Open AccessFractionally Nyquist Sample Spaced ARMA Blind Equalizer for Direct Signal Recovery in Passive Bistatic Radar
Author(s) -
Wang Feng,
Shen Wei,
Jiang Defu,
Wei Shuang
Publication year - 2017
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2017.01.010
Subject(s) - bistatic radar , equalizer , signal (programming language) , passive radar , computer science , nyquist–shannon sampling theorem , acoustics , radar , telecommunications , physics , channel (broadcasting) , radar imaging , computer vision , programming language
This paper proposes a modified signal processing structure based on the fractionally Nyquist sample spaced structure for passive bistatic radar. To recover the direct signal from the multipath clutter, an equalizer of the Auto regressive moving average (ARMA) type is proposed based on the fractionally Nyquist sample spaced constant modulus algorithm. Compared with the conventional Nyquist sample spaced equalizer, the equalizer of the fractionally Nyquist sample spaced ARMA structure is more effective in dealing with deep fading multipath channels with zeros near the unit circle. Computer simulations and real data tests indicate that the proposed approach outperforms the conventional processing structure in terms of both clutter residual and mean square error.