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共 176 条记录，以下是91-100 订阅

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CONTRIBUTION OF THE POLARIZATION DIVERSITY IN HF DIRECTION FINDING SYSTEMS

CONTRIBUTION OF THE POLARIZATION DIVERSITY IN HF DIRECTION F...

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5th SPIE conference on advanced signal processing - algorithms, architectures, and implementations

作者： ERHEL, Y EDJEOU, A BERTEL, L CTR RECH ECOLES COETQUIDAN F-56381 GUERFRANCE

ISBN: (纸本)0819416207

The aim of the paper is to estimate the contribution of the polarization diversity in high frequency (3 - 30 MHz) direction finding systems. We first describe the peculiarities of H.F. propagation and the resulting signal model involved in computer simulations. Next, we analyze the behavior of some particular direction finding systems using linear and circular geometries and polarization diversity. Some algorithms (non linear frequential analysis, M.U.S.I.C.) are tested in several conditions (narrowband or broadband signals, polarization filtering reiterated or no, sub-sampling). Theoretical and experimental results show that polarization diversity based upon the knowledge of the antenna complex responses improves greatly the efficiency of direction finding.

关键词： DIRECTION FINDING POLARIZATION ARRAY processing HIGH RESOLUTION algorithms HF PROPAGATION

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Wavelet-domain hidden Markov models for signal detection and classification

Wavelet-domain hidden Markov models for signal detection and...

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conference on advanced signal processing - algorithms, architectures, and implementations viI

作者： Crouse, MS Nowak, RD Mhirsi, K Baraniuk, RG Rice Univ. (United States) Michigan State Univ. (United States)

ISBN: (纸本)0819425842

This paper addresses the problem of detection and classification of complicated signals in noise. Classical detection methods such as energy detectors and linear discriminant analysis do not perform well in many situations of practical interest. We introduce a new approach based on hidden Markov modeling in the wavelet domain. Using training data, we fit a hidden Markov model (HMM) to the wavelet transform to concisely represent its probabilistic time-frequency structure. The HMM provides a natural framework for performing likelihood ratio tests used in signal detection and classification. We compare our approach with classical methods for classification of nonlinear processes, change-point detection, and detection with unknown delay.

关键词： wavelets hidden Markov models detection classification

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Optimal inversions of uncertain matrices - an estimation and control perspective

Optimal inversions of uncertain matrices - an estimation and...

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conference on advanced signal processing algorithms architectures and implementations XIII

作者： Tao, KM SRI Int Menlo Pk CA 94025 USA

ISBN: (纸本)0819450782

Many system and signal related problems involve matrix inversion of some kind. For example, in estimation and signal recovery applications, inversion of the channel response matrix is often required in order to estimate the source signals. In the control of multivariable systems, inverting a process gain matrix may be called for in order to deliver appropriate control actions. There are situations where these matrices should be considered as uncertain (or random): for example, when the process/channel environments vary randomly, or when significant uncertainties are involved in estimating these matrices. Based on a unified approach, this paper considers both the right inversion (for control) and the left inversion (for estimation) of random matrices. In both cases, minimizing a statistical error function leads to the determination of optimal or linear optimal inversion. Connections with related techniques, such as the total least squares (TLS), the ridge regression, the Levenberg-Marquardt algorithm and the regularization theory are discussed. A variant Kalman filtering problem with randomly varying measurement gain matrix is among the applications addressed. Monte Carlo simulation results show substantial benefits by taking process/model uncertainty into consideration.

关键词： statistical inversion of uncertain matrices signal processing estimation control Kalman filtering with random measurement matrix channel equalization

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Seismic-array signal processing for moving source localization

Seismic-array signal processing for moving source localizati...

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conference on advanced signal processing algorithms, architectures, and implementations XviI

作者： Stafsudd, Jing Z. Hudson, Ralph E. Taciroglu, Ertugrul Yao, Kung UCLA Dept Elect Engn Los Angeles CA 90095 USA UCLA Dept Civil & Environm Engn Los Angeles CA 90095 USA

ISBN: (纸本)9780819468451

In this paper, we consider the use of a seismic sensor array for the localization and tracking of a wideband moving source. The proposed solution consists of two steps: source Direction-Of-Arrival (DOA) estimation and localization via DOA estimates. Three DOA estimation methods are considered. The Covariance Matrix Analysis and the Surface Wave Analysis are previously published DOA estimation algorithms shown to be effective in the localization of a stationary wideband source. This paper investigates their performance on moving wideband sources. A novel DOA estimation algorithm, the Modified Kirlin's Method was also developed for the localization of a moving Source. The DOAs estimated by these algorithms are combined rising a least-squares optimization for source localization. The application of these algorithms to real-life data show the effectiveness of both the Surface Wave Analysis and the Modified Kirlin's Method in locating and tracking a wideband moving source.

关键词： direction-of-arrival (DOA) source localization mover localization seismic signal processing surface waves

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Simultaneous operation of two over-the-horizon radars

Simultaneous operation of two over-the-horizon radars

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conference on advanced signal processing algorithms, architectures, and implementations XIV

作者： Zhang, YM Frazer, GJ Amin, MG Villanova Univ Ctr Adv Commun Villanova PA 19085 USA Def Sci & Technol Org Intelligence Surveillance & Reconnaissance Div Edinburgh SA 5111 Australia

ISBN: (纸本)0819454974

Over the horizon radar (OTHR) is a well developed sensor technology in established use for long-range air and surface surveillance. More detailed information about the targets can be achieved by using simultaneous operation of multiple OTHRs. However, a key limitation with HF radar is the conflict between selection of an appropriate operating frequency and the demand for radar waveform bandwidth commensurate with the range resolution requirement of the radar. In this paper, we consider the simultaneous operation of two over-the-horizon radar systems that use the same frequency band with different chirp waveforms to respond the advanced wide-area surveillance needs without reducing, the pulse repetitive frequency. A cross-radar interference cancellation technique is proposed and shown to be effective.

关键词： Radar Doppler effect Receivers Surveillance Time-frequency analysis Fermium Frequency modulation signal processing Knowledge management Sensor technology

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A unified Bayesian framework for algorithms to recover blocky signals

A unified Bayesian framework for algorithms to recover block...

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conference on advanced signal processing algorithms, architectures, and implementations XviI

作者： Calvetti, Daniela Somersalo, Erkki Case Western Reserve Univ Dept Math Cleveland OH 44106 USA Case Western Reserve Univ Ctr Modeling Integrated Metab Syst Cleveland OH 44106 USA Aalto Univ Dept Math Helsinki Finland

ISBN: (纸本)9780819468451

We consider the problem of recovering signals from noisy indirect observations under the additional a priori information that the signal is believed to be slowly varying except at all unknown number of points where it may have discontinuities of unknown size. The model problem is a linear deconvolution problem. To take advantage of the qualitative prior information available, we use a non-stationary Markov model with the variance of the innovation process also unknown, and apply Bayesian techniques to estimate both the signal and the prior variance. We propose a fast iterative method for computing a MAP estimates and we show that, with a rather standard choices of the hyperpriors, the algorithm produces the fixed point iterative solutions of the total variation and of the Perona-Malik regularization methods. We also demonstrate that, unlike the non-statistical estimation methods, the Bayesian approach leads to a very natural reliability assessment of edge detection by a Markov Chain Monte Carlo (MCMC) based analysis of the posterior.

关键词： signal processing Data modeling Reliability Stochastic processes Atrial fibrillation Autoregressive models Deconvolution Monte Carlo methods Statistical analysis Mathematics

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Segmented chirp features and hidden Gauss-Markov models for classification of wandering-tone signals

Segmented chirp features and hidden Gauss-Markov models for ...

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conference on advanced signal processing algorithms, architectures and implementations XII

作者： Ainsleigh, PL USN Undersea Warfare Ctr Newport RI 02840 USA

ISBN: (纸本)0819445584

A new feature set and decision function are proposed for classifying transient wandering-tone signals. signals are partitioned in time and modeled as having piecewise-linear instantaneous frequency and piecewise-constant amplitude. The initial frequency, chirp rate, and amplitude are estimated in each segment. The resulting sequences of estimates are used as features for classification. The decision function employs a linear Gaussian dynamical model, or hidden Gauss-Markov model (HGMM). The parameters that characterize the HGMM for each class are estimated from labeled training sequences, and the trained models are used to evaluate the class-conditional likelihoods of an unlabeled signal. The signal is assigned to the-class whose model gives the maximum conditional likelihood. Simulation experiments demonstrate perfect classification performance in a three-class forced-choice problem.

关键词： Ferroelectric materials Bismuth Picosecond phenomena Information technology Weapons of mass destruction signal processing

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A novel signal detection technique based on generalized scale transforms - art. no. 63130Y

A novel signal detection technique based on generalized scal...

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conference on advanced signal processing algorithms, architectures, and implementations Xvi

作者： Nickel, Robert M. Penn State Univ Dept Elect Engn University Pk PA 16802 USA

ISBN: (纸本)0819463922

We are presenting an extension to the classic multiple signal classification method (MUSIC) developed by Schmidt and Bienvenu in 1979.(1) While the classic MUSIC algorithm is limited to the detection of constant frequency sinusoids in white noise, the proposed new method is capable of detecting signals with a continuously varying instantaneous frequency. The method is based on the development of a discrete-time version of the generalized scale transform (GST) which was introduced by Nickel and Williams in 1999.(2) As a byproduct we obtain techniques for discrete-time warp-shift invariant filtering which can be used in addition to the signal detection to separate signals with different instantaneous frequency contours.

关键词： warping functions sampling theory generalized scale transform signal detection multiple signal classification (MUSIC)

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Missile signal processing common computer architecture for rapid technology upgrade

Missile signal processing common computer architecture for r...

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conference on advanced signal processing algorithms, architectures, and implementations XIV

作者： Rabinkin, D Rutledge, E Monticciolo, P MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819454974

Interceptor missiles process IR images captured by a focal plane array for locating and guiding the interceptor toward an intended target. A typical interceptor signal processing chain comprises two parts. Front-end video processing operates on all pixels of the image and performs such operations as non-uniformity correction (NUC), image stabilization, frame integration and detection. Back-end target processing, which tracks and classifies targets detected in the image, performs such algorithms as Kalman tracking, spectral feature extraction and target discrimination. signal processing requirements increased as sensor bandwidth increases and interceptors operate against more sophisticated targets. In the past, video processing was implemented using ASICs or FPGAs because computation requirements exceeded the throughput of general-purpose processors. Target processing was performed using hybrid architectures that included ASICs. DSPs and general-purpose processors. The resulting systems tended to be very function-specific, and required custom software development. These systems were developed using non-integrated toolsets, and test equipment had to be developed along with the processor platform. The lifespan of the interceptor platform on which the signal processors operate often spans decades, while the specialized nature of processsor hardware and software makes it difficult and costly to upgrade. As a result., the signal processing systems often run on outdated components, signal processing algorithms are difficult to update. and system effectiveness is impaired by the inability to rapidly, respond to new threats. A new design approach to interceptor signal processing is made possible by three developments: Moore's Law - driven improvement in computational throughput;a newly introduced vector computing capability in general-purpose processors and a modern set of open interface software standards. Today's multiprocessor commercial-off-the-shelf (COTS) platforms hav

关键词： signal processing Digital signal processing Target detection Detection and tracking algorithms Image processing Standards development MATLAB Commercial off the shelf technology signal to noise ratio Software development

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Application of time-frequency analysis methods to speaker verification

Application of time-frequency analysis methods to speaker ve...

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conference on advanced signal processing algorithms, architectures, and implementations Xvi

作者： Williams, W. J. Bossemeyer, R. W. Quantum Signal LLC Ann Arbor MI 48176 USA Univ Michigan EECS Ann Arbor MI 48109 USA Speech Technol Appl Res Inc St Charles IL USA

ISBN: (纸本)0819463922

Time-Frequency Analysis has previously been successfully applied to characterize and quantify a variety of acoustic signals, including marine mammal sounds. In this research, Time-Frequency analysis is applied to human speech signals in an effort to reveal signal structure salient to the biometric speaker verification challenge. Prior approaches to speaker verification have relied upon signal processing analysis such as linear prediction or weighted Cepstrum spectral representations of segments of speech and classification techniques based on stochastic pattern matching. The authors believe that the classification of identity of a speaker based on time-frequency representation of short time events occurring in speech could have substantial advantages. Using these ideas, a speaker verification algorithm was developed(1) and has been refined over the past several years. In this presentation, the authors describe the testing of the algorithm using a large speech database, the results obtained, and recommendations for further improvements.

关键词： time-frequency speaker verification multimodal biometrics homeland security pattern recognition

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