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Source Number Estimation for Iterative Coarray Beamforming with Partially Augmentable arrays

Source Number Estimation for Iterative Coarray Beamforming w...

引用

sensor array and multichannel signal processing workshop

作者： Fauzia Ahmad Jannatul Ferdous Department of Electrical and Computer Engineering Temple University Philadelphia PA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

In this paper, we present an iterative coarray domain beamforming algorithm with source number estimation for direction finding using partially augmentable sparse arrays, whose coarrays are non-uniform. Specifically, we employ a variant of the fast iterative interpolated beamforming (FIIB) that estimates the contributions of the missing coarray elements to emulate a uniform coarray. We exploit the deterministic nature of the noise in the coarray domain, together with its presence only at the central coarray element, to efficiently incorporate source number estimation in the FIIB algorithm. Using simulated data with a co-prime array, we demonstrate that the proposed algorithm is able to provide accurate estimates of the number of sources with high probability.

关键词： Measurement Direction-of-arrival estimation Accuracy array signal processing Conferences Noise Estimation

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Atomic Norm Denoising for Multi-Frequency-Snapshot Doa Estimation

Atomic Norm Denoising for Multi-Frequency-Snapshot Doa Estim...

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sensor array and multichannel signal processing workshop

作者： Yongsung Park Peter Gerstoft Yifan Wu Michael B. Wakin NoiseLab University of California San Diego La Jolla CA USA Colorado School of Mines Golden CO USA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Motivated by atomic norms in gridless sparse signal recovery’ we introduce a gridless direction-of-arrival (DOA) estimator capable of handling scenarios with multiple frequencies and multiple snapshots. Within the atomic norm frame-work, we consider a multi-frequency model analogous to a multi-snapshot model. Subsequently, we extend the model to accommodate both multi-snapshot and multi-frequency data. The proposed method is illustrated through numerical simulations and validated using ocean acoustic experimental data.

关键词： Time-frequency analysis Direction-of-arrival estimation array signal processing Estimation signal processing algorithms Frequency estimation Data models

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Multi-sensor integration and mapping strategies for the detection and remediation of the red mud spill in Kolontar, Hungary: Estimating the thickness of the spill layer using hyperspectral imaging and Lidar

Multi-sensor integration and mapping strategies for the dete...

引用

3rd workshop on Hyperspectral Image and signal processing: Evolution in Remote Sensing, WHISPERS 2011

作者： Lenart, Csaba Burai, Peter Smailbegovic, Amer Biro, Tibor Katona, Zsolt Andricevic, Roko Karoly Robert College Hungary Photon D.o.o. Split Croatia Envirosense Hungary Ltd. Hungary Faculty of Civil Engineering and Architecture University of Split Croatia

The village of Kolontr, Hungary had became the site of one of the largest industrial spills in Europe on October 4th, 2010. The primary objective of the hyperspectral remote sensing mission was monitoring needed to estimate environmental damage, the precise size of the polluted area, the rating of substance concentration in the mud, and the overall condition of the flooded district. The secondary objective was aimed to provide geodetic data necessary for the high-resolution visual information from the data obtained with an additional Lidar survey, and for coherent modelling of the event. For quick assessment and remediation purposes, it was deemed important to estimate the thickness of the red mud, particularly the areas where the depths of the layer were more than 3cm. The results showed that some of the existing tools can be readily modified and implemented to get the most out of the available advanced remotely sensed data. © 2011 ieee.

关键词： Optical radar

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Vectored VDSL from a practical perspective: ISmart FEXT cancellation performance

Vectored VDSL from a practical perspective: ISmart FEXT canc...

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sensor array and multichannel signal processing workshop

作者： Ronen Yizhaq Gilad Elad Domanovitz Amit Priebatch Ilan Sharfer Avi Matza Eitan Tsur Product Innovation Actelis Networks Limited Petach Tikva Israel Access Research and Development Network Solutions Division ECI Telecom Limited Petach Tikva Israel

Far End Crosstalk (FEXT) in a twisted pair cable is the most dominant noise impairment in short loops for VDSL2 systems. Its impact significantly reduces the VDSL2 modems performance and in some cases might reduce the modem throughput by more than 50%. Canceling the FEXT impact using Dynamic Spectral Management Level 3 (DSM L3, aka Vectoring aka FEXT Cancellation) is an emerging technology for high rates data traffic over copper (Up to 100Mbit/sec). We have developed an eight VDSL2 modems prototype with DSM L3 capabilities. In this article we introduce an overview of our system design and a variety of tests results that reflect the DSM L3 potential.

关键词： Modems Crosstalk DSL Estimation Conferences signal processing Copper

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array processing estimation of non-linearly superimposed acoustic waves

Array processing estimation of non-linearly superimposed aco...

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sensor array and multichannel signal processing workshop

作者： G. Pinero L. Vergara Department of Comunicaciones Universidad Politécnica de Valencia Valencia Spain

Acoustic pressure waves are non-linearly superimposed when a periodic gas flow is perturbing the propagating medium, as it arises in car exhaust systems. In such an environment, the application of standard beamforming techniques to the estimation of the forward and backward waves needs a previous reformulation to establish a linear superposition model. In this paper a new linearization method for the superposition of waves is proposed and compared to the classical assumption of linear pressure superposition. Moreover, a new problem formulation including the noise corruption of source waves is presented. In both new and classical linear contexts, three different beamformers-delay-and-sum (DS), linearly constrained minimum variance (LCMV) and minimum mean squared error (MMSE)-have been applied to numerical data generated by a thermodynamics modeling software. Results have shown that the new linearization method improves the backward wave estimation error in almost 3 dB for typical experiment conditions (few sensors and moderate signal-to-noise ratio).

关键词： array signal processing Nonlinear acoustics Acoustic waves Fluid flow Acoustic propagation Exhaust systems Thermodynamics Context modeling Estimation error signal to noise ratio

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Link Between the Joint Diagonalisation of Symmetrical Cubes and PARAFAC: An Application to Secondary Surveillance Radar

Link Between the Joint Diagonalisation of Symmetrical Cubes ...

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sensor array and multichannel signal processing workshop

作者： N. Petrochilos P. Comon CReSTIC University of Reims Reims France Algorithmes I3S-CNRS University of Nice Sophia-Antipolis France

The Manchester decoding algorithm (MDA) presented in N. Petrochilos and A.J. van der Veen (2004) succeeds in separating secondary surveillance radar (SSR) replies impinging on an array. The final step of the MDA consist of jointly diagonalizing a collection of several symmetric cubes by a sub-optimal technique. In this article, we demonstrate that it is in fact a PARAFAC problem with an almost symmetric solution. Furthermore, comparisons with other algorithms are carried out, with the help of computer simulations

关键词： Surveillance Radar applications Null space Receiving antennas Decoding Air traffic control Vectors Aircraft Eigenvalues and eigenfunctions Tensile stress

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signal processing by particle filtering for binary sensor networks

Signal processing by particle filtering for binary sensor ne...

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ieee Digital signal processing workshop

作者： P.M. Djuric M. Vemula M.F. Bugallo Department of Electrical and Computer Engineering Stony Brook University Stony Brook NY USA

In a wireless sensor network, limited power, communication, and computational resources are the major constraints that have to be overcome for their successful deployment and utilization. Binary sensor networks are a class of networks that get around these constraints. There, the sensors transmit only a binary digit on the occurrence of the event of interest, and therefore, the signals that reach the fusion center of these networks are highly compressed and pose challenging problems for recovering the sensed information. We consider the problem of tracking a vehicle, which moves along a 2-dimensional space, by using a binary sensor network that fuses information by particle filtering.

关键词： signal processing Intelligent sensors Target tracking sensor fusion Wireless sensor networks Computer networks Fuses Information filtering Information filters sensor phenomena and characterization

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An optimal step size relative gradient based joint diagonalization algorithm

An optimal step size relative gradient based joint diagonali...

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ieee International workshop on Computational Advances in Multi-sensor Adaptive processing (CAMSAP)

作者： Hicham Ghennioui Nadège Thirion-moreau Eric Moreau Laboratoire LSEET UMR CNRS 6017 Institut des Sciences de l Ingènieur de Toulon et du Var ISITV La Valette-du-Var France

ISBN: (纸本)9781424451791;9781424451807

This paper addresses the problem of the non unitary joint diagonalization of a given set of complex matrices. We focus on gradient based algorithms. A new algorithm based on a relative gradient approach is suggested. Its algorithmic complexity is established and the optimal stepsize is calculated algebraically at each iteration to decrease the number of iterations required to reach the convergence while discarding the often difficult stepsize choice problem. Computer simulations are provided to illustrate the behavior of this algorithm in different contexts. It is also compared with other existing joint diagonalization algorithms.

关键词： signal processing algorithms Matrix decomposition Least squares approximation Tensile stress Reactive power Convergence Computer simulation array signal processing Blind source separation Independent component analysis

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Blind Phase-Offset Estimation in Sparse Partly Calibrated arrays

Blind Phase-Offset Estimation in Sparse Partly Calibrated Ar...

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sensor array and multichannel signal processing workshop

作者： Tianyi Liu Marius Pesavento Communication Systems Group Technische Universitat Darmstadt Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Spatial frequency estimation from a superposition of impinging waveforms in the presence of noise is important in many applications. While subspace-based methods offer high-resolution parameter estimation at a low computational cost, they heavily rely on precise array calibration with a synchronized clock, posing challenges for large distributed antenna arrays. In this study, we focus on direction-of-arrival (DoA) estimation within sparse partly calibrated rectangular arrays. These arrays consist of multiple perfectly calibrated sub arrays with unknown phase-offsets among them. We present a gridless sparse formulation for DoA estimation leveraging the multiple shift-invariance properties in the partly calibrated array. Additionally, an efficient blind calibration technique is proposed based on semidefinite relaxation to estimate the intersubarray phase-offsets accurately.

关键词： Phased arrays Direction-of-arrival estimation array signal processing Conferences Noise Estimation Frequency estimation

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Linear Convergence of Iteratively Reweighted Least Squares for Nuclear Norm Minimization

Linear Convergence of Iteratively Reweighted Least Squares f...

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sensor array and multichannel signal processing workshop

作者： Christian Kümmerle Dominik Stöger Department of Computer Science University of North Carolina at Charlotte Charlotte NC USA Department of Mathematics KU Eichstätt-Ingolstadt Ingolstadt Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Low-rank matrix recovery problems are ubiquitous in many areas of science and engineering. One approach to solve these problems is Nuclear Norm Minimization, which is itself computationally challenging to solve. Iteratively Reweighted Least Squares (IRLS) uses a sequence of suitable (re-)weighted least squares problems to minimize the nuclear norm. However, while global convergence guarantees have been established for IRLS in this context, no convergence rates have been known so far. In this paper, we show that an IRLS variant named MatrixIRLS converges to the ground truth solution with a linear rate. Numerical simulations corroborate our theoretical findings.

关键词： array signal processing Conferences Minimization Numerical simulation Convergence sensor arrays

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