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Blind identification of FIR MIMO channels by decorrelating subchannels

IEEE TRANSACTIONS ON SIGNAL processing 2003年第5期51卷 1143-1155页

作者： Hua, YB An, SJ Xiang, Y Univ Calif Riverside Dept Elect Engn Riverside CA 92521 USA Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3010 Australia

We study blind identification and equalization of finite impulse response (FIR) and multi-input and multi-output (MIMO) channels driven by colored signals. We first show a sufficient condition for an FIR MIMO channel to be identifiable up to a scaling and permutation using the second-order statistics of the channel output. This condition is that the channel matrix is irreducible (but not necessarily column-reduced), and the input signals are mutually uncorrelated and of distinct power spectra. We also show that this condition is necessary in the sense that no single part of the condition can be further weakened without another part being strengthened. While the above condition is a strong result that sets a fundamental limit of blind identification, there does not yet exist a working algorithm under that condition. In the second part of this paper, we show that a method called blind identification via decorrelating subchannels (BIDS) can uniquely identify an FIR MIMO channel if a) the channel matrix is nonsingular (almost everywhere) and column-wise coprime and (b) the input signals are mutually uncorrelated and of sufficiently diverse power spectra. The BIDS method requires a weaker condition on the channel matrix than that required,by most existing methods for the same problem.

关键词： adaptive signal processing blind system identification blind channel deconvolution colored sources decorrelation MIMO channels sensor array processing

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Landmine detection and localization using chemical sensor array processing

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IEEE TRANSACTIONS ON SIGNAL processing 2000年第5期48卷 1295-1305页

作者： Jeremic, A Nehorai, A Univ Illinois Dept Elect Engn & Comp Sci Chicago IL 60607 USA

We develop methods for automatic detection and localization of landmines using chemical sensor arrays and statistical signal processing techniques. The transport of explosive vapors emanating from buried landmines is modeled as a diffusion process in a two-layered system consisting of ground and air. Measurement and statistical models are then obtained from the associated concentration distribution. We derive two detectors (the generalized likelihood ratio (GLR) test and the mean detector) and determine their performance in terms of the probabilities of false alarm and detection. To determine the unknown location of a landmine, we derive a maximum likelihood (ML) estimation algorithm and evaluate its performance by computing the Cramer-Rao bound (CRB). The results are applied to the design of chemical sensor arrays, satisfying criteria specified in terms of detection and estimation performance measures and for optimally selecting the number and positions of sensors and the number of time samples, To illustrate the potential of the proposed techniques in a realistic demining scenario, we derive a moving-sensor algorithm in which the stationary sensor array is replaced by a single moving sensor. Numerical examples are given to demonstrate the applicability of our results.

关键词： landmine detection localization moving sensor sensor array processing

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Polarimetric adaptive detection in non-Gaussian noise

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SIGNAL processing 2003年第2期83卷 297-306页

作者： De Maio, A Alfano, G Univ Naples Federico II Dipartimento Ingn Elett & Telecommun I-80125 Naples Italy

in this paper we address polarimetric adaptive detection of targets embedded in compound-Gaussian clutter with unknown covariance matrix. To this end we assume that a set of secondary data, free of signal components and with the same covariance structure of the cell under test, is available. We resort to a design procedure based upon the generalized likelihood ratio test (GLRT): first we derive the GLRT assuming that the textures are known, then we plug into the derived test suitable estimates of these parameters. Remarkably, the newly proposed detector has the constant false alarm rate (CFAR) property with respect to the texture statistical characterization. Moreover, even though it does not ensure the CFAR property with respect to the clutter covariance matrix, a sensitivity analysis shows that the probability of false alarm is only slightly affected by variations in the clutter correlation properties. Finally, the performance assessment, conducted via Monte Carlo simulations, confirms the capability of the receiver to operate in real radar scenarios. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： sensor array processing polarimetric radar adaptive detection

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A new subspace identification algorithm for high-resolution DOA estimation

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2002年第10期50卷 1382-1390页

作者： McCloud, ML Scharf, LL Magis Networks Inc San Diego CA 92130 USA Colorado State Univ Ft Collins CO 80523 USA

In this paper, we propose a new direction of arrival (DOA) estimator for sensor-array processing. The estimator is based on a linear algebraic connection between the standard subspace model of the array correlation matrix and a special signal-plus-interference model, which we develop in this paper. The estimator we propose is a signal subspace scaled MUSIC algorithm, which we call SSMUSIC. It is not a subspace weighted MUSIC, because the scaling depends on the eigenstructure of the estimated signal subspace. SSMUSIC has the advantage of simultaneously estimating the DOA and the power of each source. We employ a second-order perturbation analysis of the estimator and derive stochastic representations for its bias and squared-error. We compare the new DOA estimator with the MUSIC estimator, based on these representations. Numerical results demonstrate the superior performance of SSMUSIC relative to MUSIC and the validity of the perturbation results.

关键词： bearing response function direction of arrival (DOA) MUSIC sensor array processing subspace processing

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Landmine detection and localization using chemical sensor array processing

Landmine detection and localization using chemical sensor ar...

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Detection and Remediation Technologies for Mines and Minelike Targets IV Conference

作者： Jeremic, A Nehorai, A Univ Illinois Chicago IL 60607 USA

ISBN: (纸本)0819431842

We develop methods for the automatic detection and localization of landmines using chemical sensor arrays and statistical signal processing techniques. The transport of explosive vapors emanating from buried landmines is modeled as a diffusion process in a two layered system consisting of ground and air. The measurement and statistical models are derived by exploiting the associated concentration distribution. We derive a generalized likelihood ratio (GLR) detector and evaluate its performance in terms of the probabilities of detection and false alarm. To determine the unknown location of a landmine we derive a maximum likelihood (ML) estimation algorithm and evaluate its performance by computing the Cramer-Rao bound (CRB). The results are applied to the design of chemical sensor arrays, satisfying criteria specified in terms of detection and estimation performance measures, and to optimally select the number and positions of sensors and the number of time samples. To illustrate the potential of the proposed techniques in a realistic demining scenario, we derive a moving sensor algorithm in which the stationary sensor array is replaced by a single moving sensor. Numerical examples are given to demonstrate the applicability of our results.

关键词： landmine detection localization moving sensor sensor array processing

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Maximum-likelihood direction-of-arrival estimation in the presence of unknown nonuniform noise

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IEEE TRANSACTIONS ON SIGNAL processing 2001年第7期49卷 1310-1324页

作者： Pesavento, M Gershman, AB McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada

We consider the problem of estimating directions of arrival (DOAs) of multiple sources observed on the background of nonuniform white noise with an arbitrary diagonal covariance matrix. A new deterministic maximum likelihood (ML) DOA estimator is derived. Its implementation is based on an iterative procedure which includes a stepwise concentration of the log-likelihood (LL) function with respect to the signal and noise nuisance parameters and requires only a few iterations to converge. New closed-form expressions for the deterministic and stochastic direction estimation Cramer-Rao bounds (CRBs) are derived for the considered nonuniform model. Our expressions can be viewed as an extension of the well-known results by Stoica and Nehorai and Weiss and Friedlander to a more general noise model than the commonly used uniform one. In addition, these expressions extend the recent results by Matveyev et al. to the multiple source case. Comparisons with the above-mentioned earlier results help to discover several interesting properties of DOA estimation in the nonuniform noise case, To compare the estimation performance of the proposed ML, technique with the results of our CRB analysis and with the performance of conventional "uniform" ME, simulation results are presented. Additionally, we test our technique using experimental seismic array data. Our simulations and experimental results both validate essential performance improvements achieved by means of the approach proposed.

关键词： direction-of-arrival estimation maximum likelihood algorithm nonuniform noise sensor array processing

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A polarimetric adaptive matched filter

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SIGNAL processing 2001年第12期81卷 2583-2589页

作者： De Maio, A Ricci, G Univ Naples Federico II Dipartimento Ingn Elett & Telecomunicaz I-80125 Naples Italy

In this paper, we address polarimetric adaptive detection of targets embedded in Gaussian noise with unknown covariance matrix. To this end we assume that a set of secondary data, free of signal components and with the same covariance matrix of the cell under test, is available. We resort to a two-step design procedure based upon the generalized likelihood ratio test (GLRT). It is shown that the newly proposed detector has the constant false alarm rate property with respect to the covariance matrix of the noise. More remarkably, it has the same performance, but a lower complexity, than the corresponding plain GLRT. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： sensor array processing polarimetric radar adaptive detection

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Weighted closed-form estimators for blind source separation

Weighted closed-form estimators for blind source separation

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11th IEEE Workshop on Statistical Signal processing (SSP 2001)

作者： Zarzoso, V Herrmann, F Nandi, AK Univ Liverpool Dept Elect Engn & Elect Signal Proc & Commun Grp Liverpool L69 3GJ Merseyside England

ISBN: (纸本)0780370112

This paper investigates a novel closed-form estimation class, so-called weighted estimator (WE). for blind source separation in the basic two-signal problem. Proper combination of previously proposed estimators yields consistent estimates of the separation parameters under general conditions. In the real-mixture case, we determine analytic expressions for the WE asymptotic (large-sample) variance and the source-dependent weight value of the most efficient estimator in the class. By means of the bicomplex-number formalism. the WE is extended to the complex-mixture scenario, for which Cramer-Rao bounds are also derived. Simulations compare the WE with other methods, demonstrating its potential.

关键词： blind source separation estimation theory higher-order statistics. non-Gaussian signal processing sensor array processing

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Gain decomposition methods for radio telescope arrays

Gain decomposition methods for radio telescope arrays

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11th IEEE Workshop on Statistical Signal processing (SSP 2001)

作者： Boonstra, AJ van der Veen, AJ Netherlands Fdn Res Astron ASTRON NL-7991 PD Dwingeloo Netherlands

ISBN: (纸本)0780370112

In radio telescope arrays, the complex receiver gains and sensor noise powers are initially unknown and have to be calibrated. Gain calibration enhances the quality of astronomical sky images and moreover, improve the effectiveness of certain radio telescope phased-array data processing techniques, such as radio interference (RFI) mitigation and beamforming. In this paper we present several closed form and iterative complex gain estimation methods. These methods are analyzed and compared to the Cramer-Rao lower bound for the variance of the estimated gain. The models are tested both on simulated data and on observed telescope data.

关键词： applications in radio astronomy sensor array processing

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Bayesian array signal processing in additive generalized Gaussian noise

Bayesian array signal processing in additive generalized Gau...

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11th IEEE Workshop on Statistical Signal processing (SSP 2001)

作者： Kannan, B Natl Univ Singapore Ctr Wireless Commun Singapore 11764 Singapore

ISBN: (纸本)0780370112

In this paper, we present a Bayesian approach for DOA and frequency estimation of narrow band signals in additive generalized Gaussian noise. Using Bayesian techniques, the posterior probability densities for DOA (Direction Of Arrival) and frequency parameters are derived from the signal and noise models. These posterior probabilities are then used in the Metropolis-Hastings (M-H) algorithm to derive the samples for the DOA and frequency parameters. The performances of our algorithms are studied by plotting the MSEs (Mean Square Errors) of the parameters for various SNRs. The MSEs of the parameters are compared with the CRLBs (Cramer Rao Lower Bound) for the generalized Gaussian models.

关键词： non-Gaussian signal processing sensor array processing Bayesian estimation M-H algorithm

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