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Resilient Multitask Distributed Adaptation Over Networks With Noisy Exchanges

Resilient Multitask Distributed Adaptation Over Networks Wit...

引用

sensor array and multichannel signal processing workshop

作者： Chengcheng Wang Wee Peng Tay Ye Wei Yuan Wang School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Automation Engineering Northeast Electric Power University China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

We develop a resilient distributed strategy over multitask networks, where individual tasks are linearly related within each neighborhood, and information exchanges between neighboring agents are noisy. In the proposed strategy, each agent follows an adapt-then-project procedure to iteratively update its local estimate. In particular, weighted projection operators are utilized in the projection step in order to attenuate the negative effect of noisy exchanges on the cooperative inference performance. We motivate a strategy for computing the weights in a distributed and adaptive manner. Simulation results demonstrate that the proposed scheme shows good resilience against noise in the information exchange between agents.

关键词： array signal processing Simulation Conferences Noise measurement Task analysis Information exchange Resilience

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Track - Before- Detect Labeled Multi - Bernoulli Filter for Multi- Target Bearing-Only Tracking using an Autonomous Underwater Vehicle

Track - Before- Detect Labeled Multi - Bernoulli Filter for ...

引用

sensor array and multichannel signal processing workshop

作者： Ce Zheng Yankun Chen Qisen Wang Xiang Li Sijian Liu Chao Dong Key Laboratory of Marine Environmental Survey Technology and Application Ministry of Natural Resources of the People's Republic of China Guangzhou China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai China College of Oceanography and Space Informatics China University of Petroleum (East China) Qingdao China

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

This paper considers an autonomous underwater vehicle (AUV) mounted with an array of sensors to detect the presence of multiple targets and estimate their relative locations. We propose a track-before-detect labeled multi-Bernoulli filter, which directly utilizes the signals received from the sensor array as the measurement in the form of a sample-covariance matrix (SCM). Tractable filtering equations are derived by using a change of variable and complex inverse-Wishart approximation. Simulation results demonstrate the improved performance of the proposed filter in challenge scenarios of low signal-to-noise ratio and multiple target crossing.

关键词： Autonomous underwater vehicles Target tracking array signal processing Filtering Simulation Mathematical models sensors

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Target Detection in Clutter Using Receiver with Reduced DOF in Frequency Domain

Target Detection in Clutter Using Receiver with Reduced DOF ...

引用

sensor array and multichannel signal processing workshop

作者： Yang Li Qian He Rick S. Blum Alexander M. Haimovich University of Electronic Science and Technology of China Chengdu China Lehigh University Bethlehem PA USA New Jersey Institute of Technology New Jersey USA

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper addresses the problem of target detection against a background of clutter by using frequency snapshots with reduced degrees of freedom (DOF). We derive the optimal detector under the Neyman-Pearson criterion for general frequency snapshots selection with arbitrary DOF. If the clutter statistics are known/well-estimated, a greedy method for selecting the frequency snapshots is presented. For unknown clutter statistics, we employ a uniform random frequency snapshot selection method and show how the DOF employed affects the detection performance.

关键词： array signal processing Frequency-domain analysis Conferences Object detection Receivers Detectors Clutter

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Distributed Multiarray Noise Reduction With Online Estimation Of Masks And Spatial Filters

Distributed Multiarray Noise Reduction With Online Estimatio...

引用

sensor array and multichannel signal processing workshop

作者： Julitta Bartolewska Konrad Kowalczyk Department of Electronics AGH University of Science and Technology Krakow Poland

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

A rapid increase in popularity of smart devices equipped with acoustic sensors enables the design of speech enhancement methods for distributed setups. In this work, we present a distributed noise reduction scheme in which the time-frequency masks and spatial filters are estimated at the nodes based on the locally available microphone signals and the compressed signals received from other nodes, where each node transmits only a single signal. The proposed block processing facilitates online estimation of masks and distributed spatial filters in an interchanged fashion. The results of performed numerical experiments indicate that the proposed online distributed noise reduction scheme performs similarly to the centralized approach, in which signals of all microphones of the distributed arrays are available for joint processing, and it significantly outperforms the local approach in which only the local microphone signals are available for the estimation of masks and spatial filters.

关键词： Time-frequency analysis Wiener filters array signal processing Estimation Acoustic sensors Speech enhancement Spatial filters

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Hybrid Beamforming Design for Downlink MU-MIMO-OFDM Millimeter-Wave Systems

Hybrid Beamforming Design for Downlink MU-MIMO-OFDM Millimet...

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sensor array and multichannel signal processing workshop

作者： Sepideh Gherekhloo Khaled Ardah Martin Haardt Communications Research Laboratory (CRL) TU Ilmenau Ilmenau Germany

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Hybrid beamforming (HBF) structures have been recently proposed as one of the solutions to reduce cost and energy consumption of fully-digital multi-user MIMO systems in the millimeter-wave range. However, most of the initial references on HBF design assume frequency-flat single-carrier MIMO systems. Their extension to the frequency-selective multi-carrier MIMOOFDM case is, in general, not a straightforward task, especially in partially-connected architectures. In this paper, we propose a new HBF design approach for multi-user massive MIMO-OFDM systems. Simulation results reveal that the proposed solution achieves a comparable performance to the benchmark methods in the fully-connected case, while significantly outperforming them in case of partially-connected architectures.

关键词： Energy consumption array signal processing Simulation Millimeter wave technology Interference Benchmark testing Downlink

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Persymmetric Subspace Rao and Wald Tests for Distributed Target in Partially Homogeneous Environment

Persymmetric Subspace Rao and Wald Tests for Distributed Tar...

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sensor array and multichannel signal processing workshop

作者： Yongchan Gao Linlin Mao Hongbing Ji Liyan Pan Department of Electronic Engineering Xidian University Xi’an China Institute of Acoustics Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

We consider the problem of distributed target detection in partially homogeneous Gaussian clutter with unknown covariance matrix. The target is assumed to lie in a multirank subspace with unknown coordinates. By incorporating the persymmetric structure of the covariance matrix into the detector design, we devise a persymmetric subspace Rao detector (PerRao) and a persymmetric subspace Wald detector (Per-Wald). It is remarkable that the Per-Rao coincide with the Per-Wald in the partially homogeneous environment, and both detectors are shown to ensure constant false alarm rate (CFAR) with respect to the covariance matrix. Numerical examples verify the superiority of the proposed methods in training-restricted situations.

关键词： Training array signal processing Conferences Adaptive arrays Detectors Object detection Covariance matrices

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ADMM-Based Outage Constrained MIMO-ISAC Hybrid Beamforming Design

ADMM-Based Outage Constrained MIMO-ISAC Hybrid Beamforming D...

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sensor array and multichannel signal processing workshop

作者： Hao Liang Bin Liao College of Electronics and Information Engineering Shenzhen University Shenzhen China State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen University Shenzhen China

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

This paper considers the problem of robust hybrid beamforming design for multiple-input multiple-output (MIMO) integrated sensing and communications (ISAC) systems in the presence of channel state information (CSI) error. Specifically, the analog and digital hybrid beamformer at the transmitter is designed with imperfect CSI, through synthesizing a desired transmit power pattern for radar sensing under the outage probability constraints on the signal-to-interference-plus-noise ratio (SINR) of each user. The formulated nonconvex problem is addressed by taking advantage of the Cantelli's Inequality and the Alternating Direction Method of Multipliers (ADMM) frame- work, and deriving the solution of each subproblem involved in the algorithm. Numerical experiments are carried out to show the effectiveness and robustness of the proposed MIMO-ISAC hybrid beamforming design.

关键词： array signal processing Simulation signal processing algorithms Interference Probability Integrated sensing and communication Approximation algorithms

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Distributed UAV Beamforming Using Graph Recurrent Neural Networks

Distributed UAV Beamforming Using Graph Recurrent Neural Net...

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sensor array and multichannel signal processing workshop

作者： Wenqing Zheng Brian M. Sadler Fernando Gama Tianlong Chen Univ. of Texas at Austin Austin TX USA Univ. of Pennsylvania Philadelphia PA USA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

In this paper we develop a novel learning-based approach for mobile distributed beamforming without channel state information. We consider narrowband beamforming between a mobile UAV group and a base station under limited feedback, and propose a graph recurrent neural network (GRNN) approach to leverage local collaboration among the UAVs. The GRNN method is shown to be robust to variations in UAV speeds and group heading, and scales with the UAV group size. We compare to codebook and binary feedback methods and show that better performance is achieved with the proposed GRNN method.

关键词： Training Base stations Tracking loops Recurrent neural networks array signal processing Autonomous aerial vehicles Picture archiving and communication systems

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A Gridless Method for Doa Estimation Under the Coexistence of Mutual Coupling and Unknown Nonuniform Noise

A Gridless Method for Doa Estimation Under the Coexistence o...

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sensor array and multichannel signal processing workshop

作者： Dan Li Yuanyuan Jiang Xiaohuan Wu Wei-Ping Zhu Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper addresses the issue of direction-of-arrival (DOA) estimation under the coexistence of mutual coupling and nonuniform noise. We first construct a selection matrix based on the structural characteristics of the mutual coupling matrix (MCM) to form a new manifold matrix which is not affected by the mutual coupling effect. Then, we employ the covariance fitting criteria to form a semidefinite programming for DOA estimation. Compared to most of existing sparse methods, our method does not require discretization of the angle space, hence is able to achieve super-resolution. Simulations are carried out to verify the effectiveness of the propose method.

关键词： Manifolds Mutual coupling Direction-of-arrival estimation Fitting Superresolution Estimation signal processing algorithms

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A Compressive Sensing Approach for Single-Snapshot Adaptive Beamforming

A Compressive Sensing Approach for Single-Snapshot Adaptive ...

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sensor array and multichannel signal processing workshop

作者： Huiping Huang Abdelhak M. Zoubir Hing Cheung So Technische Universität Darmstadt City University of Hong Kong

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper introduces a compressive sensing approach for single-snapshot adaptive beamforming. The observation data model is considered as source components in additive white noise, and then a compressive sensing formulation is introduced to estimate the parameters of the interference signals. That is, a LASSO regression problem is proposed and solved, yielding the directions as well as the powers of the interference signals. On the other hand, the noise power is estimated by means of averaging the squares of the difference between the observation data and the estimate of the source components. Finally, the interference-plus-noise covariance matrix is reconstructed and used for adaptive beamformer design. Simulation results show better performance of the proposed beamformer than several existing beamformers, in the case of a single snapshot.

关键词： array signal processing Simulation Conferences Interference Additive white noise Data models sensors

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