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检索条件"任意字段=2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010"

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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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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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Channel Estimation for Hybrid MIMO Communication with (Non-) Uniform Linear arrays via Tensor Decomposition

Channel Estimation for Hybrid MIMO Communication with (Non-)...

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sensor array and multichannel signal processing workshop

作者： Ali Koochakzadeh Piya Pal Electrical and Computer Engineering Department University of California San Diego

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper considers the problem of channel estimation for millimeter wave wireless communication channels. Many existing channel estimation approaches utilize the spatial sparsity of mmWave channels and employ compressive sensing based techniques to estimate the parameters of the channel, such as the Angles of Arrival (AoA) and Angles of Departure (AoD) of the channel paths. In this paper, we show how the problem of channel estimation can be converted into a fourth order tensor decomposition problem, which offers several benefits. Firstly, we do not need a grid-based search for the angles. More importantly, our algorithm is applicable for both uniform and non-uniform arrays at the transmitter and receiver. In particular, our method can exploit well-known benefits offered by the difference co-array of suitably designed sparse arrays and provably identify a larger number of channel paths compared to existing approaches 1 .

关键词： Wireless communication Radio frequency Sufficient conditions Tensors Transmitters Channel estimation signal processing algorithms

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Power Allocation Strategy for OFDM Waveform in RadCom Systems

Power Allocation Strategy for OFDM Waveform in RadCom System...

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sensor array and multichannel signal processing workshop

作者： Mohammad A.B. Mohammad Guolong Cui Xianxiang Yu Mohammad Ahmed Ashenafi Yadessa Gemechu School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

At present, the integrated radar and communication (RadCom) system has attracted much attention. It has several advantages such as power consumption, reducing system size, weight,...etc. This paper proposes a power allocation strategy for the RadCom system in signal-dependent clutter, where both systems use the Orthogonal Frequency Division Multiplexing (OFDM) waveform. The convex optimization problem is formulated and solved analytically by using the Karush-Kuhn-Tuckers (KKT) optimality conditions. The proposed strategy minimizes the total transmitted power while fulfilling the two systems requirements i.e., signal-to-Clutter-plus-Noise Ratio (SCNR) for the target detection performance and Data Information Rate (DIR) for the communication system performance. Finally, the simulation results are presented to verify the effectiveness of the proposed power allocation strategy.

关键词： Power demand OFDM Simulation Radar Radar signal processing Resource management Clutter

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Multi-Channel Spaceborne SAR Imaging Method for Maritime Scenarios

Multi-Channel Spaceborne SAR Imaging Method for Maritime Sce...

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sensor array and multichannel signal processing workshop

作者： Xiaolan Qiu Junying Yang Mingyang Shang Lihua Zhong Chibiao Ding Key Laboratory of Technology in GeoSpatial Information Processing and Application Systems Aerospace Information Research Institute Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

The spaceborne SAR is required to fulfill the increasing demands for improved spatial resolution and wider swath coverage in recent years. The azimuth multi-channel SAR system is a typical technique adopted for realizing high-resolution and wide-swath (HRWS) simultaneously. The flexibility of this system also provides favorable conditions for moving target detection. Aiming at the problems of moving target detection, velocity estimation, and imaging of SAR maritime scenes in the spaceborne multi-channel system, this paper proposes a set of processes based on coarse imaging, detection, velocity estimation and refocusing. The experimental results of the simulation verify the effectiveness of the method.

关键词： Azimuth Conferences Imaging Estimation Object detection Radar polarimetry Doppler effect

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Gridless Sparsity-Based Localization for Near-Field Sources with Symmetric Linear array

Gridless Sparsity-Based Localization for Near-Field Sources ...

引用

sensor array and multichannel signal processing workshop

作者： Weiliang Zuo Jingmin Xin Tong Xiao Nanning Zheng Akira Sano Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China Department of System Design Engineering Keio University Yokohama Japan

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, we investigate the problem of estimating the directions-of-arrival (DOAs) and ranges of multiple nearfield narrowband sources impinging on a symmetric uniform linear array (ULA). By forming a Toeplitz-like correlation matrix from the anti-diagonal elements of the array covariance matrix, a convex optimization problem for the resultant Toeplitz-like matrix reconstruction is established and further a gridless sparsity-based localization for near-field sources is proposed. The DOAs can then be retrieved by using the recovered correlation matrix according to root-MUSIC or Vandermonde decomposition theorem. Additionally, the ranges are obtained through a subspace-based estimator with the corresponding estimated DOAs, while the association of the estimated DOAs and ranges are completed at the same time. Finally, the numerical examples are provided to substantiate the performance of our proposed method, and the simulation results demonstrate that the proposed method provides remarkable and satisfactory estimation performance.

关键词： Location awareness Direction-of-arrival estimation Symmetric matrices Correlation Simulation Estimation Convex functions

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Rank regularized beamforming in single group multicasting networks

Rank regularized beamforming in single group multicasting ne...

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sensor array and multichannel signal processing workshop

作者： Dima Taleb Marius Pesavento Communication Systems Group Technische Universität Darmstadt Darmstadt Germany

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In multicasting networks, a multi-antenna base station transmits the same information to a single group of users. In this work we consider general rank beamforming using orthogonal space-time block codes (OSTBC)s. The beamforming problem is non-convex and generally NP hard. The semidefinite relaxation technique is employed to solve the problem. In order to control the rank of the beamforming solution we propose to replace the power minimization by a regularized volume minimization which is known as a surrogate for the rank minimization. We propose an iterative two scale algorithm to find the appropriate value for the regularization parameter that yields the desired rank and to compute stationary points of the corresponding optimization problem. The high computational complexity of the proposed algorithm is improved significantly using a one scale algorithm, where the value of the regularization variable is reduced along with the decreasing rank. Simulation results demonstrate that our algorithms outperform the stateof-the-arts procedures in terms of the transmitted power and symbol error rate (SER). For a proper setting of the regularization variable, one scale algorithm outperforms the best compared methods in terms of computational complexity.

关键词： Multicast algorithms array signal processing Simulation signal processing algorithms Multicast communication Minimization Approximation algorithms

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Mainlobe Jamming Suppression Via Independent Component Analysis for Polarimetric SIMO Radar

Mainlobe Jamming Suppression Via Independent Component Analy...

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sensor array and multichannel signal processing workshop

作者： Mengmeng Ge Guolong Cui Zhenghong Zhang Lin Zhou Xianxiang Yu Feng Yang Lingjiang Kong School of Information and Communication Engineering University of Electronic Science and Technology of China Science and Technology on Electronic Information Control Laboratory Chengdu China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

The presence of mainlobe jamming will significantly reduce the radar detection capabilities. Conventional independent component analysis (ICA)-based methods will suffer from the ineffectiveness when the angle of the target is same as that of the jammer. In this paper, exploring polarization characteristics, we propose an approach based on ICA for polarimetric SIMO (P-SIMO) radar to resist mainlobe jamming. Specifically, the signal model of P-SIMO radar accounting for the target and jamming signals is derived. Then, the approach based on ICA is utilized to separate the target component and jamming component while achieving the mainlobe jamming suppression. Finally, the effectiveness and capacities of proposed method are demonstrated by simulations, and the results show that the proposed method outperforms conventional ICA-based method.

关键词： Radar detection Radar Independent component analysis Resists Numerical simulation Radar polarimetry Radar signal processing

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Direct Adaptive Equalization with CFO Pre-compensation for Single-Carrier Underwater Acoustic Communications

Direct Adaptive Equalization with CFO Pre-compensation for S...

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sensor array and multichannel signal processing workshop

作者： Jun Tao Fengzhong Qu Hongtao Zhang Key Laboratory of Underwater Acoustic Signal Processing of the Ministry of Education School of Information Science and Engineering Southeast University Nanjing China Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Zhejiang University Zhoushan China Hangzhou Applied Acoustics Research Institute Hangzhou China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

For single-carrier underwater acoustic (UWA) communications, phase correction is critical to the symbol detection on the receiver side. Existing receiver schemes either run a phase- locked loop (PLL) in parallel with an equalizer or perform the phase correction at the output of an equalizer. Both parallel and serial phase correction methods suffer limitations in practical use though. In this work, we propose to introduce a carrier frequency offset (CFO) pre-compensation module for existing receivers, with the CFO estimated with an m-sequence. The so-obtained receiver scheme was tested by real data collected in an at-sea UWA communication trial. Experimental results verified the extra performance gain brought by the CFO precompensation. In particular, when the CFO is the main source of phase rotation, conventional CFO correction modules like the PLL can be dropped without performance degradation.

关键词： Degradation array signal processing Conferences Receivers Performance gain Adaptive equalizers Frequency estimation

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Automotive Dual-Function Radar Communications Systems: An Overview

Automotive Dual-Function Radar Communications Systems: An Ov...

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sensor array and multichannel signal processing workshop

作者： Dingyou Ma Nir Shlezinger Tianyao Huang Yimin Liu Yonina C. Eldar Department of Electronic Engineering Tsinghua University Beijing China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Future cars will constantly sense the environment and interchange information with their surrounding in order to successfully choose routes, avoid hazards, and comply with traffic regulations. These vehicles will be equipped with multiple sensors, including automotive radar, as well as wireless communications capabilities. The similarity in hardware and signal processing of automotive radar and wireless communications motivates designing these functionalities in a joint manner. Such dual function radar-communications (DFRC) designs are the focus of a large body of recent works. These joint designs lead to substantial gains in size, cost, power consumption, and performance, making them especially important for vehicular applications, where both the radar and communications operate in similar ranges. This paper reviews a wide variety of existing DFRC strategies and their relevance to automotive systems. We discuss the pros and cons of current methods, mapping them in the context of vehicular application, and present the main challenges and possible research directions.

关键词： Wireless communication Power demand Radar signal processing sensor systems Regulation Hazards sensors

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