is proposed. This filter utilises more neural generalisation ability than conventional methods. In experiments, it shows a higher accuracy as well as shorter processing time than conventional real‐space filters and shorter learning time than previous spectral‐domain learning filters.

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