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Robust focusing for wideband MVDR beamforming

Robust focusing for wideband MVDR beamforming

引用

sensor array and multichannel signal processing workshop

作者： Yaakov Bucris Israel Cohen Miriam A. Doron Department of Electrical Engineering Technion-Israel Institute of Technology Haifa Israel RAFAEL Advanced Defense Systems Limited Haifa Israel

In this paper, we propose and study two robust methods for coherent focused wideband Minimum Variance Distortionless Response (MVDR) beamforming. The focusing procedure introduces a frequency dependent focusing error which causes performance degradation, especially at high signal to Noise Ratio (SNR) values. The proposed robust methods aim at reducing the sensitivity of the coherent MVDR to focusing errors. The first method is based on modifying the beamformer optimization problem and generalizing it to bring into account the focusing transformations and the second is based on modifying the focusing scheme itself. A numerical study demonstrates a significant performance improvement of the proposed robust schemes when applied, using the Wavefield Interpolated Narrowband Generated Subspace (WINGS) focusing transformation.

关键词： Focusing Robustness signal to noise ratio Wideband arrays Sensitivity array signal processing

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Estimating the performance of a superdirective microphone array with a frequency-invariant response

Estimating the performance of a superdirective microphone ar...

引用

sensor array and multichannel signal processing workshop

作者： Federico Traverso Marco Crocco Andrea Trucco Department of Biophysical and Electronic Engineering University of Genova Italy

The knowledge of the impact of sensors tolerances in the beamformer performance is of crucial importance in many design cases, especially when superdirective arrays are employed. The availability of the array characteristics (i.e. perturbations on sensors responses and elements displacement), allows to obtain an expectation of the system capabilities corrupted by realistic imperfections. In this paper we discuss the effectiveness of the expected beam pattern as an a priori criterion for the beamformer performance estimation. In particular, the expected beam power pattern has been compared to the actual one, resulted from an experimental investigation of a superdirective microphone array. The tight adherence between the two beam shapes accounts for the effectiveness of the proposed tool in driving the system design.

关键词： arrays Microphones Acoustic beams Robustness Sensitivity Shape Random variables

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Parametric joint detection-estimation of the number of sources in array processing

Parametric joint detection-estimation of the number of sourc...

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sensor array and multichannel signal processing workshop

作者： Noam Arkind Boaz Nadler Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel

Detection of the number of signals and estimation of their directions of arrival (DOAs) are fundamental problems in array processing. We present three main contributions to these problems, under the conditional model, where signal amplitudes are assumed deterministic unknown. First, we show that there is an explicit relation between model selection and the breakdown phenomena of the Maximum Likelihood estimator (MLE). Second, for the case of a single source, we provide a simple approximate formula for the location of the breakdown of the MLE, using tools from the maxima of stochastic processes. This gives an explicit formula for the source strength required for reliable detection. Third, we apply these results and propose a new joint detection-estimation algorithm with state-of-the-art performance. We demonstrate via simulations the improved detection performance of our algorithm, compared to other popular source enumeration methods.

关键词： arrays Analytical models Maximum likelihood detection Conferences Multiple signal classification Detection algorithms Testing

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Steering vector modeling for polarimetric arrays of arbitrary geometry

Steering vector modeling for polarimetric arrays of arbitrar...

引用

sensor array and multichannel signal processing workshop

作者： Mário Costa Andreas Richter Visa Koivunen Coe Department of Signal Processing and Acoustics SMARAD TKK Finland

In this paper, the algebraic modeling of the steering vector for dual-polarized real-world arrays with unknown configuration is addressed. The formalism provided by the wavefield modeling theory is extended to vector-fields such as completely polarized electromagnetic waves. In particular, compact expressions for decomposing the array steering vector in different orthonormal basis functions are proposed. Such decompositions are shown to be equivalent under mild conditions that typically hold in practice. Recent results on algebraic modeling of sensor arrays are generalized to vector-fields and unified. These results allow for high-resolution direction-of-arrival and polarization estimation when array calibration measurement data is available only. We show that reduced computational complexity may be achieved by making use of the Fast Fourier Transform. Such computational savings may be obtained without compromising the performance of the estimation algorithms and irrespective of the antenna array configuration. The results in this paper contribute to array design as well by providing closed-form expressions for the array steering vector, which are useful in optimizing different array performance criteria. Simulations on direction-of-arrival and polarization estimation using a real-world polarimetric array are carried out, validating our analytical results.

关键词： arrays Harmonic analysis Matrix decomposition Antenna arrays signal processing algorithms

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A computationally efficient blind estimator of polynomial phase signals observed by a sensor array

A computationally efficient blind estimator of polynomial ph...

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sensor array and multichannel signal processing workshop

作者： Alon Amar Amir Leshem Alle-Jan van der Veen EEMSC Faculty Delft University of Technnology Delft Netherlands School of Engineering Bar-llan University Ramat-Gan Israel

Consider estimating the parameters of polynomial phase signals observed by an antenna array given that the array manifold is unknown (e.g., uncalibrated array). To date, only an approximated maximum likelihood estimator (AMLE) was suggested, however, it involves a multidimensional search over the entire coefficient space. Instead, we propose a two-step estimation approach, termed as SEparate-EStimate (SEES): First, the signals are separated with a blind source separation technique by exploiting the constant modulus property; Then, the coefficients of each polynomial are estimated using a least squares method from the unwrapped phase of the estimated signal. This estimator does not involve any search in the coefficient spaces and its computational complexity increases linearly with respect to the polynomial order, whereas that of the AMLE increases exponentially. Simulations show that the proposed estimator achieves the Cramér-Rao lower bound (CRLB) at moderate or high signal to noise ratio (SNR).

关键词： Polynomials arrays signal to noise ratio Direction of arrival estimation Estimation Frequency estimation Frequency modulation

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Blind extraction algorithm with direct desired signal selection

Blind extraction algorithm with direct desired signal select...

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sensor array and multichannel signal processing workshop

作者： B. B. A. J. Bloemendal J. van de Laar P. C. W. Sommen Department of Electrical Engineering Eindhovan University of Technology Eindhoven Netherlands Digital Signal Processing Group Philips Research Laboratories Eindhoven Netherlands

In many practical applications we are interested in the extraction of only one desired signal out of a mixture of signals. A disadvantage of most blind extraction approaches proposed in the literature is that they are inefficient in the sense that they also separate or extract undesired signals. To deal with this inefficiency we exploit an a priori guess of direction of arrival related parameters of the desired signal, which serves as a mold. Based on this mold we create linear combinations of noise-free correlation matrices that are used to construct a single matrix with a specific eigenstructure. The eigenvector that corresponds to the smallest eigenvalue of this matrix is the desired extraction filter. Finally it is shown that this approach paves the way to make the algorithm flexible in the utilization of additional a priori information.

关键词： Eigenvalues and eigenfunctions Correlation Vectors signal processing algorithms Noise Simulation

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Achievable MSE lower bounds in non-Bayesian Biased estimation

Achievable MSE lower bounds in non-Bayesian Biased estimatio...

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sensor array and multichannel signal processing workshop

作者： Koby Todros Joseph Tabrikian Department of Electrical and Computer Engineering Ben-Gurion University of the Negev Beersheba Israel

In this paper, a new structured approach for obtaining uniformly best biased (UBB) estimators, in the mean-square-error (MSE) sense, is established. We show that if a UBB estimator exists, then it is uniquely given by the locally best biased (LBB) estimator. A necessary and sufficient condition for the existence of a UBB estimator is derived, and it is shown that if there exists an optimal bias, such that this condition is satisfied, then it is unique, and the UBB estimator is directly obtained from the LBB estimator. The UBB estimator is derived in a non-linear Gaussian estimation problem. In comparison to the maximum-likelihood estimator, we show that the UBB estimator exhibits superior estimation performance in the MSE sense.

关键词： Maximum likelihood estimation Estimation error Closed-form solution Bayesian methods signal processing Hilbert space

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Two-dimentional direction-of-arrival estimation of coherent signals with L-sharped array

Two-dimentional direction-of-arrival estimation of coherent ...

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sensor array and multichannel signal processing workshop

作者： Guangmin Wang Jingmin Xin Nanning Zheng Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University China

In this paper, a new method is proposed for two-dimensional (2-D) direction-of-arrivals (DOAs) estimation of multiple narrowband coherent signals impinging on an L-shaped sensor arrays structured by two uniform linear arrays (ULAs). The coherency of incident signals is decorrelated through subarray averaging technique, and the null space is obtained through linear operator of the cross-correlation matrix between the received data of two ULAs without eigendecomposition. The elevation angles and the quasi-azimuth angles are firstly decoupled and estimated, and the pair-matching of two groups of angles can be accomplished by using a novel method. Then by investigating the geometrical relationship, the azimuth angles can be obtained. Furthermore the asymptotic mean-square-error (MSE) of the estimated elevation and azimuth angles are derived, and the effectively of the proposed method is verified through numerical examples.

关键词： arrays Estimation Direction of arrival estimation Covariance matrix signal to noise ratio Azimuth Antennas

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Subspace-augmented MUSIC for joint sparse recovery with any rank

Subspace-augmented MUSIC for joint sparse recovery with any ...

引用

sensor array and multichannel signal processing workshop

作者： Kiryung Lee Yoram Bresler Coordinated Science Laboratory and Department of ECE University of Illinois Urbana-Champaign Urbana IL USA

We propose a robust and efficient algorithm for the recovery of the joint support in compressed sensing with multiple measurement vectors (the MMV problem). When the unknown matrix of the jointly sparse signals has full rank, MUSIC is a guaranteed algorithm for this problem, achieving the fundamental algebraic bound on the minimum number of measurements. We focus instead on the unfavorable but practically significant case of rank deficiency or bad conditioning. This situation arises with limited number of measurements, or with highly correlated signal components. In this case MUSIC fails, and in practice none of the existing MMV methods can consistently approach the algebraic bounds. We propose subspace-augmented MUSIC, which overcomes these limitations by combining the advantages of both existing methods and MUSIC. It is a computationally efficient algorithm with a performance guarantee.

关键词： Multiple signal classification Joints signal processing algorithms Matching pursuit algorithms Sparse matrices Compressed sensing Covariance matrix

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Likelihood-Ratio and channel based access for energy-efficient detection in wireless sensornetworks

Likelihood-Ratio and channel based access for energy-efficie...

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sensor array and multichannel signal processing workshop

作者： Kobi Cohen Amir Leshem School of Engineering Bar-llan University Ramat-Gan Israel

We examine transmission scheduling by medium access control (MAC) for energy-efficient detection using Wireless sensor Networks (WSN). We focus on the binary hypothesis testing problem. The decision is made by an access point and based on received data from sensors that transmit through a fading channel. We study the significance of exploiting both Channel-State Information (CSI) and Likelihood-Ratio Information (LRI) to design adequate MAC protocol that minimizes the total transmission energy required for the detection problem. By formulating the problem as a Stochastic Shortest Path (SSP) problem we design the LRI and CSI Based Access (LCBA) protocol. LCBA trades off between LRI and CSI to minimize the total transmission energy. It allows sensors to access the channel according to the optimal policy which solves the formulated SSP problem.

关键词： Wireless sensor networks Fading sensors Indexes Channel estimation Media Access Protocol

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