Interference-plus-Noise Covariance Matrix Reconstruction via Spatial Power Spectrum Sampling for Robust Adaptive Beamforming

Zhang, Zhenyu; Liu, Wei; Wen, L.; Wang, Anguo; Shi, Heping

doi:10.1109/lsp.2015.2504954

Cited by 122 publications

(81 citation statements)

References 17 publications

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“…One approach is to estimate the interference-plus-noise matrix using prior knowledge such as array calibration and the angular sector where the desired signal is located [8,9]. The other one is to estimate the steering vector of the desired signal, with the eigenspace-based beamformer being a representative example, applicable to the arbitrary steering vector mismatch case [10].…”

Section: Introductionmentioning

confidence: 99%

Effective estimation of the desired-signal subspace and its application to robust adaptive beamforming

Zhang

Wen

Wang

et al. 2017

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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ReuseUnless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. EFFECTIVE ESTIMATION OF THE DESIRED-SIGNAL SUBSPACE AND ITS APPLICATION TO ROBUST ADAPTIVE BEAMFORMING ABSTRACTAn effective method is proposed to estimate the desired-signal (S) subspace by the intersection between the signal-plus-interference (SI) subspace and a reference space covering the angular region where the desired signal is located. The estimated S subspace is robust to steering vector mismatch and overestimation of the SI subspace, capable of detecting the relative strength of the desired signal. And even the basis of the estimated S subspace can serve as an effective estimation of the steering vector of the desired signal. With these properties, the estimated S subspace can help to select a more accurate narrow area for searching for the steering vector of the desired signal in mismatch cases. The proposed method is applied for robust adaptive beamforming with an improved performance, as demonstrated by simulation results.Index Terms-Eigenspace, intersection, robust adaptive beamforming (RAB), steering vector estimation.

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Section: Introductionmentioning

confidence: 99%

Effective estimation of the desired-signal subspace and its application to robust adaptive beamforming

Zhang

Wen

Wang

et al. 2017

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Self Cite

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“…(18), (19), and (20). Ifâ S = a S , (18), (19), and (20) are strictly true and (22) is reliable. If there exists error betweenâ S and a S , the following iterative method will reduce this error step by step so as to make (22) reliable.…”

Section: Always Holds Lemma 1 Is Obvious and It Is Easy To Be Provementioning

confidence: 98%

“…For example, the class of diagonal loading technology [9,10] augment the data covariance with a constant improves the robustness; the worst-case performance optimizationbased beamformer (WCB) [11,12] restrains the gain in signal uncertainty range that is larger than one; the covariance fitting-based beamformer [13,14] solves a new steering vector which is fitting for the sample covariance matrix to avoid desired signal cancellation; the magnitude response constraints method [15,16] improves the robustness by restraining the main beam pattern; the covariance matrix reconstruction approach [17,18] eliminates the signal component from the data covariance matrix to prevent desired signal cancellation.…”

Section: Introductionmentioning

confidence: 99%

Iterative robust adaptive beamforming

2017

EURASIP J. Adv. Signal Process.

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The minimum power distortionless response beamformer has a good interference rejection capability, but the desired signal will be suppressed if signal steering vector or data covariance matrix is not precise. The worst-case performance optimization-based robust adaptive beamformer (WCB) has been developed to solve this problem. However, the solution of WCB cannot be expressed in a closed form, and its performance is affected by a prior parameter, which is the steering vector error norm bound of the desired signal. In this paper, we derive an approximate diagonal loading expression of WCB. This expression reveals a feedback loop relationship between steering vector and weight vector. Then, a novel robust adaptive beamformer is developed based on the iterative implementation of this feedback loop. Theoretical analysis indicates that as the iterative step increases, the performance of the proposed beamformer gets better and the iteration converges. Furthermore, the proposed beamformer does not subject to the steering vector error norm bound constraint. Simulation examples show that the proposed beamformer has better performance than some classical and similar beamformers.

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“…However, because the microphone spacing is generally greater than the voice signal wavelength, with the classic adaptive beamformer based on GSC, like the Griffiths-Jim beamformer [9] and some others, slight direction estimation error will cancel part of the desired signal [10]. Many signal processing techniques, which are called robust adaptive beamforming, have been proposed to avoid the cancellation of the desired signal [11][12][13][14][15], because their performance is robust against errors. However, the problems of using GSC algorithm are not so serious while processing SLF signals.…”

Section: Introductionmentioning

confidence: 99%

Application of an Improved GSC in Tte Communication With Antenna Array

Zhang¹,

Jiang²,

Li³

2018

PIER M

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Abstract-By analyzing the characteristics of the super low frequency (SLF) electromagnetic wave in through the earth (TTE) communication, an orthogonal array of magnetic antenna is proposed for receiving SLF signal, and a new robust adaptive beamformer is used to process the received signals. The proposed beamformer is a multi-input generalized sidelobe canceller (GSC) with a coefficient constrained adaptive blocking matrix and a filter based on minimum mean-square error (MMSE) criterion. It can reduce the leakage of the desired signal and enhance the capability of interference cancellation. The received signals of the main antennas and the reference antennas of the antenna array are input to the beamformer as desired signal and reference signal, respectively. Both simulated and experimental results show that the proposed beamformer can suppress the single-tone and phase modulation interference, whose frequency is close to the desired signal's frequency. The proposed beamformer has better effect and robustness on interference cancellation than the traditional GSC.

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Interference-plus-Noise Covariance Matrix Reconstruction via Spatial Power Spectrum Sampling for Robust Adaptive Beamforming

Cited by 122 publications

References 17 publications

Effective estimation of the desired-signal subspace and its application to robust adaptive beamforming

Effective estimation of the desired-signal subspace and its application to robust adaptive beamforming

Iterative robust adaptive beamforming

Application of an Improved GSC in Tte Communication With Antenna Array

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