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Multi-sensor signal processing on a PSD matrix manifold

Multi-sensor signal processing on a PSD matrix manifold

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Wong, Kon Max Zhang, Jian-Kang Jiang, Huiying School of Information Engineering Zhengzhou University Zhengzhou China Dept of Electrical and Computer Engineering McMaster University Hamilton Canada

ISBN: (纸本)9781509021031

We propose to use the power spectral density (PSD) matrices of the received signals of a multi-sensor system as the feature of processing. PSD matrices have structural constraints and they form a manifold in signal space. We introduce two new Riemannian distance (RD) measures on the PSD matrix manifold and developed algorithms to locate the means and medians of PSD matrices in terms of these RD. These concepts are then applied to the detection of narrow-band sonar signals in noise and the results are encouraging. © 2016 ieee.

关键词： Covariance matrix

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Privacy-aware decentralized detection using linear precoding

Privacy-aware decentralized detection using linear precoding

引用

2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： He, Xin Tay, Wee Peng Sun, Meng Department of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781509021031

We study a nonparametric decentralized detection problem in which sensors send information to a fusion center that uses a support vector machine to make decisions about a public hypothesis. However, the same sensor information may also be used by the fusion center to infer about a private hypothesis, which the sensors wish to protect. To ensure information privacy (as opposed to data privacy), sensors perform linear precoding on their data. We develop an algorithm to optimize the precoder matrices in order to ensure that the empirical risk of detecting the private hypothesis is above a given threshold, while minimizing the empirical regularized risk of detecting the public hypothesis. Simulation results with both synthetic and real data sets demonstrate that our approach is able to ensure information privacy. © 2016 ieee.

关键词： sensor networks

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Practical sub-Nyquist sampling via array-based compressed sensing receiver architecture

Practical sub-Nyquist sampling via array-based compressed se...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Bolstad, Andrew K. Vian, James E. Chisum, Jonathan D. Suh, Youngho MIT Lincoln Laboratory LexingtonMA02420-9108 United States Department of Electrical Engineering University of Notre Dame South BendIN46556 United States

ISBN: (纸本)9781509021031

This paper introduces the array-based Compressed sensing Receiver Architecture (ACRA). ACRA allows digital receiver arrays to operate at dramatically larger instantaneous bandwidths by sampling the signals from different array elements at different sub-Nyquist sampling rates. signal processing inspired by the sparse fast Fourier transform allows for signal detection, estimation, and angle-of-arrival determination. Simulation results and measurements from an 18-45 GHz testbed are presented. © 2016 ieee.

关键词： Compressed sensing

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array of sensors: A spatiotemporal-state-space model for target trajectory tracking

Array of sensors: A spatiotemporal-state-space model for tar...

引用

2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Manikas, A. Sridhar, V. Kamil, Y.I.

ISBN: (纸本)9781509021031

In this paper, with the objective of tracking the trajectory of multiple mobile targets, a novel spatiotemporal-state-space model is introduced for an array of sensors distributed in space. Under the wideband assumption, the proposed model incorporates the array geometry in conjunction with crucial target parameters namely (i) ranges, (ii) directions, (iii) velocities and (iv) associated Doppler effects. Computer simulation studies show some representative examples where the proposed model is utilised to track the locations of sources in space with a very high accuracy. © 2016 ieee.

关键词： Wave propagation

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Nonlinear mobile sensor calibration using informed semi-nonnegative matrix factorization with a Vandermonde factor

Nonlinear mobile sensor calibration using informed semi-nonn...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Dorffer, Clement Puigt, Matthieu Delmaire, Gilles Roussel, Gilles Univ. Littoral Cote d'Opale EA 4491 LISIC CalaisF-62228 France

ISBN: (纸本)9781509021031

In this paper we aim to blindly calibrate a mobile sensor network whose sensor outputs and the sensed phenomenon are linked by a polynomial relationship. The proposed approach is based on a novel informed semi-nonnegative matrix factorization with a Vandermonde factor matrix. The proposed approach outperforms a matrix-completion-based method in a crowdsensing-like simulation of particulate matter sensing. © 2016 ieee.

关键词： Matrix factorization

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Incremental multiple error filtered-X LMS for node-specific active noise control over wireless acoustic sensor networks

Incremental multiple error filtered-X LMS for node-specific ...

引用

2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Plata-Chaves, Jorge Bertrand, Alexander Moonen, Marc KU Leuven Electrical Engineering Dept. ESAT-STADIUS Kasteelpark Arenberg 10 Leuven3001 Belgium

ISBN: (纸本)9781509021031

We propose an adaptive distributed algorithm to solve a node-specific Active Noise Control (ANC) problem. In this novel ANC problem, the nodes estimate different but overlapping ANC filters in order to generate secondary signals that cancel a primary noise source as it impinges on their microphones. Different sets of nodes follow a cyclic mode of cooperation in order to implement several coupled Multiple Error Filtered-X Least Mean Squares algorithms, each responsible for the estimation of part of the different node-specific ANC filters. The proposed algorithm outperforms the non-cooperative strategies and achieves the same steady-state noise reduction as a centralized solution that processes all the signals in the network. Finally, computer simulations are provided to illustrate the effectiveness of the proposed algorithm. © 2016 ieee.

关键词： Active noise control

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Synthetic aperture imaging with thinned linear sensor arrays for medical ultrasound

Synthetic aperture imaging with thinned linear sensor arrays...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Ramirez, Juan Bottenus, Nick Trahey, Gregg Krolik, Jeffrey L. Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Department of Biomedical Engineering Duke University DurhamNC27708 United States

ISBN: (纸本)9781509021031

In this paper, we exploit motion for improving the ultrasound (US) imaging performance of thinned sensor array systems. Thinned arrays provide reduced system cost and allows for the reduction of bulky channel cables. However, thinned array systems suffer from poor array processing performance from the lack of channels available to the system when compared to a Uniform Linear array (ULA). To overcome these deficiencies we propose to use motion to augment the transmit/receive events such that a general thinned array can be made to perform statistically equivalently to a ULA. The key feature of this work is that the statistical equivalence does not depend on realizing all missing sensors, instead the equivalence is at the level of the sum co-array. We show simulation results that demonstrate the system equivalence of thinned arrays with about one-third of the active sensors compared to a ULA of equal aperture. © 2016 ieee.

关键词： array processing

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Improving the scan statistic to design sensor detection systems

Improving the scan statistic to design sensor detection syst...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Fonseca, Benedito J. B. Northern Illinois University DeKalbIL United States

ISBN: (纸本)9781509021031

When designing a sensor system to detect a target emitter in a large region of interest, it is desirable to use a fusion rule that avoids fusing strong measurements from sensors close to the emitter with weak measurements from sensors far from the emitter. To satisfy this criterion, the system designer may use a fusion rule based on the scan statistic. While this rule offers improved detection performance over other rules, this paper shows that its performance suffers when the scanning process encounters a varying number of sensors. In order to mitigate this degradation, it is proposed here that the fusion rule be based on a normalized scan statistic. © 2016 ieee.

关键词： Image segmentation

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array interpolation based on multivariate adaptive regression splines

Array interpolation based on multivariate adaptive regressio...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Marinho, Marco A.M. Da Costa, Joao Paulo C.L. Antreich, Felix De Almeida, Andre L.F. Del Galdo, Giovanni De Freitas, Edison Pignaton Vinel, Alexey Brazil Germany Fortaleza Brazil Brazil IDE Halmstad University Halmstad Sweden Institute for Information Technology Ilmenau University of Technology Ilmenau Germany Fraunhofer Institute for Integrated Circuits IIS Erlangen Germany

ISBN: (纸本)9781509021031

Many important signal processing techniques such as Spatial Smoothing, Forward Backward Averaging and Root-MUSIC, rely on antenna arrays with specific and precise structures. arrays with such ideal structures, such as a centro-hermitian structure, are often hard to build in practice. array interpolation is used to enable the usage of these techniques with imperfect (not having a centro-hermitian structure) arrays. Most interpolation methods rely on methods based on least squares (LS) to map the output of a perfect virtual array based on the real array. In this work, the usage of Multivariate Adaptive Regression Splines (MARS) is proposed instead of the traditional LS to interpolate arrays with responses largely different from the ideal. © 2016 ieee.

关键词： Antenna arrays

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Single snapshot DOA estimation in the presence of mutual coupling for arbitrary array structures

Single snapshot DOA estimation in the presence of mutual cou...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Elbir, Ahmet M. Engin Tuncer, T. Dept. of Electrical and Electronics Engineering Middle East Technical University Ankara06800 Turkey

ISBN: (纸本)9781509021031

In this paper, single snapshot direction-of-arrival (DOA) estimation under mutual coupling (MC) is considered with arbitrary array structures. A compressed sensing approach is utilized and a joint-sparse recovery algorithm is proposed. In this respect, both spatial source directions and MC coefficients are embedded into ajoint-sparse vector. A new dictionary matrix is defined using the symmetricity of MC matrix. The proposed approach does not depend on the structure of MC matrix and it is suitable for any type of array geometry. In the simulations, the proposed method is evaluated for a planar array where the antennas are placed randomly in 2-D space. It is shown that the proposed method effectively estimates the source parameters and performs significantly better than the alternative methods. © 2016 ieee.

关键词： Compressed sensing

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