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Robust adaptive beamforming based on jointly estimating covariance matrix and steering vector
2011
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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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
ROBUST ADAPTIVE BEAMFORMING AGAINST ARRAY CALIBRATION ERRORS
2013
Electromagnetic Waves
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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
ROBUST ADAPTIVE BEAMFORMING FOR STEERING VECTOR UNCERTAINTIES BASED ON EQUIVALENT DOAS METHOD
2008
Electromagnetic Waves
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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
2013
Signal Processing
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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
2013
IEEE Transactions on Signal Processing
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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]
2014
Academic Press Library in Signal Processing
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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
2010
2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers
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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
2012
IEEE Antennas and Wireless Propagation Letters
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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
2009
IEEE Signal Processing Letters
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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
A DIFFERENTIAL EVOLUTION APPROACH FOR ROBUST ADAPTIVE BEAMFORMING BASED ON JOINT ESTIMATION OF LOOK DIRECTION AND ARRAY GEOMETRY
2011
Electromagnetic Waves
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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
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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:10.21311/001.39.6.48
fatcat:yrcbrcoe7jechbyiul5szdinzi
Robust Null Broadening Beamforming Based on Covariance Matrix Reconstruction via Virtual Interference Sources
2020
Sensors
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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
2013
IEEE Transactions on Aerospace and Electronic Systems
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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
2006
IEEE Signal Processing Letters
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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
2014
EURASIP Journal on Advances in Signal Processing
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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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