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

共 2593 条记录，以下是311-320 订阅

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Channel Estimation and Indoor Positioning for Wideband Multiuser Millimeter Wave Systems

Channel Estimation and Indoor Positioning for Wideband Multi...

引用

sensor array and multichannel signal processing workshop

作者： Yuxing Lin Shi Jin Michail Matthaiou Xiaohu You National Mobile Communications Research Laboratory Southeast University Nanjing P. R. China Institute of Electronics Communications and Information Technology (ECIT) Queen’s University Belfast Belfast U.K

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

We focus on channel estimation and indoor positioning of wideband multiuser millimeter wave systems. Leveraging the sparse channel characteristics, we transform the estimation problem to recovery problems of multipath parameters, e.g., angle of arrival, time delay and path fading. We model the training signal as a matricization form of a third-order canonical polyadic tensor, which consists of three factor matrices containing channel information. Inspired by array signal processing methods, we exploit the structural feature of our tensor and develop an uniqueness condition of tensor factorization, leading to a tensorbased channel estimation algorithm. In order to distinguish the multiuser signal components, we further develop a clusteringaided indoor positioning scheme. Simulation results show that the proposed methods apply to different system configurations and can achieve satisfactory estimation and positioning performance.

关键词： Training Tensors Millimeter wave technology Channel estimation signal processing algorithms Clustering algorithms Estimation

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Waveform Design for Dual-function MIMO Radar-communication Systems

Waveform Design for Dual-function MIMO Radar-communication S...

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sensor array and multichannel signal processing workshop

作者： Bo Tang Hai Wang Lilong Qin Longxiang Li College of Electronic Engineering National University of Defense Technology Hefei China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper addresses the design of constant-modulus waveforms for a dual-function multiple-input-multiple-output (MIMO) radar-communication system. The purpose of the design is to match a desired beampattern for radar sensing, and minimize the transmission distortion of communication signals. To tackle the non-convex waveform design problem, we develop an iterative algorithm based on cyclic optimization and majorization-minimization (MM). We show that the proposed algorithm has guaranteed convergence of the objective values. Numerical results demonstrate that the transmit beampattern of the synthesized waveforms can well approximate the desired one, and the emitted communication signals from the dual-function system has little distortions.

关键词： signal processing algorithms Radar Distortion Approximation algorithms sensors Iterative methods MIMO communication

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Single-Snapshot Beamforming using Fast Iterative Adaptive Techniques

Single-Snapshot Beamforming using Fast Iterative Adaptive Te...

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sensor array and multichannel signal processing workshop

作者： Aboulnasr Hassanien Elias Aboutanios Department of Electrical Engineering Wright State University Dayton OH USA School of Electrical Engineering and Telecommunications University of New South Wales Sydney Australia

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, we consider the problem of adaptive beamforming for sample-starved scenarios. A beamforming design method is developed for the case when the only available data is a single-snapshot that is contaminated by the signal-of-interest. Instead of using the non-invertible rank-one sample covariance matrix, the proposed method reconstructs the interference-plus-noise covariance matrix via estimating the interference signal component(s) and the noise variance. The computationally-efficient fast iterative interpolated beamforming (FIIB) algorithm is used to estimate the spatial frequencies and complex amplitudes associated with the interference. The reconstructed covariance matrix is used for adaptive beamforming design. Unlike existing sparsity-based covariance reconstruction techniques, the proposed method is able to reconstruct off-grid interference components and its performance is shown to not suffer from estimation bias. Simulation examples are used to demonstrate the performance superiority of the proposed method over other adaptive single-snapshot beamforming techniques.

关键词： Adaptation models array signal processing Design methodology signal processing algorithms Estimation Interference Iterative algorithms

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The Underwater Acoustic Image Measurement Based on Non-uniform Spatial Resampling RL Deconvolution

The Underwater Acoustic Image Measurement Based on Non-unifo...

引用

sensor array and multichannel signal processing workshop

作者： Jidan Mei Yuqing Pei Chao Ma Yunfei Lv Qiuying Peng Acoustic Science and Technology Laboratory Harbin Engineering University

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

When the near-field underwater acoustic image (UAI) measurement is carried out by the line array laid on the sea floor, the resolution of the conventional beamforming (CBF) acoustic image measurement method is poor, the sidelobe level is high, while the deconvolution algorithm has the effect of high resolution and low sidelobe. However, the direct deconvolution algorithm of the point spread function (PSF) shift-variant model has a large computational burden. This paper presents a non-uniform spatial resampling Richardson-Lucy (RL) fast algorithm, which based on energy distribution of conventional acoustic image measurement result make the original uniform space scanning to non-uniform spatial resampling. It can reduce the number of scanning grid, so as to reduce the amount of computation. Simulation results show that the fast RL algorithm can achieve the performance close to the original RL algorithm by reducing the computational amount by nearly an order of magnitude.

关键词： Deconvolution array signal processing Computational modeling signal processing algorithms Sea measurements Acoustic measurements Acoustic arrays

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Collaborative Spectrum Allocation and Waveform Design for Radar Coexistence

Collaborative Spectrum Allocation and Waveform Design for Ra...

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sensor array and multichannel signal processing workshop

作者： Ishai Eljarat Joseph Tabrikian Igal Bilik School of ECE Ben-Gurion University of the Negev Beer-Sheva Israel General Motors Israel Technical Center Herzliya Israel

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

The emerging problem of automotive radars congestion is addressed in this work. Modern automotive radars handle this problem via randomization of the transmit signal parameters. Alternatively, frequency allocation methods lead to narrow-band radar operation and as a result, reduced range resolution. This work proposes to mitigate the mutual interference between radars, while optimizing the localization performance by collaborative spectrum allocation and waveform design. According to the proposed approach, the transmit energy is allocated across the entire available spectrum by minimization of the Weiss-Weinstein bound. The proposed spectrum allocation approach allows to avoid frequencies occupied by interfering radars and the use of the entire spectrum allows to achieve the maximal possible resolution.

关键词： Energy resolution Estimation Radar Interference Minimization Radar signal processing Resource management

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Weak Target Detection in MIMO Radar via Beamspace Canonical Correlation

Weak Target Detection in MIMO Radar via Beamspace Canonical ...

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sensor array and multichannel signal processing workshop

作者： Mohamed Salah Ibrahim Nicholas D. Sidiropoulos Dept. of Electrical and Computer Engineering University of Virginia Charlottesville VA

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Reliable detection and accurate estimation of weak targets and their Doppler frequencies is a challenging problem in MIMO radar systems. Reflections from such targets are often overpowered by those from stronger nearby targets and clutter. Considering a 3-D data model where the coherent processing interval comprises multiple pulses, a novel weak target detection and estimation approach is proposed in this paper. The proposed method is based on creating partially overlapping spatial beams, and performing canonical correlation analysis (CCA) in the resulting beamspace. It is shown that if a target is present in the overlap sector, then its Doppler profile can be reliably estimated via beamspace CCA, even if hidden under much stronger interference from nearby targets and clutter. Numerical results are included to validate this theoretical claim, demonstrating that the proposed Beamspace Canonical Correlation (BCC) method yields considerable performance improvement over existing approaches.

关键词： Correlation array signal processing MIMO radar Estimation Object detection Reliability theory Reflection

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2020 IEEE 21st International workshop on signal processing Advances in Wireless Communications, SPAWC 2020

2020 IEEE 21st International Workshop on Signal Processing A...

引用

21st IEEE International workshop on signal processing Advances in Wireless Communications, SPAWC 2020

ISBN: (纸本)9781728154787

The proceedings contain 138 papers. The topics discussed include: multi-array designs for mmWave and sub-THz communication to UAVs;interaction-based detection strategy against probabilistic SSDF attack in CSS network;intelligent reflecting surface aided multiple access: capacity region and deployment strategy;joint channel coding and modulation via deep learning;linear precoder design for physical layer security via reconfigurable intelligent surfaces;ordered gradient approach for communication-efficient distributed learning;high rate communication over one-bit quantized channels via deep learning and LDPC codes;direction of arrival estimation of digital sources with uni-vector-sensor ESPRIT;and energy efficiency optimization in UAV-assisted communications and edge computing.

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Robust Super-resolution Frequency Division Duplex (FDD) Channel Estimation

Robust Super-resolution Frequency Division Duplex (FDD) Chan...

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sensor array and multichannel signal processing workshop

作者： Yan Liu Xue Jiang School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Channel estimation is the process of estimating channel parameters from the received samples, which are corrupted by noise. Most of the conventional methods are designed for noise-free or Gaussian noise environment. However, impulsive noise, which is also referred to as outliers, is common in practice and performance of the conventional algorithms degrades in the presence of outliers. In this paper, we propose a robust super-resolution channel estimation algorithm to deal with outliers by replacing ℓ 2 -norm constraints with ℓ 1 -norm constraints to enhance robustness to outliers and solving an improved convex program to obtain the channel parameters, the angles and time delays then are estimated jointly. Simulation results show that the proposed robust super-resolution channel estimation algorithm outperforms the traditional methods and show great robustness to the outliers.

关键词： Parameter estimation Simulation Superresolution Channel estimation signal processing algorithms Frequency conversion Robustness

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DOA estimation using sparse Bayesian learning for colocated MIMO radar with dynamic waveforms

DOA estimation using sparse Bayesian learning for colocated ...

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sensor array and multichannel signal processing workshop

作者： Bingfan Liu Baixiao Chen Minglei Yang Hui Xu National Laboratory of Radar Signal Processing Xidian University Xi’an China School of Electronic Engineering Xidian University Xi’an China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, we proposed a direction of arrival (DOA) estimation method based on sparse Bayesian learning (SBL) and a dynamic transmitted waveform design method for colocated multiple-input multiple-output (MIMO) radar. First, the SBL DOA estimation method is introduced into the MIMO radar with arbitrary transmitted waveforms. Our theoretical derivation shows that the estimation error of the SBL method is related to the transmitted waveforms. Then, we minimize the estimation error to obtain an updated transmitted waveforms, which will be transmitted in the next pulse repetition period. Numerical simulations show that compared with traditional orthogonal waveforms, the optimized waveforms could achieve a lower Cramér-Rao bound (CRB) and smaller DOA estimation error using the SBL method.

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Aircraft Target Classification Based on CNN

Aircraft Target Classification Based on CNN

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sensor array and multichannel signal processing workshop

作者： Qingyuan Zhao Xin Du Yaobing Lu Beijing Insititute of Radio Measurement Beijing China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, we applied the idea of deep learning to aircraft targets recognition based on time-frequency diagram. Firstly we introduced application of Convolutional Neural Network (CNN), and the methods of radar target recognition. Secondly, Short Time Fourier Transformation (STFT) was introduced. Thirdly, the structure of improved LeNet CNN was described, considering the character of radar echo wave. Fourthly, 4 kinds of aircraft targets were introduced. Then, the algorithm based on CNN and STFT was validated based on measured data, and was compared with Support Vector Machine (SVM). The accuracy rate could reaches up to 99.98%, 25% higher than SVM. Finally, we summarized advantages of the method proposed in this paper and give the suggestion in engineering application.

关键词： Support vector machines Deep learning Time-frequency analysis Target recognition Weapons Feature extraction Radar signal processing

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