Open AccessSpectral‐factorisation Root‐MUSIC algorithm for super‐resolution ISAR imaging
Author(s) -
Liu Qiuchen,
Wang Yong
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0575
Subject(s) - inverse synthetic aperture radar , root (linguistics) , computer science , resolution (logic) , algorithm , artificial intelligence , radar , radar imaging , telecommunications , linguistics , philosophy
Inverse synthetic aperture radar (ISAR) is widely used in both military and civil fields recently. The fast Fourier transformation is the conventional method to obtain high‐resolution ISAR images, but it is Rayleigh limited and has high sidelobes. Root‐MUSIC served as a super‐resolution method can break the Rayleigh limit. Whereas Root‐MUSIC has computational redundancy as its roots are presented as conjugated pairs. Here, a spectral factorisation Root‐MUSIC (SF‐Root‐MUSIC) is proposed for super‐resolution ISAR imaging. SF‐Root‐MUSIC efficiently reduces the order of rooting‐polynomial of Root‐MUSIC into half and has a similar resolution ability as Root‐MUSIC. The computational complexity of SF‐Root‐MUSIC is significantly reduced compared to Root‐MUSIC. Simulated signal, MIG‐25 data, and real measured Yak‐42 data are employed to validate the validity of the proposal.