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Non-Linear Source Separation Under the Langmuir Model for Chemical sensors

Non-Linear Source Separation Under the Langmuir Model for Ch...

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sensor array and multichannel signal processing workshop

作者： Pierre Maho Simon Barthelmé Pierre Comon CNRS Univ. Grenoble Alpes Grenoble France

Electronic nose is a promising bio-inspired instrument for the detection of Volatil Organic Compounds (VOCs), meaning a compound containing carbon which easily evaporates. One of the most important parts of these devices is a set of non-specific chemical sensors, which will interact with the VOC and output valuable information for its identification. the nonspecificity of these chemical sensors ensures the universality of the instrument. the main task achieved by this instrument is the detection of individual VOC. However, in many real-life applications, mixtures of VOCs are observed. the recovery of the mixture composition, meaning the individual signatures and their relative contribution, is a challenging task which can be studied in a Blind Source Separation framework. In this paper, we propose a non-linear mixture model for a particular type of chemical sensors. this model is based on the Langmuir isotherm for a multi-component gas. We study the joint identifiability of signatures and concentrations, and propose a necessary identification condition. Finally, we propose an algorithm for the blind estimation of the parameters and assess its performance through simulations.

关键词： Chemical and biological sensors sensor arrays Chemicals array signal processing signal processing algorithms Mathematical model

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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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Exploiting adaptive beamforming for compressive measurements

Exploiting adaptive beamforming for compressive measurements

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sensor array and multichannel signal processing workshop

作者： M. Sharp M. Pekala J. Nanzer I-J. Wang D. Lucarelli K. Lauritzen Applied Physics Laboratory Johns Hopkins University USA

Beamformers are spatial filters that focus energy in a particular direction while attempting to eliminate interference from other directions. this paper compares several adaptive approaches that seek to provide detection performance equivalent to classical techniques while using fewer beams, a form of measurement compression. Using an apriori distribution on the source locations together with an initial set of beams as a starting point, these algorithms adaptively form a sequence of beams based on posterior distributions of the source locations. Two methods are considered: one attempts to maximize the trace of the Fisher information and the other maximizes mutual information based on a Gaussian posterior approximation.

关键词： array signal processing Bayesian methods Libraries Approximation methods arrays Vectors Optimization

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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...

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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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Quantifying the advantages of joint processing in TDOA estimation

Quantifying the advantages of joint processing in TDOA estim...

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sensor array and multichannel signal processing workshop

作者： Arie Yeredor School of Electrical Engineering Tel Aviv University Tel-Aviv Israel

We address the problem of passive estimation of the Time-Difference of Arrival (TDOA) of an unknown, stochastic signal, at two sensors. the key question addressed here is whether additional sensors, receiving the same signal at various relative delays, can serve to improve the accuracy in estimating the TDOA of interest between the first two sensors (without exploiting any underlying parameterization, such as dependence on the transmitter's location). We derive the Cramér-Rao Lower Bound (CRLB) on the resulting joint estimation error in a model which possibly includes multipath reflections. We show analytically, that in a multipath-free scenario, at high to moderate signal to Noise Ratios, additional sensors do not offer any improvement in accuracy. However, we also demonstrate (numerically) that in the presence of multipath reflections (possibly received at all sensors), the additional sensors can indeed assist in estimating the TDOA of interest with improved accuracy.

关键词： Delay signal to noise ratio Accuracy Vectors Estimation error

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Ambiguities in direction-of-arrival estimation for nonuniform linear antenna arrays

Ambiguities in direction-of-arrival estimation for nonunifor...

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Proceedings of the 1996 4th International Symposium on signal processing and its Applications, ISSPA'96. Part 2 (of 2)

作者： Abramovich, Yuri I. Gray, Douglas A. Spencer, Nicholas K. Gorokhov, Alexei Y. Cooperative Research Cent for Sensor Signal and Information Processing Levels

this paper deals with ambiguities in DOA estimation for fully- and partially-augmentable arrays. Until now, ambiguities have been defined via the condition that the antenna manifold repeats itself (`trivial' ambiguity), or that a point on the array manifold can be written as a linear combination of some other points. We demonstrate that both fully- and partially-augmentable arrays always admit these type of ambiguities. though the standard MUSIC algorithm fails to resolve the ambiguity, the above conditions do not necessarily lead to inherent DOA estimation ambiguity. We show that inherent ambiguity for the non-uniform linear array is defined by rank-deficiency of the associated Fisher matrix, and that fully-augmentable arrays are always unambiguous in this sense. Examples of inherent non-identifiability for partially-augmentable arrays are given.

关键词： signal filtering and prediction

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A real time tracker of complex circularity

A real time tracker of complex circularity

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sensor array and multichannel signal processing workshop

作者： Sithan Kanna Scott C. Douglas Danilo P. Mandic Department of EEE Imperial College London London U.K. Department of EE Southern Methodist University TX U.S.A.

A new insight into the relationship between the complex circularity quotient and the coefficient of a linear minimum mean square estimator (LMMSE) which estimates a complex random variable from its complex conjugate is established. An adaptive version of this estimator, suitable for real time tracking of the degree of complex circularity is proposed based on the complex least mean square (CLMS) algorithm. For Gaussian data, the mean and mean square analyses show the effect of data non-circularity on the stability bounds of the real time circularity tracker. the concept is verified over simulations on both synthetic single- and multi-channel data and on real world wind signals with varying degrees of circularity.

关键词： signal processing algorithms Real-time systems Random variables Stability analysis signal processing Conferences Wind speed

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ON thE ESTIMATION OF thE COVARIANCE EIGENSPECTRUM OF array SAMPLE OBSERVATIONS

ON THE ESTIMATION OF THE COVARIANCE EIGENSPECTRUM OF ARRAY S...

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2008 ieee sensor array and multichannel signal processing workshop

作者： Francisco Rubio Xavier Mestre Parc Mediterrani de la Tecnologia Centre Tecnològic de Telecomunicacions de Catalunya Castelldefels Spain

In this paper, we propose an estimator of the eigenspectrum of the array observation covariance matrix that builds upon the well-known power method and is consistent for an arbitrarily large array dimension. Traditional estimators based on the eigendecomposition of the sample covariance matrix are known to be consistent provided that the number of observations grow to infinity with respect to any other dimension in the signal model. On the contrary, in order to avoid the loss in the estimation accuracy associated with practical finite sample-size situations, a generalization of the conventional implementation is derived that proves to be a very good approximation for a sample-size and an array dimension that are comparatively large. the proposed solution is applied to the construction of a subspace-based extension of the Capon source power estimator. For our purposes, we resort to the theory of the spectral analysis of large dimensional random matrices, or random matrix theory. As it is shown via numerical simulations, the new estimator turns out to allow for a significantly improved estimation accuracy in practical finite sample-support scenarios.

关键词： Covariance matrix Eigenvalues and eigenfunctions arrays Estimation Noise Approximation methods Convergence

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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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MAP-PF 3D position tracking using multiple sensor array

MAP-PF 3D position tracking using multiple sensor array

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sensor array and multichannel signal processing workshop

作者： Kristine L. Bell Richard Pitre Department of Statistics George Mason University Fairfax VA USA RobTre Research Limited Liability Company Clarksville MD USA

the maximum a posteriori penalty function (MAP-PF) approach is applied to three-dimensional (3D) target position tracking of multiple wideband sources using multiple distributed sensor arrays. the track estimation problem is formulated directly from the array data using the maximum a posteriori (MAP) estimation criterion. the penalty function (PF) method of nonlinear programming is used to obtain a tractable solution. A sequential update procedure is developed in which penalized maximum likelihood estimates of target directions-of-arrival (DOAs) and spectra are computed at each array and then used as synthetic measurements in a set of extended Kalman filters. the two steps are coupled via the penalty function. the current target states are used to guide the DOA/spectrum estimation, and the estimated signal spectra control the influence of the DOA estimates from each array on the final track estimates. the algorithm can be implemented in a decentralized manner where DOA/spectrum estimation is performed at the arrays, and track estimation is performed at a central processing site.

关键词： Target tracking Direction of arrival estimation arrays Estimation Spectral analysis Maximum likelihood estimation sensor arrays

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