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检索条件"任意字段=4th IEEE Sensor Array and Multichannel Signal Processing Workshop"

共 931 条记录，以下是161-170 订阅

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Statistical Angular Resolution Limit for array Radar with Ultrawideband Stochastic signals

Statistical Angular Resolution Limit for Array Radar with Ul...

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8th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Zhou, Xiaoli Wang, Hongqiang Cheng, Yongqiang Qin, Yuliang Chen, Haowen Sun, Bin Natl Univ Def Technol Sch Elect Sci & Engn Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781479914814

the 2-D angular resolution limit for array radar with ultrawideband (UWB) stochastic signals based on the statistical resolution theory is presented in this paper. the signal model of monostatic array radar with circular array configuration and UWB stochastic signals is established, while the resolution of two closely spaced targets is modelled as a binary hypothesis test. the statistical angular resolution limit (SARL) for array radar with UWB stochastic signals is derived based on the generalized likelihood ratio test (GLRT) with given probabilities of false alarm and detection. the effects of detection parameters, transmit waveforms, array geometry, signal-to-noise ratio and parameters of target on SARL are analysed. Compared with the conventional resolution defined by ambiguity function, the SARL reflects the practical resolution ability of radar and can provide an optimization criterion for radar system design.

关键词： array radar Ultra wideband technologies ANGULAR RESOLUTION resolution limit optimal criterion signals Resolving power Stochastic False alarms

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A Sparse Regularization Technique for Source Localization with Non-uniform sensor Gain

A Sparse Regularization Technique for Source Localization wi...

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8th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Weiss, Christian Zoubir, Abdelhak M. Tech Univ Darmstadt Germany Signal Proc Grp D-64283 Darmstadt Germany Grad Sch Computat Engn D-64293 Darmstadt Germany

ISBN: (纸本)9781479914814

A robust sparse regularization technique with applications to source localization in the presence of non-uniform gain distribution is presented. As a key component in sparse optimization, a proper choice of the regularization parameter is crucial. It renders high impact on the localization performance and has to account for any kind of model perturbation. Our proposed technique utilizes a statistical framework to provide a direct relation between the physical system parameters and the regularization parameter of the resulting optimization problem. It addresses the joint effects of sensor gain variations and noise. As a figure of merit, we consider the mean-squared error (MSE) between the perturbed measurements and the assumed underlying model. An upper bound of the MSE is attained in order to estimate the regularization parameter. the presented method shows good performance for moderate gain variances even in low SNR regimes.

关键词： sparse regularization model errors source localization robust model non-uniform sensor gain

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Direction of Arrival Estimation Using Nested Vector-sensor arrays Via Tensor Modeling

Direction of Arrival Estimation Using Nested Vector-Sensor A...

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8th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Han, Keyong Nehorai, Arye Washington Univ Preston M Green Dept Elect & Syst Engn St Louis MO 63130 USA

ISBN: (纸本)9781479914814

We propose a new class of nested vector-sensor arrays, via tensor modeling, which is capable of increasing the number of degrees of freedom (DOFs) for direction-of-arrival (DOA) estimation, compared with the uniform linear array (ULA). By using one component's information of the interspectral tensor, the proposed nested vector-sensor array can provide O(N-2) DOFs with only N physical sensors. To utilize the increased DOFs, a novel spatial smoothing approach is proposed, which preserves the data structure and avoids reorganization via tensor modeling. Further, we propose corresponding direction of arrival (DOA) estimation strategies. Based on the analytical results, we consider two main applications: electromagnetic (EM) vector sensors and acoustic vector sensors. We show that the DOA estimation performance is greatly improved due to the combination of the nested-array strategy and tensor modeling. the effectiveness of the proposed methods is verified through numerical examples.

关键词： Direction of arrival estimation nested array electromagnetic vector sensors acoustic vector sensors tensor

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DOA Estimation Using Coarray Interpolation Algorithm Via Nuclear Norm Optimization for Coprime MIMO Radar 11

DOA Estimation Using Coarray Interpolation Algorithm Via Nuc...

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ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Zheng, Yu Guo, Muran Liu, Lutao Harbin Engn Univ Coll Informat & Commun Engn Harbin Peoples R China 14th Res Inst Elect Technol Grp Corp Nanjing Peoples R China

ISBN: (纸本)9781728119465

As the coprime array develops, the coprime multiple-input multiple-output (MIMO) radar has been proposed to achieve a large array aperture. However, holes also exist in the sum-difference coarray of the coprime MIMO radar, thus making the lags out of continuous range unavailable for the subspace based direction of arrival (DOA) estimation algorithm. In this paper, a coarray interpolation algorithm is proposed for the coprime MIMO radar to improve the estimation performance. the interpolation is completed by solving a nuclear norm based optimization problem, where the Toeplitz structure of the interpolated covariance matrix is exploited to reduce the computational complexity. the lags that are not continuous are utilized by using the proposed algorithm. thus, the number of degrees of freedom (DOFs) and the estimation accuracy are improved. Numerical simulations are designed to examine the corresponding estimation performance.

关键词： DOA estimation MIMO radar Nuclear norm

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sensor Network Distributed Computation for Direct Position Determination

Sensor Network Distributed Computation for Direct Position D...

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ieee 7th sensor array and multichannel signal processing workshop (SAM)

作者： Pourhomayoun, Mohammad Fowler, Mark L. SUNY Binghamton Dept Elect & Comp Engn Binghamton NY 13902 USA

ISBN: (纸本)9781467310710

Classical localization systems based on TDOA/FDOA use a two-stage estimation approach. In the first stage, pairs of sensors share data to estimate TDOA/FDOA. then, the extracted TDOA/FDOA measurements are used to estimate the emitter location. In some recently published methods, an optimal single-stage approach named Direct Position Determination (DPD) has been proposed to improve the position estimation accuracy. However, unlike the classical two-stage method where the TDOA/FDOA estimation can be distributed across all sensors, DPD processes all the received signals together at a single sensor node. However, when sensors have limited computational capabilities it is desirable to distribute the computation across all sensors. Furthermore, concentrating all the processing into a single node makes the location system less robust to the loss of sensors. In this paper, we develop a distributed localization method with the goal of reducing the computational load on each sensor and increasing the reliability of the system.

关键词： Time difference of arrival

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Microphone array Beampattern Characterization for Hands-free Speech Applications

Microphone Array Beampattern Characterization for Hands-free...

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ieee 7th sensor array and multichannel signal processing workshop (SAM)

作者： Taghizadeh, Mohammad J. Garner, Philip N. Bourlard, Herve Idiap Res Inst Lausanne Switzerland Idiap Res Inst EPFL Lausanne Switzerland

ISBN: (纸本)9781467310710

Spatial filtering is the fundamental characteristic of microphone array based signal acquisition, which plays an important role in applications such as speech enhancement and distant speech recognition. In the array processing literature, this property is formulated upon beam-pattern steering and it is characterized for narrowband signals. this paper proposes to characterize the microphone array broadband beam-pattern based on the average output of a steered beamformer for a broadband spectrum. Relying on this characterization, we derive the directivity beam-pattern of delay-and-sum and superdirective beamformers for a linear as well as a circular microphone array. We further investigate how the broadband beam-pattern is linked to speech recognition feature extraction;hence, it can be used to evaluate distant speech recognition performance. the proposed theory is demonstrated with experiments on real data recordings.

关键词： Broadband beam-pattern Delay-and-sum beamformer Superdirective beamformer Distant speech recognition

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Angular Information Resolution Limit of sensor arrays

Angular Information Resolution Limit of Sensor Arrays

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8th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Cheng, Yongqiang Wang, Xuezhi Moran, Bill Natl Univ Def Technol Sch Elect Sci & Engn Beijing Peoples R China Univ Melbourne Melbourne Sch Engn Dept Elect & Elect Engn Melbourne Vic 3010 Australia Univ Melbourne Melbourne Sch Engn Def Sci Inst Melbourne Vic 3010 Australia

ISBN: (纸本)9781479914814

A measure of the ability of a sensor array to resolve two closely spaced point sources in angle is proposed here based on the framework of information geometry. the consideration of the geometric structure of a measurement model leads to the concept of information resolution which serves as a new metric to measure intrinsic similarities and differences between signal distributions that generate the manifold geometry. the statistical divergence between two sources is characterized in terms of the geodesic distance induced by the Fisher information metric. An analytical expression of the angular information resolution limit (AIRL) is derived using the constraints on the probability of error for a binary hypothesis test associated with the resolution of two sources. the influence of the detection error as well as the signal-to-noise ratio (SNR) on resolvability are demonstrated. the proposed AIRL can be used as a performance measure for sensor arrays in localizing remote sources and is applicable to various applications (e.g. radar, sonar, or astronomy).

关键词： Geometry

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A Variational Bayesian Approach to Direction Finding of Correlated Targets Using Coprime array 11

A Variational Bayesian Approach to Direction Finding of Corr...

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ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Yang, Jie Yang, Yixin Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Shaanxi Peoples R China

ISBN: (纸本)9781728119465

In this paper, we develop a sparsity-aware algorithm for direction-of-arrival (DOA) estimation of correlated targets in the context of coprime array processing. the idea is to iteratively interpolate the observed data to a virtual nonuniform linear array (NLA) in order to raise the degrees of freedom (DOF). We derive the estimation procedures using variational inference for fully Bayesian estimation, where the current parameter estimates are used to interpolate the observed data better and thus increase the likelihood of the next parameter estimates. the novelties of our method lies in its capacity of detecting more correlated sources than the number of physical sensors. Simulated data from coprime arrays are used to illustrate the superior performance of the proposed approach as compared with other state-of-the-art compressed sensing reconstruction algorithms.

关键词： Direction-of-arrival (DOA) estimation Coprime array Degrees of freedom (DOF) Variational inference

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Source counting in real-time sound source localization using a circular microphone array

Source counting in real-time sound source localization using...

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ieee 7th sensor array and multichannel signal processing workshop (SAM)

作者： Pavlidi, Despoina Griffin, Anthony Puigt, Matthieu Mouchtaris, Athanasios FORTH ICS GR-70013 Iraklion Crete Greece

ISBN: (纸本)9781467310710

Recently, we proposed an approach inspired by Sparse Component Analysis for real-time localization of multiple sound sources using a circular microphone array. the method was based on identifying time-frequency zones where only one source is active, reducing the problem to single-source localization for these zones. A histogram of estimated Directions of Arrival (DOAs) was formed and then processed to obtain improved DOA estimates, assuming that the number of sources was known. In this paper, we extend our previous work by proposing three different methods for counting the number of sources by looking for prominent peaks in the derived histogram based on: (a) performing a peak search, (b) processing an LPC-smoothed version of the histogram, (c) employing a matching pursuit-based approach. the third approach is shown to perform very accurately in simulated reverberant conditions and additive noise, and its computational requirements are very small.

关键词： Additive noise

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Fast direction of arrival estimation using a sensor-saving coprime array with enlarged inter-element spacing 10

Fast direction of arrival estimation using a sensor-saving c...

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10th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Li, Jianfeng Shen, Mingwei Jiang, Defu Hohai Univ Array & Informat Proc Lab Coll Comp & Informat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538647523

Direction of arrival (DOA) estimation using coprime array is discussed, and a fast method using a sensor-saving coprime array with enlarged inter-element spacing is proposed. Original coprime array combines the results obtained from two coprime subarrays to uniquely determine the DOA estimation, and it is shown in this paper that one subarray actually only requires half of its original sensor number and can achieve enlarged inter-element spacing based on the array compensation from the cross correlation matrix. thereafter, a fast DOA estimation method, which extracts the noise subspace without eigenvalue decomposition, is proposed to obtain coprime DOA estimations based on one dimensional root finding technique. Final unique DOA is estimated from the coincide results of the coprime estimations. Simulation results verify that the proposed method can achieve almost the same estimation performance as conventional methods while requiring less sensors.

关键词： direction of arrival estimation coprime array sensor-saving enlarged inter-element spacing

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