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A Variational Bayesian Approach to Direction Finding of Correlated Targets Using Coprime array

A Variational Bayesian Approach to Direction Finding of Corr...

引用

sensor array and multichannel signal processing workshop

作者： Jie Yang Yixin Yang School of Marine Science and Technology Northwestern Polytechnical University Xi’an Shaanxi China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, we develop a sparsity-aware algorithm for direction-of-arrival (DOA) estimation of correlated targets in the context of coprime array processing. The idea is to iteratively interpolate the observed data to a virtual nonuniform linear array (NLA) in order to raise the degrees of freedom (DOF). We derive the estimation procedures using variational inference for fully Bayesian estimation, where the current parameter estimates are used to interpolate the observed data better and thus increase the likelihood of the next parameter estimates. The novelties of our method lies in its capacity of detecting more correlated sources than the number of physical sensors. Simulated data from coprime arrays are used to illustrate the superior performance of the proposed approach as compared with other state-of-the-art compressed sensing reconstruction algorithms.

关键词： Direction-of-arrival estimation array signal processing Computational modeling Simulation Estimation signal processing algorithms Inference algorithms

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Low-complexity correlated time-averaged variable forgetting factor mechanism for diffusion RLS algorithm in sensor networks

Low-complexity correlated time-averaged variable forgetting ...

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sensor array and multichannel signal processing workshop

作者： Ling Zhang Yunlong Cai Chunguang Li Rodrigo C. de Lamare Minjian Zhao Department of Information Science and Electronic Engineering Zhejiang University Hangzhou China CETUC-PUC-Rio Rio de Janeiro Brazil

ISBN: (纸本)9781509021048

In this work, we present the low-complexity variable forgetting factor (VFF) technique for the diffusion recursive least squares (RLS) algorithm. In particular, we adopt the VFF mechanism that rely on time-averages of the posteriori error signal and incorporate it into the diffusion RLS (DRLS) algorithm to yield the low-complexity correlated time-averaged VFF diffusion RLS (LCTVFF-DRLS) algorithm. We develop detailed analyses in terms of mean and mean square performance for the proposed algorithm, and derive mathematical expressions to compute the mean square deviation (MSD) and the excess mean square error (EMSE). The simulation results show that the proposed LCTVFF-DRLS algorithm outperforms the existing DRLS algorithm with the fixed forgetting factor, and demonstrate a good match between our proposed analytical expressions and simulated results.

关键词： wireless sensor networks computational complexity least squares approximations recursive estimation recursive estimation least squares approximations complexity classes Wireless sensor networks Restless Legs Syndrome Voice Frequency Filter forgetting average time Mathematical Formulas Mean square error diffusion

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A Modified Spatio-Temporal Orthogonal Iteration Method for multichannel Audio signal Representation

A Modified Spatio-Temporal Orthogonal Iteration Method for M...

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ieee workshop on Applications of signal processing to Audio and Acoustics

作者： Scott C. Douglas Malay Gupta Department of Electrical Engineering Southern Methodist University Dallas TX USA

In this paper, we present a novel algorithm for a spatio-temporal extension of the well-known method of orthogonal iterations in linear algebra. This algorithm estimates an n-input, m-output (m ≪ n) paraunitary filter bank from a multichannel data auto-correlation sequence to maximize the total output power of the filter bank when applied to an n-dimensional input signal. We then show how this procedure can be used to generate reduced rank signal representations of recordings of m audio sources in a room as collected by an n-channel microphone array. The importance of the method for determining the number of active sound sources in a room for convolutive blind source separation is also discussed.

关键词： signal representations Microphone arrays Acoustic noise sensor arrays signal processing algorithms Filter bank Autocorrelation Blind source separation array signal processing Acoustic sensors

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A Decentralised Asynchronous Optimisation Algorithm with an Application to Phase Retrieval

A Decentralised Asynchronous Optimisation Algorithm with an ...

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sensor array and multichannel signal processing workshop

作者： Behnam Mafakheri Jonathan H. Manton Iman Shames Electrical and Electronic Engineering University of Melbourne Melbrourne Australia School of Engineering Australian National University Canberra Australia

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

This paper tackles the challenge of decentralised, nonconvex optimisation in situations where agents work asynchronously. Our main contribution is a new algorithm, partially asynchronous ADMM, designed to solve decentralised optimisation problems like phase retrieval. Importantly, it does not require a central coordinator and can work with arbitrary connected network setups. We also prove that our algorithm is equivalent to the randomised block coordinate Douglas-Rachford Splitting method. To illustrate the algorithm's effectiveness, we provide numerical results for the distributed phase retrieval problem, demonstrating its correctness and performance.

关键词： array signal processing Conferences signal processing algorithms Performance analysis Optimization sensor arrays

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Joint Optimization of Reconfigurable Intelligent Surfaces and Dynamic Metasurface Antennas for Massive MIMO Communications

Joint Optimization of Reconfigurable Intelligent Surfaces an...

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sensor array and multichannel signal processing workshop

作者： Xuewen Qian Marco Di Renzo Vincenzo Sciancalepore Xavier Costa-Pé rez Laboratoire des Signaux et Syst&#x00E8 mes Universit&#x00E9 Paris-Saclay CNRS CentraleSup&#x00E9 lec Gif-sur-Yvette France NEC Laboratories Europe GmbH Germany i2cat Research Center Spain

Reconfigurable intelligent surfaces (RISs) are a promising technology for enhancing the communication performance of future wireless systems by controlling the wireless environment. In addition, dynamic metasurface antennas (DMAs) are a promising technology for increasing the number of antenna elements of multiple-input multiple-output (MIMO) systems at a reduced cost and power consumption compared to conventional MIMO arrays. In this paper, we amalgamate these two technologies in order to realize massive MIMO communication networks with superior performance at a reduced complexity. We first introduce the considered RIS-assisted DMA-based MIMO system, and we then formulate an optimization problem to maximize the system rate. The problem is solved by using an alternating optimization algorithm, which iteratively optimizes the RIS elements, as well as the precoding matrices and the DMA elements at the transceivers. Simulation results demonstrate that jointly utilizing RISs for controlling the wireless environment and DMAs at the transceivers results in superior achieavble rates.

关键词： Wireless communication Wireless sensor networks Heuristic algorithms Simulation signal processing algorithms Reconfigurable intelligent surfaces Metasurfaces

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Planar Spherical Diffraction-arrays: Linear Sound Localization Algorithms

Planar Spherical Diffraction-Arrays: Linear Sound Localizati...

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sensor array and multichannel signal processing workshop

作者： A.A. Handzel Watertown MA USA

Sound source localization systems typically measure differences in time-of-arrival between microphones in free field arrays. Using a different concept, we previously designed and built a localization system that mimics nature's solution of harnessing wave diffraction about the head while relying only on two sensors positioned antipodally. Departing from the biological constraint of two sensors, I recently showed that for broadband sources, a high acuity array could be designed with merely three microphones. Yet adding more microphones may further increase acuity and robustness. The localization algorithm we have developed uses pair-wise comparisons between microphones, the number of which increases quadratically with the number of microphones, N. In order to minimize calculations in time sensitive applications, choosing a subset of pairs may be important. I examine this issue here through simulations of a hexagonal array. Thanks to the redundancy of spatial information contained in multiple microphone measurements, algorithms that are linear in N allow high acuity localization of broadband sources

关键词： Acoustic diffraction Microphone arrays sensor arrays Acoustic sensors Frequency Biosensors sensor systems Robustness Ear Information security

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A Note on The Maximum Number of Sources in DOA Estimation by MODE

A Note on The Maximum Number of Sources in DOA Estimation by...

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sensor array and multichannel signal processing workshop

作者： Shohei Hamada Koichi Ichige Department of Electrical and Computer Engineering Yokohama National University Yokohama Japan

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper discusses the maximum number of sources when their direction of arrivals (DOAs) are estimated by the method of direction estimation (MODE), and presents a modified version of MODE that can estimate more number of sources than that by the original MODE. It is well-known that M-element array can basically estimate up to (M – 1) DOAs, however the application of MODE may reduce up to M/2 DOAs because of its computation procedure . We propose a novel DOA estimation method by modifying MODE to employ peak-search of the primary eigenvector beam patterns instead of the null-search in the original MODE. Performance of the proposed method is evaluated through computer simulation.

关键词： Direction-of-arrival estimation array signal processing Conferences Computer simulation Estimation Eigenvalues and eigenfunctions sensor arrays

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Subband STAP processing, the fifth generation

Subband STAP processing, the fifth generation

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sensor array and multichannel signal processing workshop

作者： A.O. Steinhardt N.B. Pulsone DARPA Tactical Technology Office Arlington VA USA MIT Lincoln Laboratories Lexington MA USA

Adaptive array processing has moved through several stages of evolution. First there was spatial only adaptation, using gradient based algorithms. Second was true space-time adaptivity using time-taps on multiple channels. Third came more rapid convergence, using sample matrix inversion strategies. Fourth came dimensionally large system solutions, which focused on the need for reduced DOF such as beamspace, eigenspace, MUSIC, ESPRIT, BASS-ALE, etc. This paper argues that we are on the threshold of the fifth generation of STAP; mainly STAB in the subband domain. Subband STAP, is an elegant and computationally efficient solution to the need for increasing bandwidth in radar and sonar processing as well as mobile communications. We begin by motivating the need for wider bandwidths, from a SAR imaging perspective. Next, we show that the computational burden of wideband STAP is untenable for existing and emerging military requirements. Having motivated a compelling need we then propose subband STAP as a solution, motivated from an active sensor perspective. We describe subband STAP as an extension of the familiar STAP 3D datacube (range, angle, Doppler) to a 40 hypercube (subband range, angle, subband Doppler, subband frequency). Subbanding allows us to overcome challenging wideband effects such as Doppler-frequency coupling, high-resolution range migration, target self-nulling, channel decorrelation, and dispersion. We describe the challenges of subband STAP interference rejection and subband recombination with artifacts.

关键词： Military computing Bandwidth Wideband array signal processing Multiple signal classification Radar imaging Sonar Mobile communication Radar polarimetry Hypercubes

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A Probabilistic Graphical Model for Microphone array Source Separation using Rich Pre-Trained Source Models

A Probabilistic Graphical Model for Microphone Array Source ...

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sensor array and multichannel signal processing workshop

作者： H.T. Attias Golden Metallic Inc. San Francisco CA USA

Voice based computing applications, such as phone communication and speech recognition, use microphone arrays to capture voice from a human speaker. In many environments of interest, however, sounds from other sources interfere with the speaker's voice, posing severe problems for subsequent processing. This paper describes a new framework for treating this problem, and presents and demonstrates a new algorithm for the cancellation of interfering sounds. Our framework combines techniques from statistical machine learning with ideas from speech and audio processing. An important feature involves training rich probabilistic models on data from different types of relevant sound sources. Those source models are then incorporated into a larger probabilistic model of the observed microphone data. Using that model we derive our algorithm, which is of the expectation-maximization type and infers from data the clean sound of separate individual sources. We report very good results on data recorded in different environments

关键词： Microphone arrays Graphical models Source separation Loudspeakers Machine learning algorithms Computer applications Speech recognition Humans Machine learning Speech processing

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Exploiting array Geometry for Reduced-Subspace Channel Estimation in RIS-Aided Communications

Exploiting Array Geometry for Reduced-Subspace Channel Estim...

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sensor array and multichannel signal processing workshop

作者： Ö zlem Tuğ fe Demir Emil Bjö rnson Luca Sanguinetti Department of Computer Science KTH Royal Institute of Technology Kista Sweden Dipartimento di Ingegneria dell&#x0027 Informazione University of Pisa Pisa Italy

A reconfigurable intelligent surface (RIS) can be used to improve the channel gain between a base station (BS) and user equipment (UE), but only if its $N$ reflecting elements are configured properly. This requires accurate estimation of the cascaded channel from the UE to the BS through each RIS element. If the channel structure is not exploited, pilot sequences of length $N$ must be used, which is a major practical challenge since $N$ is typically at the order of hundreds. To address this problem without requiring user-specific channel statistics, we propose a novel estimator, called reduced-subspace least squares (RS-LS) estimator, that only uses knowledge of the array geometry. The RIS phase-shift pattern is optimized to minimize the mean-square error of the channel estimates. The RS- LS estimator largely outperforms the conventional least- squares estimator, and can be utilized with a much shorter pilot length since it exploits the fact that the array geometry confines the possible channel realizations to a reduced-rank subspace.

关键词： Geometry Training Base stations Conferences Channel estimation Estimation Mean square error methods

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