Robust widely linear beamforming via an IAA Method for the augmented IPNCM reconstruction

Jiangbo Liu, Guan Gui, Wei Xie, Xunchao Cong, Qun Wan, Fumiyuki Adachi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Based on the reconstruction of the augmented interferenceplus-noise (IPN) covariance matrix (CM) and the estimation of the desired signal's extended steering vector (SV), we propose a novel robust widely linear (WL) beamforming algorithm. Firstly, an extension of the iterative adaptive approach (IAA) algorithm is employed to acquire the spatial spectrum. Secondly, the IAA spatial spectrum is adopted to reconstruct the augmented signal-plus-noise (SPN) CM and the augmented IPNCM. Thirdly, the extended SV of the desired signal is estimated by using the iterative robust Capon beamformer with adaptive uncertainty level (AU-IRCB). Compared with several representative robust WL beamforming algorithms, simulation results are provided to confirm that the proposed method can achieve a better performance and has a much lower complexity.

Original languageEnglish
Pages (from-to)1562-1566
Number of pages5
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE100A
Issue number7
DOIs
Publication statusPublished - 2017 Jul

Keywords

  • Interference covariance matrix reconstruction
  • Iterative adaptive approach
  • Iterative robust Capon beamformer
  • Signal steering vector estimation
  • Widely linear beamforming

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics

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