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检索条件"任意字段=4th IEEE Sensor Array and Multichannel Signal Processing Workshop"

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A new beamformer based on phase dispersion to improve 2D sparse array response

A new beamformer based on phase dispersion to improve 2D spa...

引用

sensor array and multichannel signal processing workshop

作者： Oscar Martinez-Graullera David Romero-Laorden Alberto Ibañez Luis G. Ullate CAEND (UPM-CSIC) Madrid Spain

this work studies a new beamformer for non-periodic sparse bidimensional ultrasonic array transducer. It is based on a weighting factor based on signals phase dispersion to enhance the image points where the phase coherence between the received signals is high. A method to measure the phase dispersion based on Fourier analysis and its integration in the beamformer are presented. Its performance is evaluated using a non-periodic 2D sparse array based on Fermat spiral with 96 elements and a diameter of 60λ. Compared with conventional Delay-And-Sum beamformer the proposed solution reduces the aperture lateral resolution and improves its dynamic range, achieving up to 50dB of contrast in the image and less 1° in lateral resolution.

关键词： arrays Dispersion Apertures Coherence Dynamic range Spirals Image resolution

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Dynamic Transmit Power Allocation for Distributed Mimo Radar Target Detection

Dynamic Transmit Power Allocation for Distributed Mimo Radar...

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sensor array and multichannel signal processing workshop

作者： Tuomas Aittomäki Sundeep Prabhakar Chepuri Visa Koivunen Department of Microelectronics TU Delft The Netherlands Department of Signal Processing and Acoustics Aalto University Finland

Distributed multiple-input multiple-output (MIMO) radars can use multiple transmitters and receivers simultaneously to detect targets. In order to maximize the probability of target detection, it is necessary to allocate the available transmit power resources suitably. the optimal allocation requires calculating the probability of detection, which is a computationally complex task, so using the exact distribution is very difficult in a dynamic scenario. In order to alleviate this problem, we propose an approximate distribution that is computationally simpler. this approximation is compared with the exact distribution as well as other cost functions that depend on the distribution of the test statistic, including the Kullback-Leibler divergence. It is demonstrated that the approximate distribution works well in the power allocation problem for MIMO radar target detection.

关键词： signal to noise ratio Covariance matrices Resource management Optimization Object detection Transmitters Receivers

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Sound Source Localization for Hearing Aid Applications Using Wireless Microphones

Sound Source Localization for Hearing Aid Applications Using...

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sensor array and multichannel signal processing workshop

作者： Mojtaba Farmani Michael Syskind Pedersen Jesper Jensen Oticon A/S SmØrum Denmark

State-of-the-art hearing aids (HAs) can connect to a wireless microphone worn by a talker of interest. this ability allows HAs to have access to almost noise-free sound signals of the target talker. In this paper, we aim to estimate the direction of arrival (DoA) of the target signal, given access to the noise-free target signal. Knowing the DoA of the target signal enables HAs to spatialize the wirelessly received target signals. the proposed estimator is based on a maximum likelihood (ML) approach and a database of DoA-dependent relative transfer functions (RTFs), and it supports both monaural and binaural microphone array configurations. For binaural configurations, we propose an information fusion strategy, which decreases the number of parameters required to be wirelessly transferred between the HAs. Further, we show that the proposed method not only has lower computational complexity, but also performs better than recent DoA estimators, which have access to the noise-free target signal.

关键词： Microphones Direction-of-arrival estimation Wireless communication Maximum likelihood estimation Databases Wireless sensor networks

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New insights into second and fourth-order direction finding for NonCircular sources

New insights into second and fourth-order direction finding ...

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sensor array and multichannel signal processing workshop

作者： Anne Ferréol Pascal Chevalier THALES Communications et security France

these last three decades, many second order (SO) and higher order (HO) high resolution (HR) direction finding (DF) methods, such as 2q-MUSIC (q ≥ 1), exploiting the information contained in the SO or HO circular (C) cumulants of the data, have been developed. However, for 2qth-order non-circular (NC) sources such as M-PSK sources with M ≤ 2q, strong gains in performance may be obtained by taking into account the information contained in both 2qth-order C and NC cumulants of the data, giving rise to NC 2qth-order DF methods. Numerous NC DF methods have been developed these last fifteen years but mainly at the SO and under restrictive assumptions on the sources. the purpose of this paper is to give new insights into NC 2q-MUSIC methods for 1 ≤ q ≤ 2 and for arbitrary NC sources.

关键词： Vectors Multiple signal classification signal processing algorithms arrays Noise Eigenvalues and eigenfunctions

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Dictionary based reconstruction and classification of randomly sampled sensor network data

Dictionary based reconstruction and classification of random...

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sensor array and multichannel signal processing workshop

作者： Grigorios Tsagkatakis Panagiotis Tsakalides Institute of Computer Science (ICS) Foundation for Research and Technology Hellas Crete Greece Department of Computer Science University of Crete Heraklion Crete Greece

In this paper, we propose a method for recovering and classifying WSN data while minimizing the number of samples that need to be acquired, processed, and transmitted. the problem is formulated according to the recently proposed framework of Matrix Completion (MC), which asserts that a low rank matrix can be recovered from a small number of randomly sampled entries. the application of MC in WSN data is motivated by the assumption that sensory data exhibit intra-sensor correlations and that these data can be represented using known examples. We formulate the problem as that of recovering the low rank measurement matrix by encoding the contributions of known examples, the dictionary elements, for reconstructing and classifying the data. Experimental results using artificial data suggest that the proposed scheme is able to accurately reconstruct and classify the sensory data from a small number of measurements.

关键词： Wireless sensor networks Dictionaries Correlation Noise Accuracy Minimization Noise measurement

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Successive Convex Approximation Algorithms for Sparse signal Estimation with Nonconvex Regularizations

Successive Convex Approximation Algorithms for Sparse Signal...

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sensor array and multichannel signal processing workshop

作者： Yang Yang Marius Pesavento Syrneon Chatzinotas Bjōrn Ottersten University of Luxembourg Luxembourg Technische Universitāt Darmstadt Darmstadt Germany

In this paper, we propose a successive convex approximation framework for sparse optimization where the nondifferentiable regularization in the objective function is nonconvex and it can be written as the difference of two convex functions. the proposed framework is based on a nontrivial combination of the majorization-minimization method and successive convex approximation for nonconvex optimization where the regularization function is convex. the proposed framework is flexible and it leads to algorithms that exploit the problem structure and have a low complexity. We demonstrate these advantages by an example application where the nonconvex regularization is the capped l1 -norm function. Customizing the proposed framework, we obtain a best-response type algorithm for which all elements of the unknown parameter are updated in parallel according to closed-form expressions. Finally, the proposed algorithms are numerically tested.

关键词： Approximation algorithms signal processing algorithms Complexity theory Search problems Upper bound Convergence Optimization

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A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar

A Multi-Channel Partial-Update Algorithm for Sea Clutter Sup...

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sensor array and multichannel signal processing workshop

作者： Yahui Ma Shengheng Liu Jun Lu School of Information and Electronics Beijing Institute of Technology Beijing China China Academy of Electronics and Information Technology Beijing China

Sea clutters with Doppler-varying spectrum exert a notable negative impact on the detection performance, especially with low-velocity targets, when a passive bistatic radar is employed to detect sea-surface targets. One feasible solution is to modulate the reference signal onto the Doppler dimension and, as such, a filter with a wide notch and sharp edges can be obtained to suppress the residual clutters. However, to achieve this goal, a considerably high computational complexity is demanded in the existing two-dimensional (2D) adaptive filters. In this context, a novel 2D partial-update normalized least mean square algorithm is proposed to reduce the computational load, as well as to yield a superior clutter suppression performance. the effectiveness of the proposed approach is verified by real-data experiments.

关键词： Clutter signal processing algorithms Doppler effect Computational complexity Receiving antennas Bistatic radar Surveillance

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Multi-Efficiency Based Resource Allocation for Cognitive Radio Networks with Deep Learning

Multi-Efficiency Based Resource Allocation for Cognitive Rad...

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sensor array and multichannel signal processing workshop

作者： Miao Liu Tiecheng Song Lei Zhang Hikmet Sari Guan Gui National Mobile Communications Research Laboratory Southeast University Nanjing China School of Electrical and Information engineering Jiangsu University of Technology Changzhou China College of Telecommunication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

In this paper, a multi-efficiency based scheme is considered, for not only the energy efficiency (EE) and spectrum efficiency (SE) of the primary users (PUs) and the secondary users (SUs), but also the computing efficiency (CE) of the deep learning based RA algorithm in the cognitive radio networks (CRN). Considering the OFDMA based resource allocation (RA) problem for the underlaying SUs, a weighted sum of the secondary interference power is introduced as the objective to minimize. To solve the problem, a deep learning based reweighted message-passing algorithm (ReMPA) is proposed. Compared to the previous scheme and the traditional scheme, the simulation results show that the proposed scheme has effective improvement on both the SE and EE for PUs and SUs.

关键词： array signal processing sensor arrays Conferences Communications technology Resource management Machine learning

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the LOCATA Challenge Data Corpus for Acoustic Source Localization and Tracking

The LOCATA Challenge Data Corpus for Acoustic Source Localiz...

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sensor array and multichannel signal processing workshop

作者： Heinrich W. Löllmann Christine Evers Alexander Schmidt Heinrich Mellmann Hendrik Barfuss Patrick A. Naylor Walter Kellermann Friedrich-Alexander University Erlangen-Nürnberg Imperial College London Humboldt-Universität zu Berlin

Algorithms for acoustic source localization and tracking are essential for a wide range of applications such as personal assistants, smart homes, tele-conferencing systems, hearing aids, or autonomous systems. Numerous algorithms have been proposed for this purpose which, however, are not evaluated and compared against each other by using a common database so far. the ieee-AASP Challenge on sound source localization and tracking (LOCATA) provides a novel, comprehensive data corpus for the objective benchmarking of state-of-the-art algorithms on sound source localization and tracking. the data corpus comprises six tasks ranging from the localization of a single static sound source with a static microphone array to the tracking of multiple moving speakers with a moving microphone array. It contains real-world multichannel audio recordings, obtained by hearing aids, microphones integrated in a robot head, a planar and a spherical microphone array in an enclosed acoustic environment, as well as positional information about the involved arrays and sound sources represented by moving human talkers or static loudspeakers.

关键词： arrays Microphone arrays Task analysis array signal processing Acoustics Databases

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MIMO Radar and Communications Spectrum Sharing: A Multiple-Access Perspective

MIMO Radar and Communications Spectrum Sharing: A Multiple-A...

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sensor array and multichannel signal processing workshop

作者： Yu Rong Alex R. Chiriyath Daniel W. Bliss Bliss Laboratory of Information Signals and Systems Arizona State University Tempe AZ

In this paper, we investigate the joint multiple-input multiple-output (MIMO) radar and communications system convergence problem and develop a joint radar-communications performance bound using the concept of estimation rate for radar system and data information rate for communications system. At the radar receiver, we propose a Successive Interference Cancellation (SIC) strategy to estimate radar parameters and decode communications signal simultaneously. While, at the MIMO communications transmitter, we propose a spectrum sharing scheme and show that the optimal communications performance can be achieved through a spectral and spatial waterfilling algorithm. In the end, we show that the Multiple-Access (MAC) performance bound outperforms the result from the spectrally isolated MIMO radar-communications system.

关键词： Radar Silicon carbide Estimation MIMO communication Radar signal processing

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