Download Free Time Delay Estimation Book in PDF and EPUB Free Download. You can read online Time Delay Estimation and write the review.

Audio Signal Processing for Next-Generation Multimedia Communication Systems presents cutting-edge digital signal processing theory and implementation techniques for problems including speech acquisition and enhancement using microphone arrays, new adaptive filtering algorithms, multichannel acoustic echo cancellation, sound source tracking and separation, audio coding, and realistic sound stage reproduction. This book's focus is almost exclusively on the processing, transmission, and presentation of audio and acoustic signals in multimedia communications for telecollaboration where immersive acoustics will play a great role in the near future.
Time delays exist in many engineering systems such as transportation, communication, process engineering and networked control systems. In recent years, time delay systems have attracted recurring interests from research community. Much of the effort has been focused on stability analysis and stabilization of time delay systems using the so-called Lyapunov-Krasovskii functional together with a linear matrix inequality approach, which provides an efficient numerical tool for handling systems with delays in state and/or inputs. Recently, some more interesting and fundamental development for systems with input/output (i/o) delays has been made using time domain or frequency domain approaches. These approaches lead to analytical solutions to time delay problems in terms of Riccati equations or spectral factorizations. This monograph presents simple analytical solutions to control and estimation problems for systems with multiple i/o delays via elementary tools such as projection. We propose a re-organized innovation analysis approach for delay systems and establish a duality between optimal control of systems with multiple input delays and smoothing estimation for delay free systems. These appealing new techniques are applied to solve control and estimation problems for systems with multiple i/o delays and state delays under both the H2 and H-infinity performance criteria.
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 author investigates the possibility of exploiting the properties of a detected Low Probability of Intercept (LPI) signal waveform to estimate time delay, and by geometry, angle of arrival. The case is considered where a highly correlated signal is received at two stationary passive receivers. The signal source is assumed stationary, and the signal waveform designed so that the ambiguity function has a sharp peak. The minimum time?delay estimate error, the Cramer?Rao bound, is also examined. The results indicate that the method works well for highly correlated pulsed signals, and may prove useful for other types of signals, such as CW signals and pseudo?random noise.
This text introduces and investigates estimation algorithms for signal registration. Signal registration can be defined as the problem of estimating a varying displacement between two random processes. This problem has great importance in many applications, perhaps the most familiar of which lies in the field of passive sonar. The bearing of the signal source is related to the time delay (displacement) between two random waveforms. In the general signal registration problem, the time delay is itself a random function of time. Part one of this book is devoted to the problem of variable time delay estimation. Another application of the signal registration lies in image processing where registration is called motion estimation. By determining the relative displacement (motion) between the intensities of consecutive image frames, one can encode an image more efficiently. In this application, the displacement is a position-dependent vector process. Part two discusses the problem of nonuniform image motion estimation.
This book presents selected papers from the Sixteenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, in conjunction with the Thirteenth International Conference on Frontiers of Information Technology, Applications and Tools, held on November 5–7, 2020, in Ho Chi Minh City, Vietnam. It is divided into two volumes and discusses the latest research outcomes in the field of Information Technology (IT) including information hiding, multimedia signal processing, big data, data mining, bioinformatics, database, industrial and Internet of things, and their applications.