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Sensor Array and Multichannel Signal Processing Workshop (SAM), 2010 IEEE

Date 4-7 Oct. 2010

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Displaying Results 1 - 25 of 71
  • [Copyright notice]

    Publication Year: 2010 , Page(s): 1
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    Freely Available from IEEE
  • Committee

    Publication Year: 2010 , Page(s): 1 - 2
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    Provides a listing of current committee members. View full abstract»

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  • Technical program

    Publication Year: 2010 , Page(s): 1 - 11
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    Freely Available from IEEE
  • Multichannel blind compressed sensing

    Publication Year: 2010 , Page(s): 129 - 132
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (231 KB) |  | HTML iconHTML  

    Compressed sensing successfully recovers a signal, which is sparse under some basis representation, from a small number of linear measurements. However, prior knowledge of the sparsity basis is essential for the recovery process. The purpose of blind compressed sensing is to avoid the need for this prior knowledge. We consider blind compressed sensing in multichannel systems, in which the sparsity basis is unknown in both the sampling and recovery stages. Blind compressed sensing is achieved by simultaneously measuring several signals. We then suggest a simple algorithm to retrieve the unknown input. Under conditions presented in this work we demonstrate that our method can achieve results similar to those of standard compressed sensing, which rely on prior knowledge of the sparsity basis. View full abstract»

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  • A recursive model for partially correlated χ2 targets

    Publication Year: 2010 , Page(s): 229 - 232
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (278 KB) |  | HTML iconHTML  

    This work considers the problem of χ2 target detection in normal (Gaussian) noise. The single pulse power, and target RCS, are χ2 distributed with an arbitrary form factor k. The correlation between pulses is determined by target dynamics, according to a simple rule of thumb. The sequence of target pulses is constructed using a recursive model of Markov chain, and the value of the correlation coefficient is derived. An approximation of 'strict sense χ2' is assumed for the probability density function (p.d.f) of the sum of the integrated pulses. The form factor K of this density is calculated in terms of the correlation coefficient, number of integrated pulses and the form factor for the single pulse p.d.f - k. By determination of the normalized threshold for the given Pfa (probability of false alarm), the probability of detection - Pd can be obtained. One way to do these calculations is using the "universal detection equation" suggested by D.K Barton (7.2005). The model can be used in radar system performance analysis and in simulations. The advantage of these methods is the elimination of the use of tables and graphs, and enabling direct computations such as in multiple situation simulations. It can be done using commercially available advanced mathematical software. View full abstract»

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  • Sampling of pulse streams: Achieving the rate of innovation

    Publication Year: 2010 , Page(s): 133 - 136
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (261 KB) |  | HTML iconHTML  

    We consider the problem of sampling signals which are comprised of pulse streams. This model belongs to the recently introduced framework of signals with finite rate of innovation. The minimal sampling rate for such signals is the number of degrees of freedom per unit of time, referred to as the rate of innovation. Although sampling of pulse streams was treated in various works, either the rate of innovation was not achieved, or the pulse shape was limited to diracs. In this work we propose multichannel schemes for arbitrary pulse streams, operating at the rate of innovation. The proposed approach is based on modulating the input signal in each channel with a properly chosen waveform, followed by an integrator. We show that the pulses delays and amplitudes can be recovered from the samples using standard spectral estimation tools. The resulting scheme is flexible and exhibits better noise robustness than previous approaches. View full abstract»

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  • Convergence analysis of adaptive partial FEXT cancellation precoder for multichannel downstream VDSL

    Publication Year: 2010 , Page(s): 217 - 220
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (93 KB) |  | HTML iconHTML  

    In this paper we present and analyze a computationally-efficient, adaptive precoder for partial FEXT cancellation in downstream VDSL. The precoder is based on error signal feedback. We present conditions on the channel matrix and on the precoder parameter, and prove that if the conditions are satisfied then the precoder converges in expectation to the partial precoder presented by Cendrillon et al. Results are verified by simulations, which also show convergence in mean square error. View full abstract»

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  • The polynomial predictive Gaussian mixture MeMBer filter

    Publication Year: 2010 , Page(s): 233 - 236
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB) |  | HTML iconHTML  

    We propose a novel multi-target tracking algorithm, called the polynomial predictive Gaussian mixture Multi-target Multi-Bernoulli filter (PPGM-MeMBer) filter. We firstly present a unified state space model where the state equation may describe any dynamics of the true targets, no matter linear or nonlinear and no matter we know them well or not, which is more common in practice. Then we apply the Gaussian mixture MeMBer (GM-MeMBer) filter to the unified model. The analysis results show that the proposed PPGM-MeMBer filter can deal with situations when we do not know the targets dynamics well. The multi-target tracking simulation results verify the effectiveness of the proposed method. View full abstract»

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  • A method for differentially coherent detection of OFDM signals on Doppler-distorted channels

    Publication Year: 2010 , Page(s): 85 - 88
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (235 KB) |  | HTML iconHTML  

    Doppler distortion causes inter-carrier interference which prevents the use of differentially coherent detection in OFDM systems. To recover this efficient detection method, we propose to use several FFT demodulators operating in parallel over non-overlapping time segments, and to combine their outputs prior to detection. This technique aims for efficient implementation of front-end matched filtering, followed by differential MMSE combining. A low complexity algorithm is proposed for recursive computation of combiner weights, and its gain over the conventional detector is quantified through numerical examples of an underwater acoustic channel with severe Doppler distortion. View full abstract»

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  • Sparse component analysis for linear mixed models

    Publication Year: 2010 , Page(s): 137 - 140
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (293 KB) |  | HTML iconHTML  

    When seeking for a sparse solution of a linear model, a common technique is the search of a solution with minimum ℓ1 norm. In this paper, we present a new approach for the case of sparse linear mixed models. We combine the EM algorithm for solving the inverse problem with a decision test that guarantees sparseness by eliminating the statistically null components of the solution. We address its performance by means of simulations and illustrate its use with real radar data demonstrating its potential applications. View full abstract»

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  • Robust focusing for wideband MVDR beamforming

    Publication Year: 2010 , Page(s): 1 - 4
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (235 KB) |  | HTML iconHTML  

    In this paper, we propose and study two robust methods for coherent focused wideband Minimum Variance Distortionless Response (MVDR) beamforming. The focusing procedure introduces a frequency dependent focusing error which causes performance degradation, especially at high Signal to Noise Ratio (SNR) values. The proposed robust methods aim at reducing the sensitivity of the coherent MVDR to focusing errors. The first method is based on modifying the beamformer optimization problem and generalizing it to bring into account the focusing transformations and the second is based on modifying the focusing scheme itself. A numerical study demonstrates a significant performance improvement of the proposed robust schemes when applied, using the Wavefield Interpolated Narrowband Generated Subspace (WINGS) focusing transformation. View full abstract»

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  • Estimating the parameters of a moving target in MIMO radar with widely separated antennas

    Publication Year: 2010 , Page(s): 57 - 60
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (122 KB) |  | HTML iconHTML  

    In this paper, we develop a new maximum likelihood (ML) moving target parameter estimation technique for multiple-input multiple-output (MIMO) radar. It is required for this technique that different receive antennas have the same time reference, but no synchronization of initial phases of the receive antennas is needed and, therefore, the estimation process is noncoherent. The target motion within a certain processing interval is modeled as a second-order polynomial whose coefficients are given by the initial location, velocity, and acceleration of the target. The proposed ML estimator is able to jointly process the data collected from multiple consecutive radar pulses. It is shown that the considered ML problem simplifies to the classic “overdetermined” nonlinear least-squares problem. The proposed ML estimator requires multi-dimensional search over the unknown location, velocity, and acceleration parameters. The performance of the proposed estimator is validated by simulation results. View full abstract»

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  • Expected likelihood support for deterministic maximum likelihood DOA estimation

    Publication Year: 2010 , Page(s): 237 - 240
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (228 KB) |  | HTML iconHTML  

    In this paper, the “expected likelihood” approach, previously introduced for the stochastic (unconditional) Gaussian case, is extended over the so-called deterministic (conditional) Gaussian case. Direction of arrival (DOA) estimation when arbitrary temporally correlated waveforms transmitted by point sources of interest impinge onto a uniformly spaced linear array is examined. Specifically, we introduce a normalized likelihood ratio that for the true DOAs have p.d.fs that (for practical purposes) have weak enough dependence on these DOAs to be used in the expected likelihood approach. The utility of this approach is demonstrated by examples on DOA estimation in the so-called “threshold” region. View full abstract»

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  • Covariance-informed detection in compound-Gaussian clutter without secondary data

    Publication Year: 2010 , Page(s): 241 - 244
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (231 KB) |  | HTML iconHTML  

    We consider the problem of detecting a signal of interest in the presence of compound-Gaussian clutter, without resorting to secondary data in order to infer the clutter covariance matrix. Towards this end, we assume that both the texture τ and the speckle covariance matrix R are random variables with some a priori distributions. Marginalizing with respect to these variables, the probability density function of the observed primary data is derived, leading to a closed-form expression for the generalized likelihood ratio test (GLRT) of the problem at hand. Accordingly, the GLRT assuming that τ is deterministic is also derived. The two detectors are assessed through numerical simulations. View full abstract»

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  • Estimating the performance of a superdirective microphone array with a frequency-invariant response

    Publication Year: 2010 , Page(s): 5 - 8
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (377 KB) |  | HTML iconHTML  

    The knowledge of the impact of sensors tolerances in the beamformer performance is of crucial importance in many design cases, especially when superdirective arrays are employed. The availability of the array characteristics (i.e. perturbations on sensors responses and elements displacement), allows to obtain an expectation of the system capabilities corrupted by realistic imperfections. In this paper we discuss the effectiveness of the expected beam pattern as an a priori criterion for the beamformer performance estimation. In particular, the expected beam power pattern has been compared to the actual one, resulted from an experimental investigation of a superdirective microphone array. The tight adherence between the two beam shapes accounts for the effectiveness of the proposed tool in driving the system design. View full abstract»

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  • Band-diagonal regularization of Gaussian interference covariance matrices ML estimates

    Publication Year: 2010 , Page(s): 141 - 144
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (341 KB) |  | HTML iconHTML  

    The convergence rate of a number of adaptive processing algorithms for coherent signal extraction from Gaussian interference is compared. Our main attention is paid to a relatively new hybrid method of regularization of the maximum-likelihood estimate (MLE) of the covariance matrix (CM) of Gaussian vectors with discrete and continuous power spectra. Relatively high convergence rate and efficient lattice-filter-based implementation for the introduced technique are demonstrated. View full abstract»

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  • A low complexity STAP for reverberation cancellation in active sonar detection

    Publication Year: 2010 , Page(s): 245 - 248
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (370 KB) |  | HTML iconHTML  

    One of the major problems for active sonar detector is the presence of reverberation. Since the reverberation has both spatially and temporally varying characteristics, a Space Time Adaptive Processing (STAP) technique is used to adapt the processing according to the varying environment. The contribution of this paper is a low complexity STAP scheme for reverberation cancellation in active sonar detection, making use of polyphase filter architecture based sampling rate conversion. View full abstract»

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  • Independent component analysis of quaternion Gaussian vectors

    Publication Year: 2010 , Page(s): 145 - 148
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (449 KB) |  | HTML iconHTML  

    This paper addresses the independent component analysis (ICA) of quaternion Gaussian vectors. Firstly, we define the properness profile of a quaternion random variable, which can be seen as the quaternion analogue of the circularity coefficients of complex vectors. The properness profile is a three-dimensional pure quaternion vector, which does not only measure the improperness degree of the quaternion random variable, but also provides the improperness distribution. Secondly, we prove that the quaternion ICA model can be identified up to the trivial scale and permutation ambiguities, and a residual quaternion mixture among the sources with rotationally equivalent properness profiles, i.e., properness profiles related by a quaternion rotation. Finally, the main results of the paper are illustrated by means of some numerical examples. View full abstract»

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  • Combining multiband joint position-pitch algorithm and particle filters for speaker localization

    Publication Year: 2010 , Page(s): 149 - 152
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (588 KB) |  | HTML iconHTML  

    We present a combination of the multiband joint position-pitch (M-PoPi) estimation algorithm with the particle filtering framework to enhance the localization accuracy when tracking multiple concurrent speakers. A new likelihood function derived from the M-PoPi algorithm is proposed for the particle filter framework. The performance of the particle filter based tracker is compared with the M-PoPi algorithm. The proposed framework improves localization accuracy for all cases ranging from single up to three concurrent speakers. View full abstract»

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  • Multiantenna spectrum sensing: The case of wideband rank-one primary signals

    Publication Year: 2010 , Page(s): 9 - 12
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (245 KB) |  | HTML iconHTML  

    One of the key problems in cognitive radio (CR) is the detection of primary activity in order to determine which parts of the spectrum are available for opportunistic access. In this work, we present a new multiantenna detector which fully exploits the spatial and temporal structure of the signals. In particular, we derive the generalized likelihood ratio test (GLRT) for the problem of detecting a wideband rank-one signal under spatially uncorrelated noise with equal or different power spectral densities. In order to simplify the maximum likelihood (ML) estimation of the unknown parameters, we use the asymptotic likelihood in the frequency domain. Interestingly, for noises with different distributions and under a low SNR approximation, the GLRT is obtained as a function of the largest eigenvalue of the spectral coherence matrix. Finally, the performance of the proposed detectors is evaluated by means of numerical simulations, showing important advantages over previously proposed approaches. View full abstract»

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  • Blind extraction algorithm with direct desired signal selection

    Publication Year: 2010 , Page(s): 13 - 16
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (224 KB) |  | HTML iconHTML  

    In many practical applications we are interested in the extraction of only one desired signal out of a mixture of signals. A disadvantage of most blind extraction approaches proposed in the literature is that they are inefficient in the sense that they also separate or extract undesired signals. To deal with this inefficiency we exploit an a priori guess of direction of arrival related parameters of the desired signal, which serves as a mold. Based on this mold we create linear combinations of noise-free correlation matrices that are used to construct a single matrix with a specific eigenstructure. The eigenvector that corresponds to the smallest eigenvalue of this matrix is the desired extraction filter. Finally it is shown that this approach paves the way to make the algorithm flexible in the utilization of additional a priori information. View full abstract»

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  • A Migrating Target Indicator for wideband radar

    Publication Year: 2010 , Page(s): 249 - 252
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (287 KB) |  | HTML iconHTML  

    The standard way to suppress clutter in narrowband radar is to use Moving Target Indicator (MTI) cancellation techniques. High Range Resolution (HRR) radars are becoming more and more important because they can detect and track targets more accurately. As for such radars the bandwidth is increased, the resolution is decreased and leads to target range migration over the coherent pulse interval (CPI). Due to this range walk, standard low resolution MTI processing is not adapted anymore to HRR MTI radar data. We propose here to extend the principle of the MTI processing to the wideband case. We refer to this method as the Migrating Target Indicator (MiTI), since it eliminates the non-migrating targets from the received signals. View full abstract»

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  • Likelihood-Ratio and channel based access for energy-efficient detection in wireless sensornetworks

    Publication Year: 2010 , Page(s): 17 - 20
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (233 KB) |  | HTML iconHTML  

    We examine transmission scheduling by medium access control (MAC) for energy-efficient detection using Wireless Sensor Networks (WSN). We focus on the binary hypothesis testing problem. The decision is made by an access point and based on received data from sensors that transmit through a fading channel. We study the significance of exploiting both Channel-State Information (CSI) and Likelihood-Ratio Information (LRI) to design adequate MAC protocol that minimizes the total transmission energy required for the detection problem. By formulating the problem as a Stochastic Shortest Path (SSP) problem we design the LRI and CSI Based Access (LCBA) protocol. LCBA trades off between LRI and CSI to minimize the total transmission energy. It allows sensors to access the channel according to the optimal policy which solves the formulated SSP problem. View full abstract»

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  • Subspace-based direction-of-arrival estimation for more sources than sensors using planar arrays

    Publication Year: 2010 , Page(s): 21 - 24
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (389 KB) |  | HTML iconHTML  

    We propose a novel subspace-based direction-of-arrival (DOA) estimation method and an associated planar array geometry optimization technique. The proposed DOA estimation approach allows to estimate the DOAs of more sources than sensors and to resolve manifold ambiguities in the case of uncorrelated signals. It is related to the covariance augmentation (CA) technique, but in contrast to the CA technique, it can be applied to non-uniform planar array geometries. View full abstract»

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  • Target tracking in mixed LOS/NLOS environments based on individual TOA measurement detection

    Publication Year: 2010 , Page(s): 153 - 156
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (277 KB) |  | HTML iconHTML  

    Non-line-of-sight (NLOS) signal propagation is one of the most important factors affecting the accuracy of localization or tracking especially in urban or indoor environments. This paper presents a method of alleviating the influence of the NLOS signal propagation using a novel individual measurement detection (IMD) approach based on the prior probability density function (pdf) of a moving target's state. The IMD approach can effectively identify line-of-sight (LOS) time-of-arrival (TOA) measurements from all mixed LOS/NLOS measurements. The extended Kalman Filter (EKF) algorithms is adopted to estimate the positions of the moving target using all selected LOS measurements. Simulation results show that the proposed approach outperforms the recent EKF semi-parametric modified residuals (SPMR) approach both in tracking and in computational efficiency. View full abstract»

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