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Robust adaptive beamforming based on jointly estimating covariance matrix and steering vector

Yujie Gu, Amir Leshem
2011 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
First, the theoretical covariance matrix is estimated based on the shrinkage method.  ...  In this paper, a new adaptive beamforming algorithm with joint robustness against covariance matrix uncertainty as well as steering vector mismatch is proposed.  ...  In this paper, we propose a new robust adaptive beamforming algorithm, which is based on estimating the theoretical covariance matrix using a shrinkage method and estimating the mismatch steering vector  ... 
doi:10.1109/icassp.2011.5947027 dblp:conf/icassp/GuL11 fatcat:uy5fwc55hvgbnbpjhlrsjbhb5q


Kai Yang, Zhiqin Zhao, Qing Huo Liu
2013 Electromagnetic Waves  
Moreover, a computationally efficient convex optimization-based algorithm is used to estimate the mismatch of the steering vector associated with the desired signal.  ...  The proposed method is based on the fact that the sample covariance matrix can approximate the interference covariance matrix properly when the desired signal is small, and a reconstructed covariance matrix  ...  ACKNOWLEDGMENT This work was supported in part by the National Natural Science Foundation of China under Grants 61032010, 61231001, and 61171044 and the Fundamental Research Funds for the Central Universities  ... 
doi:10.2528/pier13042203 fatcat:xsafhwaysrfzvoqwaa5plzwnuy


Yu-Jie Gu, Zhi-Guo Shi, Kang Sheng Chen, Yu Li
2008 Electromagnetic Waves  
In this way, the signal steering vector and the diagonal loading sample matrix inversion (DL-SMI) version adaptive beamformer can be obtained.  ...  Based on the observed data, we try to estimate an equivalent directionof-arrival (DOA) for each sensor, in which all factors causing the steering vector uncertainties are ascribed to the DOA uncertainty  ...  ROBUST BEAMFORMER BASED ON EQUIVALENT DOAS METHOD In this section, based on equivalent DOAs method, we develop a new robust adaptive beamforming, which ascribes all the steering vector uncertainties to  ... 
doi:10.2528/pier07102202 fatcat:i2vhe4ir4jhzhkiy4su7n6twue

Principles of minimum variance robust adaptive beamforming design

Sergiy A. Vorobyov
2013 Signal Processing  
In the last decade, several fruitful principles to minimum variance distortionless response (MVDR) robust adaptive beamforming (RAB) design have been developed and successfully applied to solve a number  ...  Robustness is typically understood as an ability of adaptive beamforming algorithm to achieve high performance in the situations with imperfect, incomplete, or erroneous knowledge about the source, propagation  ...  The beamformer weight vector is computed subsequently based on the MVDR expression, using the refined estimate of the desired signal steering vector just as in the RAB based on one-dimensional covariance  ... 
doi:10.1016/j.sigpro.2012.10.021 fatcat:t24hgwfzpbcunonaeinfbgf7yu

Maximally Robust Capon Beamformer

Michael Rubsamen, Marius Pesavento
2013 IEEE Transactions on Signal Processing  
However, estimation errors of the signal steering vector and the array covariance matrix can result in severe performance deteriorations of the SCB, especially if the training data contains the desired  ...  The proposed maximally robust Capon beamformer (MRCB) is at least as robust as the maximum output power Capon beamformer with the same uncertainty set for the signal steering vector.  ...  Beamformer performance versus the presumed upper bound on the norm of the signal steering vector estimation errors (for dB, , and the exact array covariance matrix).  ... 
doi:10.1109/tsp.2013.2242067 fatcat:jyofecnnyrbkpjmk25hbvvsmg4

Adaptive and Robust Beamforming [chapter]

Sergiy A. Vorobyov
2014 Academic Press Library in Signal Processing  
The major differences, however, come from the fact that adaptive filtering is based on temporal processing of a signal, while adaptive beamforming stresses on spatial processing.  ...  Adaptive beamforming is a versatile approach to detect and estimate the signal-of-interest (SOI) at the output of sensor array using data adaptive spatial or spatio-temporal filtering and interference  ...  Gershman has shared with the author some materials on adaptive beamforming including a number of figures used in this chapter.  ... 
doi:10.1016/b978-0-12-411597-2.00012-6 fatcat:esdeztey2rbn7ll7ue66wagcse

Robust adaptive beamforming via estimating steering vector based on semidefinite relaxation

Arash Khabbazibasmenj, Sergiy A. Vorobyov, Aboulnasr Hassanien
2010 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers  
This is to use minimum variance distortionless response principle for beamforming vector computation in tandem with sample covariance matrix estimation and steering vector estimation based on some information  ...  Motivated by such unified framework, we develop a new robust adaptive beamforming method based on finding a more accurate estimate of the actual steering vector than the available prior.  ...  Use minimum variance distortionless response principle for beamforming vector computation in tandem with sample covariance matrix estimation and steering vector estimation based on some prior information  ... 
doi:10.1109/acssc.2010.5757574 fatcat:2hoj4dmb6jfylhwpvtkcntetf4

Adaptive Beamforming for Uniform Linear Arrays With Unknown Mutual Coupling

Bin Liao, Shing-Chow Chan
2012 IEEE Antennas and Wireless Propagation Letters  
By maximizing the output power, the steering vector and hence the robust beamformer can be estimated analytically.  ...  The estimated steering vector is then used to obtain the robust Capon beamformer as (7) B.  ... 
doi:10.1109/lawp.2012.2196017 fatcat:r3vbg5xinjbvjhuajwam43gjqy

Automatic Generalized Loading for Robust Adaptive Beamforming

Jun Yang, Xiaochuan Ma, Chaohuan Hou, Yicong Liu
2009 IEEE Signal Processing Letters  
Numerical examples show that our methods are more robust to errors on array steering vector and sample covariance matrix than other tested parameter-free methods.  ...  In the proposed methods, Hermitian matrices are loaded on sample covariance matrix, and this is different from those methods based on the well-known diagonal loading approach.  ...  Numerical examples in terms of SINR and SOI power estimate show that the proposed methods are robust to errors on array steering vector and sample covariance matrix.  ... 
doi:10.1109/lsp.2008.2010807 fatcat:fuuqbppb2fdpnpb3mg5bquoeya


Rammohan Mallipeddi, Joni Polili Lie, P. N. Suganthan, Sirajudeen Gulam Razul, Chong Meng S. See
2011 Electromagnetic Waves  
Based on the obtained steering vector, estimate for look direction and reconstructed covariance matrix, near optimal output SINR, can be obtained with the increase in the input SNR without observing any  ...  The performance of traditional beamformers tends to degrade due to inaccurate estimation of covariance matrix and imprecise knowledge of array steering vector.  ...  CONCLUSION This paper proposes a DE based adaptive beamforming algorithm addressing the issues such as inaccurate estimation of the covariance matrix and mismatch between the actual and presumed steering  ... 
doi:10.2528/pier11052205 fatcat:2ijjgmhg75bxniyqcvo5ferf7y

Robust Adaptive Beamforming with Null Broadening

2016 Revista Técnica de la Facultad de Ingeniería Universidad del Zulia  
In this paper, a new robust adaptive beamforming algorithm via null broadening is investigated, which is obtained by reconstructing and optimizing the interference-plus-noise covariance matrix, and estimating  ...  the true steering vector to improve the robustness against array vector errors and motional interference.  ...  step3: Use (16) to calculate the weight vector opt w based on the reconstructed interference-plus-noise covariance matrix -1 in  R  and the optimal steering vector a  .  ... 
doi:10.21311/ fatcat:yrcbrcoe7jechbyiul5szdinzi

Robust Null Broadening Beamforming Based on Covariance Matrix Reconstruction via Virtual Interference Sources

Jian Yang, Jian Lu, Xinxin Liu, Guisheng Liao
2020 Sensors  
Based on the reconstructed INC and signal-plus-noise covariance (SNC) matrices, the steering vector of the desired signal can be obtained by solving a new convex optimization problem.  ...  A novel null broadening beamforming method based on reconstruction of the interference-plus-noise covariance (INC) matrix is proposed, in order to broaden the null width and offset the motion of the interfering  ...  In recent years, due to its good robustness against mismatches, a novel robust adaptive beamforming method based on covariance matrix reconstruction and steering vector estimation has attracted much attention  ... 
doi:10.3390/s20071865 pmid:32230886 fatcat:ft6qsebvlnbxfcvxytb7z3emxq

Recursive Steering Vector Estimation and Adaptive Beamforming under Uncertainties

Bin Liao, Shing-Chow Chan, Kai-Man Tsui
2013 IEEE Transactions on Aerospace and Electronic Systems  
In addition, a robust beamformer with a new error bound that uses the proposed steering vector estimate is derived by optimizing the worst case performance of the array after taking the uncertainties of  ...  It employs the subspace principle and estimates the desired steering vector by using a convex optimization approach.  ...  Finally, the proposed robust steering vector estimation and diagonally loaded MVDR beamformer based on worst case performance Step 1) Update the covariance matrix R(t) recursively as R(t) =¯R(t ¡ 1) +  ... 
doi:10.1109/taes.2013.6404116 fatcat:rbwb4xjavbbjvimqje6rdbfa2m

An expected least-squares beamforming approach to signal estimation with steering vector uncertainties

Y.C. Eldar, A. Nehorai, P.S. La Rosa
2006 IEEE Signal Processing Letters  
Index Terms-Array processing, beamforming, least squares (LS), random steering vector, signal estimation.  ...  We treat the problem of beamforming for signal estimation in the presence of steering vector uncertainties, where the goal is to estimate a signal amplitude from a set of array observations.  ...  In particular, we choose and so that our model of the random steering vector is the same in average to the one used by the robust SINR-based method in [5] .  ... 
doi:10.1109/lsp.2006.870356 fatcat:zsbdeaeezffmda3wv4ozrnl7ly

A robust adaptive beamforming method based on the matrix reconstruction against a large DOA mismatch

Julan Xie, Huiyong Li, Zishu He, Chaohai Li
2014 EURASIP Journal on Advances in Signal Processing  
Without estimating the desired signal steering vector, an optimal weight can finally be solved by rotating this orthogonal subspace based on the output power of the desired signal maximization.  ...  In contrast to previous works, this new beamformer employs two reconstructed matrices, the interference-plus-noise covariance matrix and the desired signal-plus-noise covariance matrix, instead of their  ...  In [16] , authors have proposed a robust beamformer based on the interference-plus-noise covariance matrix reconstruction and steering vector estimation.  ... 
doi:10.1186/1687-6180-2014-91 fatcat:a3okxzrf2rchjgkc5axpzj5afy
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