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检索条件"任意字段=2008 IEEE Sensor Array and Multichannel Signal Processing Workshop"

共 1267 条记录，以下是61-70 订阅

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Direct Position Determination of Locally Scattered Sources Using Generalized array Manifold Model

Direct Position Determination of Locally Scattered Sources U...

引用

sensor array and multichannel signal processing workshop

作者： Devan Palur Palanivelu Marc Oispuu Wolfgang Koch Thomas Dallmann Fraunhofer Institute for Communication Information Processing and Ergonomics FKIE Wachtberg Germany Radio Technologies for Automated and Connected Vehicles Research Group Technische Univcrsität Ilmenau Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Source localization from raw array data by repa-rameterizing the array steering vector by the source position is a fundamental principle of direct position determination (DPD). In this paper, we propose a DPD method to estimate the position of locally scattered sources using an unsynchronized array sensor network. Here, we use the well-known generalized array manifold (GAM) model which approximates the steering vector using its first-order gradient in order to characterize the local scattering effect. The proposed method is compared with the conventional two-stage bearings-only localization (BOL) approach. Simulation results reveal that the proposed DPD position estimates asymptotically attain the derived Cramér-Rae Bound (CRB) for high SNR values and an improved localization accuracy is achieved by exploiting the local scattering parameters in the localization.

关键词： Location awareness Manifolds Accuracy Systematics array signal processing Scattering Vectors

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Frequency-Switching Sparse arrays

Frequency-Switching Sparse Arrays

引用

sensor array and multichannel signal processing workshop

作者： Yimin D. Zhang Md. Waqeeb T. S. Chowdhury Department of Electrical and Computer Engineering Temple University Philadelphia PA USA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

In this paper, we propose high-resolution target direction-of-arrival (DOA) estimation using frequency-switching sparse arrays which implement multi-frequency sparse arrays in a low-complexity manner. Unlike multi-frequency sparse arrays which require processing of wideband signals comprising multiple frequency components, the proposed frequency-switching sparse arrays only need to process a single-frequency component at any time instant, thereby eliminating such hurdles and significantly reducing the system complexity. A frequency-switching sparse array achieves the same number of degrees-of-freedom as a multi-frequency counterpart with comparable DOA estimation performance. Numerical results on the DOA estimation performance and Cramer- Rao bounds are provided to illustrate the effectiveness of the proposed frequency-switching sparse arrays.

关键词： Time-frequency analysis Direction-of-arrival estimation array signal processing Estimation Receivers Frequency estimation Frequency diversity

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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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A Graph Autoencoder Approach to Crowdsourcing

A Graph Autoencoder Approach to Crowdsourcing

引用

sensor array and multichannel signal processing workshop

作者： Panagiotis A. Traganitis Charilaos I. Kanatsoulis Dept. of Electrical and Computer Engineering Michigan State University East Lansing MI USA Dept. of Computer Science Stanford University Palo Alto CA USA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Crowdsourcing deals with combining and aggregating labels from crowds of annotators of unknown reliability. While most works on label aggregation operate under the assumption of independent and identically distributed data, the present work introduces an algorithm that operates under known data dependencies or correlations. To exploit these dependencies, a novel graph autoencoder-based algorithm is developed that fuses annotator labels for crowdsourced classification tasks. Numerical tests on real data showcase the potential of the proposed approach.

关键词： Crowdsourcing Correlation Fuses Conferences signal processing algorithms Distributed databases Classification algorithms

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Revisiting semi-supervised training objectives for differentiable particle filters

Revisiting semi-supervised training objectives for different...

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sensor array and multichannel signal processing workshop

作者： Jiaxi Li John-Joseph Brady Xiongjie Chen Yunpeng Li Computer Science Research Centre University of Surrey Guildford United Kingdom

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Differentiable particle filters combine the flexibility of neural networks with the probabilistic nature of sequential Monte Carlo methods. However, traditional approaches rely on the availability of labelled data, i.e., the ground truth latent state information, which is often difficult to obtain in real-world applications. This paper compares the effectiveness of two semi-supervised training objectives for differentiable particle filters. We present results in two simulated environments where labelled data are scarce.

关键词： Training Monte Carlo methods Conferences Neural networks signal processing algorithms Performance gain Probabilistic logic

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Sparse array and Precoding Design for Integrated Sensing and Communication Systems

Sparse Array and Precoding Design for Integrated Sensing and...

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sensor array and multichannel signal processing workshop

作者： R.S. Prasobh Sankar Sundeep Prabhakar Chepuri Indian Institute of Science Bengaluru Karnataka India

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

In this paper, we perform joint antenna selection and transmit pre-coder design for integrated sensing and communication (ISAC) systems to meet signal-to-interference-plus-noise-ratio (SINR) requirements at the users while being capable of identifying, i.e., estimating the direction of arrivals (DoAs), of certain number of sources. We first present a sufficient condition to ensure certain identifiability. Next, through a series of relaxations, we obtain a convex approximation to the combinatorial antenna selection and precoding problem, which we solve using off-the-shelf solvers. The proposed method offers comparable performance to ISAC systems with optimal antenna selection obtained through exhaustive search while significantly out-performing ISAC systems with arbitrarily selected active antennas.

关键词： Sufficient conditions Direction-of-arrival estimation array signal processing Transmitting antennas Interference Integrated sensing and communication Radar antennas

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An Efficient Optimization Framework for Learning General Signed Graphs From Smooth signals

An Efficient Optimization Framework for Learning General Sig...

引用

sensor array and multichannel signal processing workshop

作者： Shi-Yuk Fong Anthony Man-Cho So Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong SAR China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong SAR China

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Graph learning has been widely used in many fields to study the relationships between different entities in a dataset. We present an optimization framework based on the proximal alternating direction method of multipliers (pADMM) for learning general signed graphs from smooth signals. We show that our proposed pADMM enjoys global convergence and a local linear convergence rate. Then, we demonstrate the effectiveness of the proposed framework through numerical experiments on signed graphs. Our proposed framework provides a promising approach for learning general signed graphs from smooth signals and can be a valuable tool for data analysis and decision-making in various fields.

关键词： Data analysis array signal processing Conferences Decision making Optimization Convergence sensor arrays

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Blind Phase-Offset Estimation in Sparse Partly Calibrated arrays

Blind Phase-Offset Estimation in Sparse Partly Calibrated Ar...

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sensor array and multichannel signal processing workshop

作者： Tianyi Liu Marius Pesavento Communication Systems Group Technische Universitat Darmstadt Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Spatial frequency estimation from a superposition of impinging waveforms in the presence of noise is important in many applications. While subspace-based methods offer high-resolution parameter estimation at a low computational cost, they heavily rely on precise array calibration with a synchronized clock, posing challenges for large distributed antenna arrays. In this study, we focus on direction-of-arrival (DoA) estimation within sparse partly calibrated rectangular arrays. These arrays consist of multiple perfectly calibrated sub arrays with unknown phase-offsets among them. We present a gridless sparse formulation for DoA estimation leveraging the multiple shift-invariance properties in the partly calibrated array. Additionally, an efficient blind calibration technique is proposed based on semidefinite relaxation to estimate the intersubarray phase-offsets accurately.

关键词： Phased arrays Direction-of-arrival estimation array signal processing Conferences Noise Estimation Frequency estimation

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Linear Convergence of Iteratively Reweighted Least Squares for Nuclear Norm Minimization

Linear Convergence of Iteratively Reweighted Least Squares f...

引用

sensor array and multichannel signal processing workshop

作者： Christian Kümmerle Dominik Stöger Department of Computer Science University of North Carolina at Charlotte Charlotte NC USA Department of Mathematics KU Eichstätt-Ingolstadt Ingolstadt Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Low-rank matrix recovery problems are ubiquitous in many areas of science and engineering. One approach to solve these problems is Nuclear Norm Minimization, which is itself computationally challenging to solve. Iteratively Reweighted Least Squares (IRLS) uses a sequence of suitable (re-)weighted least squares problems to minimize the nuclear norm. However, while global convergence guarantees have been established for IRLS in this context, no convergence rates have been known so far. In this paper, we show that an IRLS variant named MatrixIRLS converges to the ground truth solution with a linear rate. Numerical simulations corroborate our theoretical findings.

关键词： array signal processing Conferences Minimization Numerical simulation Convergence sensor arrays

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Overdemodulation-Aided One-Bit DoA Estimation

Overdemodulation-Aided One-Bit DoA Estimation

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sensor array and multichannel signal processing workshop

作者： Saeid Sedighi Bhavani Shankar Mysore R Björn Ottersten Valeo Schalter und Sensoren GmbH Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Sensing and communication systems commonly employ quadrature demodulation for signal down-conversion to baseband, using two orthogonal sinusoidal signals–an approach well-suited for systems equipped with high-resolution Analog-to-Digital Converters (ADCs). However, the performance of this approach is compromised when constrained to one-bit resolution ADCs. Motivated by this fact, in this paper, we explore the problem of one-bit DoA estimation, where the received signal is deliberately overdemodulated using multiple offset sinusoidal signals in the coherent analog down conversion before being processed by a one-bit ADC. Through numerical analysis, we reveal that the overdemodulation technique substantially enhances the accuracy of one-bit DoA estimation.

关键词： Direction-of-arrival estimation Accuracy array signal processing Numerical analysis Conferences Estimation sensors

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