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检索条件"任意字段=2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016"

共 1002 条记录，以下是151-160 订阅

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Sparse-signal processing on information-based range grid

Sparse-signal processing on information-based range grid

引用

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

作者： de Jong, Edwin Pribic, Radmila Univ Groningen Dept Appl Phys NL-9700 AB Groningen Netherlands Thales Nederland Delft Sensors Adv Dev Delft Netherlands

ISBN: (纸本)9781479914814

Radar obtains its parameters on an estimation grid whose cell size is related to resolution of underlying radar processing. Existing radar exploits a regular grid (i.e. constant resolution) although the resolution changes with stronger echoes at shorter ranges. We compute radar resolution from the intrinsic geometrical structure of data models that is characterized by the Fisher information. Based on this information-geometry approach, we create an estimation grid whose cells have a constant information distance. In addition, we explore how such an irregular estimation grid can suit radar processing in practice, and propose applying the information-based grid with the sparse-signal processing from compressive sensing. This novel radar processing is applied in an one-dimensional case of range estimation, with emphasis on the grid effects to the sensing incoherence. Results reveal the new flexibility in radar design.

关键词： sparse signals compressive sensing information geometry Fisher information distance radar resolution

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Blind identification of under-determined complex mixtures of independent sources

Blind identification of under-determined complex mixtures of...

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3rd ieee sensor array and multichannel signal processing workshop

作者： Comon, P Rajih, M I3S Lab F-06903 Sophia Antipolis France

ISBN: (纸本)0780385454

This paper is devoted to under-determined linear mixtures of independent random variables (i.e. with more inputs than outputs). Blind identifiability of general under-determined mixtures is first discussed, and the maximum number of sources is given, depending on the hypotheses assumed. Then an algorithm proposed by Taleb, essentially usable for 2-dimensional mixtures, is extended to the complex field. A procedure is proposed in order to avoid the enormous increase in complexity. Computer simulations demonstrate the ability of the algorithm to identify mixtures of N QPSK sources received on 1 or 2 sensors.

关键词： signal processing

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Multi-Tier Structured array for Sensing Pilot Design in Integrated Sensing and Communication 13

Multi-Tier Structured Array for Sensing Pilot Design in Inte...

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13rd ieee sensor array and multichannel signal processing workshop (sam)

作者： Ren, Jiaying Tsai, Shawn Mediatek USA Inc Adv Commun Technol Commun Syst Design San Diego CA 92128 USA

ISBN: (纸本)9798350344820;9798350344813

In this paper, we explore the use of large-scale sparse arrays for pilot placement in pilot-based sensing within integrated sensing and communication (ISAC) systems. Unlike conventional regular pilot placement method, sparse placement offers a significant reduction in overhead while maintaining high sensing performance. We present a novel large-scale sparse array construction method by introducing a multi-tier array structure. Using the proposed method, the design of large-scale sparse arrays can be simplified into several smaller-sized array design problems, significantly reducing computational complexity and storage requirements. Numerical examples demonstrate the effectiveness of the proposed method for low-overhead sensing pilot placement design, which is applicable in future 6G applications.

关键词： Integrated sensing and communication (ISAC) pilot design sparse array design orthogonal frequency division multiplexing (OFDM) 5G new radio 6G

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sensor array shape estimation using active sonar clutter

Sensor array shape estimation using active sonar clutter

引用

2nd ieee sensor array and multichannel signal processing workshop

作者： Varadarajan, V Krolik, J Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

ISBN: (纸本)0780375513

This paper concerns the problem of array shape estimation from clutter (ASEC) for a towed active sonar array. Although heading sensors can provide towed-array shape information, they are sometimes not sufficiently available or accurate to facilitate beamforming with low sidelobe levels necessary for detection of low-Doppler targets, especially in the presence of severe bottom reverberation. We propose a maximum likelihood array shape calibration technique that exploits the azimuth-Doppler frequency relationship of the clutter by fitting the reverberation snapshots from a single sonar ping to the low rank space-time clutter subspace.

关键词： Sonar

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Interferometric imaging of a rotating sphere using synthetic aperture techniques

Interferometric imaging of a rotating sphere using synthetic...

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1st ieee sensor array and multichannel signal processing workshop (sam 2000)

作者： Rieken, DW Fuhrmann, DR Washington Univ Dept Elect Engn Elect Syst & Signals Res Lab St Louis MO 63130 USA

ISBN: (纸本)0780363396

Interferometry has been used for decades to image distant electromagnetic sources at long wavelengths. However, the long data collection intervals have prevented imaging rotating objects such as planets. We will show that one can craft an interferometric imaging algorithm using synthetic aperture beamforming techniques by doing linear beamforming on the correlation domain data rather than the signal-domain data. We will then use this analogy to show how it is possible to create previously unrealized interferometric images of a rotating spherical blackbody.

关键词： Antenna arrays array signal processing Band pass filters Correlators Directive antennas Frequency Jupiter Laboratories Radio astronomy Radio interferometry

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processing-aware compression for sensor networks

Processing-aware compression for sensor networks

引用

2nd ieee sensor array and multichannel signal processing workshop

作者： Vasudevan, L Ortega, A Univ So Calif Dept Elect Engn Inst Signal & Image Proc Integrated Media Syst Ctr Los Angeles CA 90089 USA

ISBN: (纸本)0780375513

In sensor networks, where power and bandwidth are at a premium, there is a clear need to use compression to limit the amount of information exchanged by the sensors. In this paper we study the signal compression problem in situations where signals are being processed for the purpose of source localization. In these scenarios compression should be optimized for the accuracy of source localization, rather than to provide a reproduction of the signals with some desired fidelity. We show how this leads to novel design techniques that have clear advantages over standard quantizer design approaches.

关键词： sensor networks

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Optimal Precoding Design for Decentralized Detection of Deterministic signals

Optimal Precoding Design for Decentralized Detection of Dete...

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

作者： Fang, Jun Li, Hongbin Chen, Zhi Li, Shaoqian Univ Elect Sci & Technol China Natl Key Lab Commun Chengdu 610054 Peoples R China Stevens Inst Technol Dept Elect & Comp Engn Hoboken NJ 07030 USA

ISBN: (纸本)9781467310710

We consider a decentralized detection problem in a power-constrained wireless sensor networks (WSNs), in which a number of sensor nodes collaborate to detect the presence of a deterministic vector signal. The signal to be detected is assumed known a priori. Each sensor conducts a local linear processing to convert its observations into one or multiple messages. The messages are conveyed to the fusion center (FC) by an uncoded amplify-and-forward scheme, where a global decision is made. Given a total network transmit power constraint, we investigate the optimal linear processing strategy for each sensor. Our study finds that the optimal linear precoder has the form of a matched filter. Depending on the channel characteristics, one or multiple versions of the filtered/compressed message should be reported to the FC.

关键词： Decentralized detection precoding design wireless sensor networks

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Fast rank-adaptive beamforming

Fast rank-adaptive beamforming

引用

1st ieee sensor array and multichannel signal processing workshop (sam 2000)

作者： McWhorter, T Mission Res Corp Monterey CA 93940 USA

ISBN: (纸本)0780363396

This paper is concerned with the construction of an adaptive beamformer, which uses the dominant subspace information of a sample covariance matrix. We assume that the sample covariance matrix and its eigenvalue decomposition (EVD) are to be updated as data arrive. We present a unified structure for updating the EVD and introduce a robust method for adapting the rank of the dominant subspace. We use the EVD of the sample covariance matrix to build a fast rank- and weight-adaptive beamformer. A useful component of the beamforming routine is a fast algorithm for updating the estimates of the direction of arrival of the dominant sources.

关键词： Algorithm design and analysis array signal processing Bibliographies Covariance matrix Eigenvalues and eigenfunctions Joining processes Matrix decomposition Performance evaluation Robustness Stochastic processes

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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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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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