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Robust adaptive beamforming based on a new steering vector estimation algorithm
Signal Processing, 2013A new approach to the design of robust adaptive beamforming is introduced. In the proposed approach, the mismatch vector of the desired steering vector is estimated by solving a quadratically constrained quadratic programming problem using an interference-plus-noise subspace projection matrix.
Weimin Jia +3 more
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An efficient interference steering matrix estimation scheme for weight vector correction
Digital Signal Processing, 2021Abstract To make the sensor array beamformer insensitive to steering vector error, an efficient interference steering matrix (ISM) estimation scheme for weight vector correction is devised in this paper. The basic idea of this approach is converting the training data into interference-free condition via ISM estimation, thereby correcting the weight ...
Pan Zhang
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Robust Beamforming Based on Steering Vector and Covariance Matrix Estimation
Circuits, Systems, and Signal Processing, 2018In this paper, a novel robust design algorithm based on estimation of signal steering vector and covariance matrix is developed. The theoretical covariance matrix is first estimated via the shrinkage method. Subsequently, the desired signal steering vector is estimated based on maximizing array output power under the correlation coefficient constraint ...
Junhui Qian, Junhui Qian, Nuo Huang
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Robust Adaptive Beamforming Based on Steering Vector Estimation and Covariance Matrix Reconstruction
IEEE Communications Letters, 2015In this letter, a novel robust adaptive beamforming (RAB) technique is proposed. It offers robust performance even with large look direction error in the array steering vector (ASV) and an uncertainty in the covariance matrix. In essence, the proposed ASV estimation technique treats the ASV as a vector lying within the intersection of two subspaces ...
Jinyang Song, Fengfeng Chen
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Smart Innovation, Systems and Technologies, 2019 International audienceAdaptive beamforming methods, when applied to practical problems, are known to suffer severe performance degradation if a mismatch occurs between the presumed and actual steering vectors.
Ghattas Akkad, Ali Mansour
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Steering vector estimation in uncalibrated arrays
IEEE Transactions on Signal Processing, 1995This paper presents an iterative algorithm for estimating the signal steering vectors and associated power levels received by an array of uncalibrated isotropic sensors. The inputs are assumed to consist of narrowband, uncorrelated directional signals in the presence of additive white noise. An iterative algorithm is employed to successively search for
Ching-Yih Tseng +2 more
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A Novel Adaptive Beamforming Method based on Steering Vector and Interference Estimation
2022 International Applied Computational Electromagnetics Society Symposium (ACES-China), 2022Yibin Rui, Renhong Xie, Huiyi Wang
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IEEE Transactions on Signal Processing, 2012 A general notion of robustness for robust adaptive beamforming (RAB) problem and a unied principle for min-imum variance distortionless response (MVDR) RAB techniques design are formulated. This principle is to use standard MVDR beamformer in tandem with
Sergiy Vorobyov +2 more
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Estimation of signal steering vectors in uncalibrated arrays
Proceedings of 27th Asilomar Conference on Signals, Systems and Computers, 2002This paper considers the problem of extracting the signal powers and steering vectors from the signal covariance matrix without the knowledge of array manifold. Under the assumption of narrowband and uncorrelated signals, it is shown that it is necessary and sufficient for the signal powers and steering vectors to satisfy two conditions, termed the ...
null Ching-Yih Tseng +2 more
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A Steering Vector Estimation Algorithm in Uncalibrated Arrays
2008 3rd International Conference on Innovative Computing Information and Control, 2008The projection rotation scaling algorithm has perfect performance for estimating the steering vectors of uncalibrated isotropic sensors. But orders of the estimated steering vectors have randomicity in the algorithm. This paper presents a new steering vector initialization and signal subspace forming method.
Meng-Hong Qu, Ying Wu
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