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Introductory, systematic treatment of the many interrelated aspects. Twenty-three contributions address the fundamentals, spectral estimation algorithms, image processing, land and ocean seismic data, telecommunications, 3-D object reconstructions. Alk. paper. Annotation copyright Book News, Inc. Po
This paper investigated methods for passive estimation of the bearing to a slowly moving acoustically radiating source. The mathematics for the solution to such a problem is analogous to estimating the time delay (or group delay) between two time series. Since the estimation of time delay is intimately related to the coherence between two time series, a summary of the properties of coherence is presented. (Author).
This study investigates methodologies for passive estimation of the bearing to a slowly moving acoustically radiating source. The mathematics for the solution to such a problem is analogous to estimating the time delay (or group delay) between two time series. The estimation of time delay is intimately related to the coherence between two time series. New results on using coherence to provide information about linear and nonlinear systems are presented. The maximum likelihood (ML) estimate of time delay is derived; the explicit dependence of the estimate on coherence is evident in the realization in which the two time series are prefiltered (to accentuate frequency bands of high coherence) and subsequently crosscorrelated. Also included are statistics of the estimates of the magnitude-squared coherence (MSC), including the probability density function, the cumulative distribution function, and the m-th moment of the MSC estimate. A complete discussion of the bias and the variance of the MSC estimates is presented. The receiver operating characteristics of a linearly thresholded coherence estimation detector are also presented. A general FORTRAN 4 computer program using the fast Fourier transform to estimate time delay is given.
This document presents both the oral and written versions of a paper presented (in 15 minutes) on 13 April 1976 at the 1976 IEEE International Conference on Acoustics Speech, and Signal Processing, in Philadelphia, Pennsylvania. A maximum likelihood (ML) estimator is derived for determining time delay between two signals observed in the presence of uncorrelated noise, under the assumptions of known signal and noise spectral characteristics. This ML estimator is derived for determining time delay between two signals observed in the presence of uncorrelated noise, under the assumptions of known signal and noise spectral characteristics. This ML estimator can be realized as a pair of receiver prefilters followed by a cross correlator. The time argument at which the correlator achieves a maximum is the delay estimate. Qualitatively, the role of the prefilters is to weight the signal passed to the correlator according to the strength of the coherence function. Other realizations of the ML processor are also discussed. The variance of a generalized correlation time delay estimator is derived when the estimate is in the neighborhood of the true delay. An example using these results is given with emphasis on the effect of erroneously specifying the frequency weighting to be employed. Limitations of the derived results are also discussed. (Author).
The summer school held in Portovenere followed a tutorial format with the purpose of familiarizing postdoctoral or postgraduate students in the basic theories and up-to-date applications of present knowledge. Although, from a teaching point of view, a certain areount of overlapping is always useful, in order to avoid excessive duplication direct contact between lecturers expert in the same subject was encouraged during the preparation phase. In recent years computer facilities and theoretical implementa tion have considerably increased the possibility of solving problems relating to signal detection in noise. Any type of communication may take advantage of signal processing principles, including any type of physical measurement that can be considered as a non-semantic and/or quasi-semantic communication. Since signal processing techniques are common to many branches of science (telecommunications, radar, sonar, seismology, geophysics, nuclear research, space research and others), the advanced and sophisticated levels reached singularly in anyone of them could be used to the advantage of the others. In particular, underwater acoustics is a discipline which, to some extent, represents a practical general model that has permitted the development of signal processing techniques suitable to meet data reduction and interpretation needs of other branches of science. This ASI consequently underlined the inter-disciplinarity of signal proces sing in order that the principles of outstanding methods developed in one field may be adapted to others.
Contents: On Generating Processes With Specified Coherence; Evaluation of the Statistics of the Estimate of Magnitude Squared Coherence; Some Practical Considerations of Coherence Estimation; Estimation of the Magnitude-Squared Coherence Function (Spectrum); Statistics of the Estimate of Magnitude Coherence; The Smoothed Coherence Transform (SCOT); Coherence Estimation as Affected by Weighting Functions and Fast Fourier Transform Size; A Digital Computer Algorithm for Estimation of the Power Spectral Density Matrix Using the Partitioned Modified Chirp Z Transform; Coherence Estimation Via the Partitioned Modified Chirp Z Transform; Approximation for Statistics of Coherence Estimators; Time Delay Estimation; The Role of Coherence in Time Delay Estimation; On the Variance of the Phase Estimate of the Cross Spectrum and Coherence; Positive Definite Spectral Estimate and Stable Correlation Recursion for Multivariate Linear Predictive Spectral Analysis; and Confidence Bounds for Magnitude-Squared Coherence Estimates.