The Experts below are selected from a list of 12837 Experts worldwide ranked by ideXlab platform
Petre Stoica - One of the best experts on this subject based on the ideXlab platform.
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automatic robust adaptive beamforming via ridge regression
Signal Processing, 2008Co-Authors: Y Selen, Richard Abrahamsson, Petre StoicaAbstract:In this paper we derive a class of new parameter free robust adaptive Beamformers using the generalized sidelobe canceler reparameterization of the unit gain constrained minimum variance problem. In this parameterization the minimum variance Beamformer is obtained as the solution of a linear least squares (LS) problem. In the case of an inaccurate steering vector and/or few data snapshots this marginally overdetermined system gives an ill fit causing signal cancellation in the standard minimum variance (LS) solution. By regularizing the LS problem using ridge regression techniques we get a whole class of robust adaptive Beamformers, none of which requires the choice of a user parameter, as opposed to many existing methods. In this context we also propose a parameter free empirical Bayes-based ridge regression technique which, to the best of our knowledge, is novel. The performance of our approach is illustrated by numerical simulations and compared to other robust adaptive Beamformers.
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automatic robust adaptive beamforming via ridge regression
International Conference on Acoustics Speech and Signal Processing, 2007Co-Authors: Y Selen, Richard Abrahamsson, Petre StoicaAbstract:In this paper we derive a class of new parameter free robust adaptive Beamformers using the generalized sidelobe canceler reparameterization of the Capon Beamformer. In this parameterization the minimum variance Beamformer is obtained as the solution of a linear least squares problem. In the case of an inaccurate steering vector and/or few data snapshots this marginally overdetermined system gives an ill fit causing signal cancellation in the standard minimum variance solution. By regularizing the problem using ridge regression techniques we get a whole class of robust adaptive Beamformers, none of which requires the choice of a user parameter. We also propose a novel empirical Bayes-based ridge regression technique. The performance is compared to other robust adaptive Beamformers.
Rajeev Nongpiur - One of the best experts on this subject based on the ideXlab platform.
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1L-infinity Norm Design of Linear-phase Robust Broadband Beamformers using Constrained Optimization
2016Co-Authors: Rajeev Nongpiur, D J Shpak, Senior MemberAbstract:Abstract—A new method for the design of linear-phase robust far-field broadband Beamformers using constrained optimization is proposed. In the method, the maximum passband1 ripple and minimum stopband attenuation are ensured to be within pre-scribed levels, while at the same time maintaining a good linear-phase characteristic at a prescribed group delay in the passband. Since the Beamformer is intended primarily for small-sized mi-crophone arrays where the microphone spacing is small relative to the wavelength at low frequencies, the Beamformer can become highly sensitive to spatial white noise and array imperfections if a direct minimization of the error is performed. Therefore, to limit the sensitivity of the Beamformer the optimization is carried out by constraining a sensitivity parameter, namely, the white noise gain (WNG) to be above prescribed levels across the frequency band. Two novel design variants have been developed. The first variant is formulated as a convex optimization problem where the maximum error in the passband is minimized, while the second variant is formulated as an iterative optimization problem and has the advantage of significantly improving the linear-phase characteristics of the Beamformer under any prescribed group delay or linear-array configuration. In the second variant, the passband group-delay deviation is minimized while ensuring that the maximum passband ripple and stopband attenuation are within prescribed levels. To reduce the computational effort in carrying out the optimization, a nonuniform variable sampling approach over the frequency and angular dimensions is used to compute the required parameters. Experiment results show that Beamformers designed using the proposed methods have much smaller passband group-delay deviation for similar passband ripple and stopband attenuation than a modified version of an existing method. Index Terms—acoustic beamforming, broadband Beamformer, constrained optimization, speech enhancement I
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design of minimax broadband Beamformers that are robust to microphone gain phase and position errors
IEEE Transactions on Audio Speech and Language Processing, 2014Co-Authors: Rajeev NongpiurAbstract:Broadband Beamformers with small-size microphone arrays are known to be highly sensitive to microphone imperfections. A new method for the design of minimax broadband Beamformers that are robust to microphone gain, phase, and position errors is proposed. In the method, the maximum variations in the microphone errors are used in formulating a convex optimization problem where the worst-case passband error is minimized under the constraint that the worst-case stopband error is below a prescribed level. To include the microphone imperfections in the optimization problem, we developed a suitable model that incorporates the variations due to the microphone errors and at the same time is efficient to compute. An important advantage of the proposed method is the availability of corresponding worst-case passband - and stopband-error bounds for the Beamformer that has been designed; a second advantage is that it does not require the probability distributions of microphone errors. We then describe a two-phase method where the proposed method is used in the first phase to derive the passband and stopband error constraints for solving an optimization problem in the second phase where the white noise gain (WNG) of the Beamformer is maximized. In our experiments, we compare Beamformers designed using the proposed method, the two-phase method and a modified version of a competing method. Experimental results show that Beamformers designed using the proposed method have much better performance than those of the modified competing method and comparable performance with those of the two-phase method; however, unlike the two-phase method, the proposed method provides the additional guarantee that the errors will always lie within the worst-case error bounds.
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l infinity norm design of linear phase robust broadband Beamformers using constrained optimization
IEEE Transactions on Signal Processing, 2013Co-Authors: Rajeev Nongpiur, D J ShpakAbstract:A new method for the design of linear-phase robust far-field broadband Beamformers using constrained optimization is proposed. In the method, the maximum passband ripple and minimum stopband attenuation are ensured to be within prescribed levels, while at the same time maintaining a good linear-phase characteristic at a prescribed group delay in the passband. Since the Beamformer is intended primarily for small-sized microphone arrays where the microphone spacing is small relative to the wavelength at low frequencies, the Beamformer can become highly sensitive to spatial white noise and array imperfections if a direct minimization of the error is performed. Therefore, to limit the sensitivity of the Beamformer the optimization is carried out by constraining a sensitivity parameter, namely, the white noise gain (WNG) to be above prescribed levels across the frequency band. Two novel design variants have been developed. The first variant is formulated as a convex optimization problem where the maximum error in the passband is minimized, while the second variant is formulated as an iterative optimization problem and has the advantage of significantly improving the linear-phase characteristics of the Beamformer under any prescribed group delay or linear-array configuration. In the second variant, the passband group-delay deviation is minimized while ensuring that the maximum passband ripple and stopband attenuation are within prescribed levels. To reduce the computational effort in carrying out the optimization, a nonuniform variable sampling approach over the frequency and angular dimensions is used to compute the required parameters. Experiment results show that Beamformers designed using the proposed methods have much smaller passband group-delay deviation for similar passband ripple and stopband attenuation than a modified version of an existing method.
Xianghua Wang - One of the best experts on this subject based on the ideXlab platform.
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robust sparse array design for adaptive beamforming against doa mismatch
Signal Processing, 2018Co-Authors: Xiangrong Wang, Xianghua WangAbstract:Abstract The performance of an adaptive Beamformer is significantly influenced by its array configuration. The problem of optimum array configuration for minimum variance distortionless response (MVDR) Beamformers has been recently investigated under the assumption of accurate estimate or prior exact knowledge of the source direction of arrival (DOA). Inaccuracies in DOA can lead to significant performance degradation. Improving the robustness of MVDR Beamformers has commonly been achieved by adding appropriate constraints in the determination of beamforming weights, such as the linearly constrained minimum variance (LCMV) Beamformer. This work examines the sensitivity of different sparse array configurations towards uncertainty in the source DOA. It proposes enhancing system robustness through optimizing array configurations. The sparse array design problem is formulated in terms of maximizing the output signal-to-interference-plus-noise ratio (SINR) of the MVDR and LCMV Beamformers. The constrained maximization problem is expressed as the fraction of matrix determinants, and a sequential convex programming algorithm is adopted for the solution of the corresponding non-convex problem. Numerical examples are presented to validate the robustness of configured sparse array MVDR and LCMV Beamformers for small errors in source directional angles.
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optimum sparse array design for multiple Beamformers with common receiver
International Conference on Acoustics Speech and Signal Processing, 2018Co-Authors: Xiangrong Wang, Xianghua WangAbstract:The problem of optimum sparse array Beamformer design to maximize output signal-to-interference-plus-noise ratio (SINR) in the case of multiple narrowband sources was recently investigated. This was based on seeking both optimum sensor placement as well as optimum a single Beamformer for all sources in the array field of view. In this paper, we consider multiple Beamformers with a common sparse array. That is, we deal with a more prevalent case in radar and communications where each source is assigned its own beam. This could be the case for both switched and simultaneous or staring beams. The paper considers optimum sparse array design for both narrowband and wideband sources. Analysis and simulation examples demonstrate that the optimum sparse array configuration depends on both the arrival angle and the frequency of the incoming signal and it plays a vital role in determining the performance of multiple Beamformer receivers.
Georgios B. Giannakis - One of the best experts on this subject based on the ideXlab platform.
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design and analysis of transmit beamforming based on limited rate feedback
IEEE Transactions on Signal Processing, 2006Co-Authors: Pengfei Xia, Georgios B. GiannakisAbstract:This paper deals with design and performance analysis of transmit Beamformers for multiple-input multiple-output (MIMO) systems based on bandwidth-limited information that is fed back from the receiver to the transmitter. By casting the design of transmit beamforming based on limited-rate feedback as an equivalent sphere vector quantization (SVQ) problem, multiantenna beamformed transmissions through independent and identically distributed (i.i.d.) Rayleigh fading channels are first considered. The rate-distortion function of the vector source is upper-bounded, and the operational rate-distortion performance achieved by the generalized Lloyd's algorithm is lower-bounded. Although different in nature, the two bounds yield asymptotically equivalent performance analysis results. The average signal-to-noise ratio (SNR) performance is also quantified. Finally, Beamformer codebook designs are studied for correlated Rayleigh fading channels, and a low-complexity codebook design that achieves near-optimal performance is derived.
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design and analysis of transmit beamforming based on limited rate feedback
Vehicular Technology Conference, 2004Co-Authors: Georgios B. GiannakisAbstract:We deal with the design and performance analysis of transmit-Beamformers for multi-input multi-output (MIMO) systems, based on bandwidth-limited information that is fed back from the receiver to the transmitter. By casting the design of transmit-beamforming based on limited-rate feedback as an equivalent sphere vector quantization (SVQ) problem, we first consider multi-antenna beamformed transmissions through independent and identically distributed (i.i.d.) Rayleigh fading channels. We upper-bound the rate distortion function of the vector source, and also lower-bound the operational rate distortion performance achieved by the generalized Lloyd's algorithm. A simple and valuable relationship emerges between the theoretical distortion limit and the achievable performance, and the average signal to noise ratio (SNR) performance is accurately quantified. Finally, we study Beamformer codebook designs for correlated Rayleigh fading channels. and derive a low-complexity codebook design that achieves near optimal performance.
Y Selen - One of the best experts on this subject based on the ideXlab platform.
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automatic robust adaptive beamforming via ridge regression
Signal Processing, 2008Co-Authors: Y Selen, Richard Abrahamsson, Petre StoicaAbstract:In this paper we derive a class of new parameter free robust adaptive Beamformers using the generalized sidelobe canceler reparameterization of the unit gain constrained minimum variance problem. In this parameterization the minimum variance Beamformer is obtained as the solution of a linear least squares (LS) problem. In the case of an inaccurate steering vector and/or few data snapshots this marginally overdetermined system gives an ill fit causing signal cancellation in the standard minimum variance (LS) solution. By regularizing the LS problem using ridge regression techniques we get a whole class of robust adaptive Beamformers, none of which requires the choice of a user parameter, as opposed to many existing methods. In this context we also propose a parameter free empirical Bayes-based ridge regression technique which, to the best of our knowledge, is novel. The performance of our approach is illustrated by numerical simulations and compared to other robust adaptive Beamformers.
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automatic robust adaptive beamforming via ridge regression
International Conference on Acoustics Speech and Signal Processing, 2007Co-Authors: Y Selen, Richard Abrahamsson, Petre StoicaAbstract:In this paper we derive a class of new parameter free robust adaptive Beamformers using the generalized sidelobe canceler reparameterization of the Capon Beamformer. In this parameterization the minimum variance Beamformer is obtained as the solution of a linear least squares problem. In the case of an inaccurate steering vector and/or few data snapshots this marginally overdetermined system gives an ill fit causing signal cancellation in the standard minimum variance solution. By regularizing the problem using ridge regression techniques we get a whole class of robust adaptive Beamformers, none of which requires the choice of a user parameter. We also propose a novel empirical Bayes-based ridge regression technique. The performance is compared to other robust adaptive Beamformers.