NDLI: Improved OP approach utilising correlated projection and eigenspace processing for robust adaptive beamforming

Content Provider	IET Digital Library
Author	Yan, Lu Piao, Shengchun Xu, Feng Yang, Juan
Abstract	The capability of orthogonal projection (OP) approach degrades severely in the presence of array model mismatch, especially when the training samples are mixed with the strong desired signal. Therefore, an improved OP robust adaptive beamforming is proposed based on correlated projection and eigenspace processing in wide input signal-to-noise ratio to remove the desired signal self-null effect and improve robustness. In the proposed approach, the interference subspace is constructed combining the correlated projection and eigenspace processing first. Then, the interference-plus-noise covariance matrix is accurately reconstructed via super-resolution spatial spectrum estimator to eliminate desired signal from sample covariance matrix. Subsequently, the desired signal steering vector is corrected applying correlated projection and then the adaptive weighted vector is modified by OP approach. Simulation results demonstrate that the capability of the proposed approach is almost consistently same as the optimal beamformer in many scenarios.
Starting Page	1170
Ending Page	1172
Page Count	3
ISSN	00135194
Volume Number	55
e-ISSN	1350911X
Issue Number	Issue 22, Oct (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/55/22
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2019.1337
Journal	Electronics Letters
Publisher Date	2019-09-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Weighted Vector Algebra Array Model Mismatch Array Signal Processing Correlated Projection Covariance Matrices Desired Signal Steering Vector Direction of Arrival Estimation Eigenspace Processing Electromagnetic Compatibility Improved OP Robust Adaptive Beamforming Interference Interference-plus-noise Covariance Matrix Optimal Beamformer Orthogonal Projection Sample Covariance Matrix Signal Processing And Detection Signal Processing Theory Signal Reconstruction Signal Resolution Strong Desired Signal Super-resolution Spatial Spectrum Estimator Training Sample Vector Wide Input Signal-to-noise Ratio
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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