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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391-400 订阅

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Frequency Domain Trinicon-Based Blind Source Separation Method with Multi-Source Activity Detection for Sparsely Mixed signals

Frequency Domain Trinicon-Based Blind Source Separation Meth...

引用

sensor array and multichannel signal processing workshop

作者： Zelin Wang Jing Lu Kai Chen Key Laboratory of Modern Acoustics and Institute of Acoustics Nanjing University Nanjing People's Republic of China

The TRINICON (`Triple-N ICA for convolutive mixtures') framework is an effective blind signal separation (BSS) method for separating sound sources from convolutive mixtures. It makes full use of the non-whiteness, non-stationarity and non-Gaussianity properties of the source signals and can be implemented either in time domain or in frequency domain, avoiding the notorious internal permutation problem. It usually has best performance when the sources are continuously mixed. In this paper, the offline dual-channel frequency domain TRINICON implementation for sparsely mixed signals is investigated, and a multi-source activity detection is proposed to locate the active period of each source, based on which the filter updating strategy is regularized to improve the separation performance. The objective metric provided by the BSSEVAL toolkit is utilized to evaluate the performance of the proposed scheme.

关键词： Acoustics Conferences Speech processing array signal processing sensor arrays Blind source separation

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An Undersampled Phase Retrieval Algorithm via Gradient Iteration

An Undersampled Phase Retrieval Algorithm via Gradient Itera...

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sensor array and multichannel signal processing workshop

作者： Qiang Li Wei Liu Lei Huang Weize Sun Peichang Zhang College of Information Engineering Shenzhen University Shenzhen China Department of Electronic and Electrical Engineering University of Sheffield Sheffield United Kingdom

This work addresses the issue of undersampled phase retrieval using the gradient framework and proximal regularization theorem. It is formulated as an optimization problem in terms of least absolute shrinkage and selection operator (LASSO) form with (ℓ 2 +ℓ 1 ) norms minimization in the case of sparse incident signals. Then, inspired by the compressive phase retrieval via majorization-minimization technique (C-PRIME) algorithm, a gradient-based PRIME algorithm is proposed to solve a quadratic approximation of the original problem. Moreover, we also proved that the C-PRIME method can be regarded as a special case of the proposed algorithm. As demonstrated by simulation results, both the magnitude and phase recovery abilities of the proposed algorithm are excellent. Furthermore, the experimental results also show the mean square error (MSE) performance of the proposed algorithm versus iterative step.

关键词： signal processing algorithms Optimization array signal processing sensor arrays Conferences Approximation algorithms

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Energy Efficient Resource Optimization for a Downlink NOMA Heterogeneous Small-Cell Network

Energy Efficient Resource Optimization for a Downlink NOMA H...

引用

sensor array and multichannel signal processing workshop

作者： Fang Fang Julian Cheng Zhiguo Ding H. Vincent Poor School of Electrical and Electronic Engineering The University of Manchester UK School of Engineering The University of British Columbia Kelowna BC Canada Department of Electrical Engineering Princeton University rinceton NJ USA

Non-orthogonal multiple access (NOMA) is considered to be a key technology for fifth-generation mobile communication networks due to its superior spectral efficiency. In this paper, the problem of energy efficient subchannel and power allocation is investigated for a downlink NOMA heterogeneous network. The energy efficient resource allocation problem is first formulated as a mixed integer nonconvex optimization problem. By exploiting convex relaxation and dual decomposition techniques, a closed-form expression is derived via a Lagrangian approach. Simulation results show that the proposed algorithm can converge within ten iterations and obtain high system energy efficiency.

关键词： Resource management NOMA Interference Macrocell networks Sun Downlink array signal processing

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DOA Estimation Using Amateur Drones Harmonic Acoustic signals

DOA Estimation Using Amateur Drones Harmonic Acoustic Signal...

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sensor array and multichannel signal processing workshop

作者： Chaoqun Yang Zexian Wu Xianyu Chang Xiufang Shi Junfeng Wo Zhiguo Shi State Key Lab. of Industrial Control Technology Zhejiang University China

Drone localization plays an important role in anti-drone systems, which are designed for alleviating the threats brought by the illegal use of amateur drones. For the realization of drone localization, in this paper, we consider the problem of the direction-of-arrival (DOA) estimation of amateur drones. After formulating the acoustic signals of amateur drones by a harmonic model, we prove the validity of the multiple signal classification (MUSIC) algorithm under the harmonic model, and utilize it to estimate the DOAs of amateur drones. Further, we integrate this algorithm into a real-life drone tracking platform. Extensive field experimental results show that the drone tracking platform is capable of realizing the DOA estimation of an amateur drone with high accuracy.

关键词： Drones Harmonic analysis Direction-of-arrival estimation Estimation Acoustics Multiple signal classification signal processing algorithms

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Advanced Hybrid Beamforming Design for MIMO Systems

Advanced Hybrid Beamforming Design for MIMO Systems

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sensor array and multichannel signal processing workshop

作者： Bowen Yang Mehdi M. Molu Lei Zhang School of Engineering University of Glasgow Glasgow UK Samsung Cambridge Solution Centre(SCSC) Cambridge UK

One of the fundamental problems for hybrid beamformer design in MIMO systems is that, in Singular-Value-Decomposition (SVD) based beamforming, the analog beamformer is limited to constant modulus. In order to solve this issue, an algorithm is proposed in this paper. Specifically, the parallel data streams are expressed mathematically, and then the math expression of the analog beamformer is achieved through maximizing the power of desired data streams while minimizing the power of interference. Then, the digital part of the beamformer is calculated based on a channel equivalent process, i.e., considering the phase response vector of the derived analog beamformers as part of the channel observed by the digital beamformers. Simulations are performed on the proposed algorithm and compared to a recent state-of-the-art technique. The results show that the proposed one outperforms in terms of sphere of application (i.e., different antenna array sizes and channel sparsities).

关键词： Antenna arrays array signal processing signal processing algorithms Interference Radio frequency Scattering Complexity theory

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Mainlobe Deceptive Jammer Suppression with FDA-MIMO Radar

Mainlobe Deceptive Jammer Suppression with FDA-MIMO Radar

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sensor array and multichannel signal processing workshop

作者： Jingwei Xu Jialin Kang Guisheng Liao Hing Cheung So National Lab of Radar Signal Processing Xidian Univesity Xi'an Shaanxi China City University of Hong Kong Hong Kong China

Anti-jamming technique has become an increasing demand in radar systems due to the fast development of electronic countermeasures. To alleviate the extremely difficult deceptive jammer suppression problem, frequency diverse array (FDA) based multiple-input multiple-output (MIMO) radar is devised and a sample selection based deceptive jammer suppression method is developed. The basic principle of the FDA-MIMO radar regarding its superiority in canceling the deceptive jammers is studied in detail. In order to handle the pseudorandom distribution issue of false targets within the secondary training samples, a subspace projection based sample selection method is proposed. When certain a priori knowledge of the true target is available, the time-delayed false targets can be adequately suppressed, even if the latter are in the mainlobe direction. Simulation examples demonstrate the effectiveness of our solution.

关键词： Jamming array signal processing Delay effects Radar countermeasures Doppler radar

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A Method for Simultaneous Creation of an Acoustic Trap and a Quiet Zone

A Method for Simultaneous Creation of an Acoustic Trap and a...

引用

sensor array and multichannel signal processing workshop

作者： Carl Andersson Jens Ahrens Audio Technology Group Division of Applied Acoustics Chalmers University of Technology Gothenburg Sweden

An acoustical levitation trap can be created by maximizing the Laplacian of the Gor'kov potential and minimizing the pressure at a given location. Marzo et al. have successfully used Broyden-Fletcher-Goldfarb-Shanno minimization to find the phases to be imposed on the elements of an ultrasonic transducer array to create the required pressure field. We extend this method to create a field with one acoustical trap and a quiet zone at a different location. This can be used to, for example, create an independent second trap at the location of the quiet zone. We show through numerical simulations that it is possible to create such sound fields using ultrasonic arrays, and we demonstrate the advantages of the proposed approach over the direct design of a sound field with more than one trap. Our method can create a quiet zone extending almost two wavelengths without affecting the levitation trap.

关键词： Linear programming Acoustics Levitation Transducers array signal processing sensor arrays

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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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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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Robust Adaptive Beamforming signal Techniques for Drone Surveillance

Robust Adaptive Beamforming Signal Techniques for Drone Surv...

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sensor array and multichannel signal processing workshop

作者： Shangang Fan Jiangbo Liu Mengqian Tian Hao Huang Fei Dai Lie Yang Guan Gui NJUPT College of Telecommunication and Information Engineering Nanjing China UESTC School of Electronic Engineering Chengdu China

Drone surveillance poses a big technical challenge in the signal beamforming due to the drones' small size and low flying speed at low altitude collisions and etc. In a drone surveillance system, robust adaptive beamforming is required to identify suspicious targets. However, interference motion and array steering vector (ASV) mismatch problems often occurs in the situation of the antenna platform motion or propagation channel variability. To solve these problems, we propose a robust adaptive beamforming algorithms, which can broaden interference nulls. Specifically, by introducing a norm constraint, the proposed algorithm produces a broad trough at the direction of interference and adopts an idea of worst case performance optimization to robustly against the ASV mismatch. Simulation results demonstrate the validity of the proposed algorithm in terms of both output beampattern and signal-to-interference-plus-noise ratio (SINR).

关键词： Interference Covariance matrices array signal processing Robustness signal processing algorithms signal to noise ratio Antenna arrays

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