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Multitone sensor gain calibration in an uncertain underwater environment

Multitone sensor gain calibration in an uncertain underwater...

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sensor array and multichannel signal processing workshop

作者： I. Avital J. Tabrikian H. Messer Department of EE-Systems Tel-Aviv University Tel-Aviv Israel Ben-Gurion University of the Negev Beersheba Israel

array processing techniques for source detection and localization in an underwater acoustic environment are highly sensitive to both environmental modeling errors, such as sound propagation conditions, and sensor gain mismatch. Sonar arrays, which are normally rigorously calibrated before placement, may develop gain mismatch due to mechanical failures or local environmental variations, such as sediment build-up. In order to avoid performance degradation of detection and localization algorithms, a sensor gain calibration process can be carried out periodically. This paper proposes a maximum likelihood algorithm for sensor gain calibration in a shallow water environment. In the presence of environmental uncertainties, a robust algorithm is required, and such an algorithm is consequentially developed. The proposed method is based on the simultaneous estimation of the relative gains and the acoustic transfer function. To improve the accuracy of the sensor gain estimation, a-priori knowledge of the relationship between the sensor gains at different frequencies is exploited. The performance of the proposed calibration method is evaluated via simulations.

关键词： Calibration Acoustic sensors Mechanical sensors Frequency estimation array signal processing Acoustic signal detection Underwater tracking Underwater acoustics Acoustic propagation sensor arrays

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Cramer-Rao bounds for estimating range, velocity, and direction with a sensor array

Cramer-Rao bounds for estimating range, velocity, and direct...

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sensor array and multichannel signal processing workshop

作者： A. Dogandzic A. Nehorai EEC$ Department (M/C 154) University of Illinois Chicago Chicago IL USA

We derive Cramer-Rao bound (CRB) expressions for the range (time delay), velocity (Doppler shift), and direction of a point target using an active radar or sonar array. The CRB expressions are derived for an arbitrary signal waveform and a noise model that allows both spatial and temporal correlation. We discuss the relationship between the CRB and ambiguity function for this model. Then, we simplify the CRB for the cases of temporally or spatially uncorrelated noise. We compute the CRB for a 3-dimensional array with isotropic sensors in spatially uncorrelated noise and show that it is a function of the array geometry only through the "moments of inertia" of the array. The volume of the confidence region for the target's location is proposed as a measure of accuracy. For this measure, we show that the highest (and lowest) target location accuracy is achieved if the target lies along one of the principal axes of inertia of the array.

关键词： sensor arrays Doppler shift Delay effects Doppler radar Radar antennas Delay estimation Sonar Volume measurement Antenna arrays Baseband

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Beamspace IQML

Beamspace IQML

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sensor array and multichannel signal processing workshop

作者： Zhi Tian H.L. Van Trees Center of Excellence George Mason Univ. Fairfax VA USA Center of Excellence in C3I George Mason University Fairfax VA USA

The iterative quadratic maximum likelihood (IQML) is an efficient approach for estimating the directions of arrival (DOA) of signals impinging on a uniform linear array. It is desirable to apply the IQML method in beamspace so as to take advantage of the benefits of beamspace operations in terms of reduced computational complexity and improved resolution thresholds. The difficulty with beamspace IQML is that the Vandermonde structure of the array manifold may not preserve during the beamspace transformation. We tackle this obstacle using discrete Fourier transform (DFT) beams and derive a parameterized polynomial in the beamspace dimension. The proposed beamspace IQML algorithm is computationally efficient, and provides satisfactory estimation results.

关键词： Discrete Fourier transforms sensor arrays Polynomials Maximum likelihood estimation Direction of arrival estimation Iterative methods Computational complexity signal resolution Multiple signal classification Vectors

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Effects of crossterms on the performance of time-frequency MUSIC

Effects of crossterms on the performance of time-frequency M...

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sensor array and multichannel signal processing workshop

作者： M.G. Amin Yimin Zhang Department of Electrical and Computer Engineering Villanova University Villanova PA USA

Spatial time-frequency distributions (STFDs) have been introduced as the natural means to deal with source signals that are localizable in the time-frequency domain. It has been shown that improved estimates of the signal and noise subspaces are achieved by constructing the subspaces from the time-frequency signatures of the signal arrivals rather than from the data covariance matrices, which are commonly used in conventional subspace estimation methods. This paper discusses the application of STFD to high-resolution direction finding. We focus on both the role and the effect of crossterms in angle estimation when multiple time-frequency points are incorporated. Simulation examples are presented to compare the performance of joint block-diagonalization and time-frequency averaging techniques for incorporating multiple autoterm and crossterm points in subspace estimation.

关键词： Time frequency analysis Multiple signal classification sensor arrays signal processing Frequency estimation Performance analysis Vectors Noise robustness Energy resolution Spatial resolution

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Adaptive digital beamforming for preserving monopulse target angle estimation accuracy in jamming

Adaptive digital beamforming for preserving monopulse target...

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sensor array and multichannel signal processing workshop

作者： Kai-Bor Yu D.J. Murrow GE Research and Development Center Niskayuna NY USA Radar & Sensors Systems Ockheed Martin Ocean Syracuse NY USA

The monopoulse technique for target angle estimation fails when there is sidelobe and/or mainlobe jamming. If not effectively encountered, electronic jamming prevents successful radar target detection and tracking. We have developed a technique which cancels one mainlobe jammer and multiple sidelobe jammers in such a way that enables both target detection and unbiased monopulse angle estimation. Our technique makes use of adaptive digital beamforming for sidelobe jamming cancellation followed by a mainlobe canceller for mainlobe jamming cancellation. A constrained adaptation is imposed to maintain the mainbeam in the sidelobe cancellation process.

关键词： array signal processing Jamming Adaptive arrays Radar tracking Object detection Direction of arrival estimation Target tracking signal to noise ratio Phased arrays signal processing algorithms

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A retina-like CMOS sensor and its applications

A retina-like CMOS sensor and its applications

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sensor array and multichannel signal processing workshop

作者： G. Sandini P. Questa D. Scheffer B. Diericks A. Mannucci LIRA-Laboratories DIST University of Genoa Italy Aitek S.r.l Genoa Italy IMEC Belgium Video Display Systems S. r. l Italy

This paper describes the implementation in silicon of a retina-like sensor characterized by a space-variant resolution similar to that of the human retina. Besides the actual implementation using CMOS technology, the design peculiarities of retina-like sensors are compared with the use of software or hardware electronic remappers. The paper also describes the realization of a retina-like digital camera and its applications for real-time control and image transmission.

关键词： sensor phenomena and characterization Application software CMOS technology Silicon Humans Retina CMOS image sensors Space technology Hardware Digital cameras

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An approach to adaptive beam-forming for wide-band systems using a subband decomposition

An approach to adaptive beam-forming for wide-band systems u...

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sensor array and multichannel signal processing workshop

作者： G.M. Raz M I T Lincoln Laboratory Lexington MA USA

The purpose of this work is to introduce two variations of an approach to adaptive beam-forming for wide-band sensor array systems using a subband decomposition. Subband decomposition facilitates a computational complexity efficient approach to the adaptive beam-forming problem. We derive optimal adaptive weights in the subband domain using two optimality criteria: (a) maximum SINR, and (b) minimum MSE. It is shown that, unlike the narrow-band case where these criteria yield the same weights up to an overall multiplicative constant, here the two criteria result in different adaptive weights. Explicit conditions for this approach are given. Further, an approach for avoiding spatial mismatch errors is shown.

关键词： Wideband sensor arrays sensor systems Adaptive arrays Computational complexity signal to noise ratio Narrowband Filter bank Covariance matrix Gas insulated transmission lines

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Cellular and PCS propagation measurements and statistical models for urban multipath on an antenna array

Cellular and PCS propagation measurements and statistical mo...

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sensor array and multichannel signal processing workshop

作者： C.M. Keller D.W. Bliss MIT Lincoln Laboratories Lexington MA USA

Multipath propagation has a significant impact on the performance of cellular and personal communication services (PCS) systems in urban environments. This paper contains analyses to better understand urban multipath and examines the use of base-station antenna arrays to obtain spatial diversity. The results are based on data collected on large sparse aperture arrays and finely sampled arrays at a location below surrounding roof top heights for both PCS and cellular frequencies. A statistical model is formulated to explain the relationship between multipath scatterers and signal cross-correlations as a function of antenna spacing.

关键词： Personal communication networks Antenna measurements Antennas and propagation Antenna arrays Aperture antennas Scattering Receiving antennas Broadband antennas Adaptive arrays Decorrelation

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Mean convergence rate of a decision directed adaptive beamformer with Gaussian interference

Mean convergence rate of a decision directed adaptive beamfo...

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sensor array and multichannel signal processing workshop

作者： T.E. Biedka J.H. Reed W.H. Tranter Raytheon Systems Company Greenville TX USA Mobile and Portable Radio Research Group Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Blacksburg VA USA

New analytic results on the convergence of a blind decision directed adaptive algorithm in a beamforming application are presented. The data received at multiple antennas is assumed to consist of a desired PSK signal plus additive Gaussian noise and interference. The mean improvement in output SINR obtained with one iteration of the adaptive algorithm is predicted. This is used to estimate the number of iterations required for convergence. Results are presented for BPSK and QPSK signals. The performance of the decision directed algorithm and a constant modulus algorithm is also compared.

关键词： Convergence Adaptive algorithm Algorithm design and analysis array signal processing Receiving antennas Phase shift keying Additive noise Gaussian noise Interference signal to noise ratio

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Searching beyond SVD for rank reduction

Searching beyond SVD for rank reduction

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sensor array and multichannel signal processing workshop

作者： Yingbo Hua Department of Electrical and Electronic Engineering University of Melbourne VIC Australia

Singular value decomposition (SVD) is analytically inherent in various reduced rank filters and/or estimators. But the computation of SVD is generally not an efficient way for rank reduction. This paper introduces an efficient approach to computing for rank reduction. This approach, referred to as the alternate power (AP) method, is globally and exponentially convergent under a weak condition, and is a generalization of the conventional power method for subspace computation. The AP method is especially useful for computing the reduced rank filter (RRF) by Brillinger (1975), the reduced rank Wiener filter (RRWF) by Scharf (1991), and the reduced rank maximum likelihood estimate (RRMLE) by Stoica and Viberg (1996).

关键词： Wiener filter Singular value decomposition Power engineering computing Maximum likelihood detection Maximum likelihood estimation Filtering signal processing Data compression Feature extraction Matrix decomposition

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