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The performance of sparse time-reversal mirrors in the context of underwater communications

The performance of sparse time-reversal mirrors in the conte...

引用

ieee workshop on Statistical signal and array processing

作者： J. Gomes V. Barroso Instituto Superior Tecnico-Instituto de Sistemas e Robótica Lisboa Portugal

Recently, wave focusing using a uniform time-reversal array has been demonstrated in the ocean with very encouraging results. This technique may be used to regenerate a mildly distorted signal at the input of a digital underwater acoustic receiver, hence reducing its equalization requirements at the expense of additional complexity at the transmitter. This work investigates the performance improvements that become possible when sparse and non-uniform arrays are used. Results from the theory of randomly-spaced arrays are extended to a simplified ocean waveguide, revealing that familiar relations between the sensor placement density function and the directional characteristics of the generated acoustic field are still valid in the large-scale. Simulation results confirm the validity of these derivations.

关键词： Mirrors sensor arrays Oceans Acoustic distortion Underwater acoustics Transmitters Acoustic arrays Acoustic waveguides Waveguide theory sensor phenomena and characterization

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Joint time-frequency analysis of SAR data

Joint time-frequency analysis of SAR data

引用

ieee workshop on Statistical signal and array processing

作者： R. Fiedler R. Jansen Naval Research Laboratory Inc. Washington D.C. DC USA

The image formation process associated with coherent imaging sensors is particularly sensitive to and is often corrupted by non-stationary processes. In the case of synthetic aperture radar (SAR), non-stationary processes result from motion within the scene, variable radar cross section, multipath, topographic variations, sensor anomalies, and deficiencies in the image formation processing chain. This paper addresses SAR image formation processing, the complex response function for a point source, and SAR JTF image formation implementations. Each of these topics is described within the context of applying JTF processing to all aspects of SAR image formation and analysis.

关键词： Time frequency analysis Image sensors Synthetic aperture radar Layout Radar imaging Reflectivity signal processing Image analysis sensor phenomena and characterization Fourier transforms

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Distributed source localization with multiple sensor arrays and frequency-selective spatial coherence

Distributed source localization with multiple sensor arrays ...

引用

ieee workshop on Statistical signal and array processing

作者： R.J. Kozick B.M. Sadler Bucknell University Lewisburg PA USA Army Research Laboratory Adelphi MD USA

Multiple sensor arrays distributed over a planar region provide the means for highly accurate localization of the (x,y) position of a source. In some applications, such as microphone arrays receiving aeroacoustic signals from ground vehicles, random fluctuations in the air lead to frequency-selective coherence of the signals that arrive at widely separated arrays. We present a performance analysis for localization of a wideband source using multiple sensor arrays. The wavefronts are modeled with perfect spatial coherence over individual arrays and with frequency-selective coherence between distinct arrays. The sensor signals are modeled as wideband Gaussian random processes, and we study the Cramer-Rao bound (CRB) on source localization accuracy for varying levels of signal coherence and for processing schemes with different levels of complexity. We show that significant improvements in source localization accuracy are possible when partial signal coherence from array to array is exploited. Further, we show that a distributed processing scheme involving bearing estimation at the individual arrays and time-delay estimation between pairs of sensors performs nearly as well as the optimum scheme that jointly processes the signals from all sensors. Results based on measured aeroacoustic data are included to illustrate frequency-selective signal coherence at distributed arrays.

关键词： sensor arrays Microphone arrays Frequency signal processing Wideband Land vehicles Fluctuations Performance analysis Spatial coherence Random processes

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A bootstrap technique for rank estimation

A bootstrap technique for rank estimation

引用

ieee workshop on Statistical signal and array processing

作者： P. Pelin R. Brcich A. Zoubir Australian Telecommunications Research Institute (ATRJ) Curtin University of Technology Perth WA Australia

A crucial step in many signal processing applications is the determination of the effective rank of a noise corrupted multi-dimensional signal, i.e. the dimension of the signal subspace. Standard techniques for rank estimation, such as the minimum description length, often have shortcomings in practice, an example being when noise parameters are unknown. An alternative scheme is proposed for rank detection. From successive pairs of the ordered eigenvalues of the array covariance, a series of statistics is formed. The statistics are chosen such that their distributions for noise eigenvalue pairs are close. The actual distributions are unknown and are estimated with the bootstrap. The rank is then found by a sequential comparison of the estimated distributions using a Kolmogorov-Smirnov test.

关键词： Colored noise Eigenvalues and eigenfunctions signal processing Testing Australia Covariance matrix sensor arrays Statistical distributions signal processing algorithms Probability

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Multiple source direction finding with an array of M sensors using two receivers

Multiple source direction finding with an array of M sensors...

引用

ieee workshop on Statistical signal and array processing

作者： E. Fishler H. Messer Department of Electrical Engineering-Systems Tel-Aviv University Israel

ISBN: (纸本)0780359887

Multiple source direction finding algorithms (e.g., MUSIC) are applied on simultaneous measurements collected by M sensors. However, practical considerations may dictate using less receivers than sensors, such that the measurements cannot be collected simultaneously. In such cases, data is collected sequentially from the different array elements in a process which is referred to as "time varying preprocessing", or "switching". In this paper we study multiple source direction finding (DF) with an array of M>2 elements, where only two receivers are available.

关键词： sensor arrays Maximum likelihood estimation Noise level Covariance matrix Multiple signal classification Time varying systems Costs Narrowband signal representations Additive noise

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Bounds on uncalibrated array signal processing

Bounds on uncalibrated array signal processing

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ieee workshop on Statistical signal and array processing

作者： B.M. Sadler R.J. Kozick Army Research Laboratory Adelphi MD USA Bucknell University Lewisburg PA USA

Deterministic constrained Cramer-Rao bounds (CRBs) are developed for general linear forms in additive white Gaussian noise. The linear form describes a variety of array processing cases, including narrow band sources with a calibrated array, the uncalibrated array cases of instantaneous linear mixing and convolutive mixing, and space-time coding scenarios with multiple transmit and receive antennas. We employ the constrained CRB formulation of Stoica and Ng (ieee Sig. Proc. Letters, vol.5, no.7, pp.177-179, July 1998), allowing the incorporation of side information into the bounds. This provides a framework for a large variety of scenarios, including semi-blind, constant modulus, known moments or cumulants, and others. The CRBs establish bounds on blind estimation of sources using an uncalibrated array, and facilitates comparison of calibrated and uncalibrated arrays when side information is exploited.

关键词： array signal processing sensor arrays Linear antenna arrays Narrowband Phased arrays Laboratories Additive white noise Receiving antennas Additive noise Vectors

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Estimating the parameters of multiple wideband chirp signals in sensor arrays

Estimating the parameters of multiple wideband chirp signals...

引用

ieee workshop on Statistical signal and array processing

作者： A.B. Gershman M. Pesavento M.G. Amin Department of ECE McMaster University Hamilton ONT Canada Department of ECE Villanova University Villanova PA USA

The problem of estimating the parameters of multiple wideband polynomial-phase signal sources in sensor arrays is addressed. A new deterministic maximum likelihood (ML) direction of arrival (DOA) estimator and the respective Cramer-Rao bound (CRB) are presented for the general case of multiple constant-amplitude polynomial-phase sources. Since the proposed ML estimator is computationally intensive, an approximate solution is proposed, originating from the analysis of the ML function in the single chirp case. As a result, the so-called chirp beamformer is derived, which is applicable to "well-separated" sources that have distinct time-frequency or/and spatial signatures. Our beamforming approach requires the solving of a 3D optimization problem and, therefore, enjoys essentially simpler implementation to that dictated by the exact ML.

关键词： sensor arrays Parameter estimation Wideband Chirp Polynomials Maximum likelihood estimation Direction of arrival estimation Time frequency analysis Narrowband Frequency estimation

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array processing in the presence of unknown nonuniform sensor noise: a maximum likelihood direction finding algorithm and Cramer-Rao bounds

Array processing in the presence of unknown nonuniform senso...

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ieee workshop on Statistical signal and array processing

作者： M. Pesavento A.B. Gershman Department of ECE McMaster University Hamilton ONT Canada

We address the problem of estimating directions of arrival (DOAs) of multiple sources observed on the background of nonuniform white noise with an arbitrary unknown diagonal covariance matrix. A new deterministic maximum likelihood (ML) DOA estimator is derived. Its implementation is based on an iterative procedure which includes 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 (1989, 1990), and Weiss and Friedlander (1993, 1995) to a more general noise model than the commonly used uniform one. Simulation and experimental (seismic data processing) results illustrate the performance of the estimator and validate our theoretical analysis.

关键词： array signal processing sensor arrays Direction of arrival estimation Maximum likelihood estimation White noise Covariance matrix Closed-form solution Stochastic resonance Analytical models Data processing

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Comparative study of two-dimensional maximum likelihood and interpolated root-MUSIC with application to teleseismic source localization

Comparative study of two-dimensional maximum likelihood and ...

引用

ieee workshop on Statistical signal and array processing

作者： Pei-Jung Chung A.B. Gershman J.F. Bohme Department of Electrical Engineering and Information Science Ruhr University of Bochum Bochum Germany Department of Electrical and Computer Engineering McMaster University Hamilton ONT Canada

ISBN: (纸本)0780359887

We apply the 2D broadband maximum likelihood (ML) and interpolated root-MUSIC methods to estimate the azimuth and velocity parameters of teleseismic events recorded by the GERESS array. A sequential test based on likelihood ratios (LR) is developed for signal detection. Our experimental results show that both methods can provide reliable estimates of signal parameters. However, ML is shown to have better estimation accuracy and robustness than interpolated root-MUSIC at the expense of a higher computational cost.

关键词： Maximum likelihood estimation Multiple signal classification sensor arrays Application software Azimuth Sequential analysis Computational efficiency signal detection Direction of arrival estimation Information science

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A neural network approach for DOA estimation and tracking

A neural network approach for DOA estimation and tracking

引用

ieee workshop on Statistical signal and array processing

作者： L. Badidi L. Radouane Département de physique L.E.S.S.I. Morocco

ISBN: (纸本)0780359887

Many signal subspace-based approaches have been proposed for determining the fixed direction of arrival (DOA) of plane waves impinging on an array of sensors. However, the computational burden of subspace-based algorithms makes them unsuitable for real-time processing of nonstationary signal parameters. We present an iterative procedure for DOA estimation and tracking, The complete procedure consists of, first, extracting the noise or signal subspace, by training the MCA or PCA algorithms, respectively. These algorithms contain only relatively simple operations and have self-organizing properties. Then, using the Newton algorithm, we get the estimated DOA. The performance on simulated data representing both constant and time-varying signals of the approach is presented.

关键词： Neural networks Direction of arrival estimation sensor arrays Iterative algorithms Covariance matrix Vectors signal processing Principal component analysis Frequency estimation Multiple signal classification

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