Model Based Localization For A Shallow Ocean Experiment
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Model Based Localization For A Shallow Ocean Experiment
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Author :
language : en
Publisher:
Release Date : 1995
Model Based Localization For A Shallow Ocean Experiment written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with categories.
Model Based Inversion For A Shallow Ocean Application
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Author :
language : en
Publisher:
Release Date : 1994
Model Based Inversion For A Shallow Ocean Application written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
A model-based approach to invert or estimate the sound speed profile (SSP) from noisy pressure-field measurements is discussed. The resulting model-based processor (MBP) is based on the state-space representation of the normal-mode propagation model. Using data obtained from the well-known Hudson Canyon experiment, a noisy shallow water ocean environment, the processor is designed and the results compared to those predicted using various propagation models and data. It is shown that the MBP not only predicts the sound speed quite well, but also is able to simultaneously provide enhanced estimates of both modal and pressure-field measurements which are useful for localization and rapid ocean environmental characterization.
Model Based Signal Processing
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Author : James V. Candy
language : en
Publisher: John Wiley & Sons
Release Date : 2005-10-27
Model Based Signal Processing written by James V. Candy and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-10-27 with Technology & Engineering categories.
A unique treatment of signal processing using a model-based perspective Signal processing is primarily aimed at extracting useful information, while rejecting the extraneous from noisy data. If signal levels are high, then basic techniques can be applied. However, low signal levels require using the underlying physics to correct the problem causing these low levels and extracting the desired information. Model-based signal processing incorporates the physical phenomena, measurements, and noise in the form of mathematical models to solve this problem. Not only does the approach enable signal processors to work directly in terms of the problem's physics, instrumentation, and uncertainties, but it provides far superior performance over the standard techniques. Model-based signal processing is both a modeler's as well as a signal processor's tool. Model-Based Signal Processing develops the model-based approach in a unified manner and follows it through the text in the algorithms, examples, applications, and case studies. The approach, coupled with the hierarchy of physics-based models that the author develops, including linear as well as nonlinear representations, makes it a unique contribution to the field of signal processing. The text includes parametric (e.g., autoregressive or all-pole), sinusoidal, wave-based, and state-space models as some of the model sets with its focus on how they may be used to solve signal processing problems. Special features are provided that assist readers in understanding the material and learning how to apply their new knowledge to solving real-life problems. * Unified treatment of well-known signal processing models including physics-based model sets * Simple applications demonstrate how the model-based approach works, while detailed case studies demonstrate problem solutions in their entirety from concept to model development, through simulation, application to real data, and detailed performance analysis * Summaries provided with each chapter ensure that readers understand the key points needed to move forward in the text as well as MATLAB(r) Notes that describe the key commands and toolboxes readily available to perform the algorithms discussed * References lead to more in-depth coverage of specialized topics * Problem sets test readers' knowledge and help them put their new skills into practice The author demonstrates how the basic idea of model-based signal processing is a highly effective and natural way to solve both basic as well as complex processing problems. Designed as a graduate-level text, this book is also essential reading for practicing signal-processing professionals and scientists, who will find the variety of case studies to be invaluable. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department
Model Based Processing For Underwater Acoustic Arrays
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Author : Edmund J. Sullivan
language : en
Publisher: Springer
Release Date : 2015-05-14
Model Based Processing For Underwater Acoustic Arrays written by Edmund J. Sullivan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-14 with Science categories.
This monograph presents a unified approach to model-based processing for underwater acoustic arrays. The use of physical models in passive array processing is not a new idea, but it has been used on a case-by-case basis, and as such, lacks any unifying structure. This work views all such processing methods as estimation procedures, which then can be unified by treating them all as a form of joint estimation based on a Kalman-type recursive processor, which can be recursive either in space or time, depending on the application. This is done for three reasons. First, the Kalman filter provides a natural framework for the inclusion of physical models in a processing scheme. Second, it allows poorly known model parameters to be jointly estimated along with the quantities of interest. This is important, since in certain areas of array processing already in use, such as those based on matched-field processing, the so-called mismatch problem either degrades performance or, indeed, prevents any solution at all. Thirdly, such a unification provides a formal means of quantifying the performance improvement. The term model-based will be strictly defined as the use of physics-based models as a means of introducing a priori information. This leads naturally to viewing the method as a Bayesian processor. Short expositions of estimation theory and acoustic array theory are presented, followed by a presentation of the Kalman filter in its recursive estimator form. Examples of applications to localization, bearing estimation, range estimation and model parameter estimation are provided along with experimental results verifying the method. The book is sufficiently self-contained to serve as a guide for the application of model-based array processing for the practicing engineer.
Advanced Signal Processing Handbook
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Author : Stergios Stergiopoulos
language : en
Publisher: CRC Press
Release Date : 2017-09-08
Advanced Signal Processing Handbook written by Stergios Stergiopoulos and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-08 with Technology & Engineering categories.
Advances in digital signal processing algorithms and computer technology have combined to produce real-time systems with capabilities far beyond those of just few years ago. Nonlinear, adaptive methods for signal processing have emerged to provide better array gain performance, however, they lack the robustness of conventional algorithms. The challenge remains to develop a concept that exploits the advantages of both-a scheme that integrates these methods in practical, real-time systems. The Advanced Signal Processing Handbook helps you meet that challenge. Beyond offering an outstanding introduction to the principles and applications of advanced signal processing, it develops a generic processing structure that takes advantage of the similarities that exist among radar, sonar, and medical imaging systems and integrates conventional and nonlinear processing schemes.
Oceans 95
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Author :
language : en
Publisher:
Release Date : 1995
Oceans 95 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Marine resources categories.
Acoustic Sensing Techniques For The Shallow Water Environment
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Author : Andrea Caiti
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-21
Acoustic Sensing Techniques For The Shallow Water Environment written by Andrea Caiti and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-21 with Science categories.
This volume contains the collection of papers from the second workshop on Experimental Acoustic Inversion Techniques for Exploration of the Shallow Water Environment. Acoustic techniques provide the most effective means for remote sensing of ocean and sea floor processes, and for probing the structure beneath the sea floor. No other energy propagates as efficiently in the ocean: radio waves and visible light are severely limited in range because the ocean is a highly conductive medium. However, sound from breaking waves and coastal shipping can be heard throughout the ocean, and marine mammals communicate acoustically over basin scale distances. The papers in this book indicate a high level of research interest that has generated significant progress in development and application of experimental acoustic inversion techniques. The applications span a broad scope in geosciences, from geophysical, biological and even geochemical research. The list includes: estimation of geotechnical properties of sea bed materials; navigation and mapping of the sea floor; fisheries, aquaculture and sea bed habitat assessment; monitoring of marine mammals; sediment transport; and investigation of natural geohazards in marine sediments. Audience This book is primarily intended for physicists and engineers working in underwater acoustics and oceanic engineering. It will also be of interest to marine biologists, geophysicists and oceanographers as potential users of the methodologies and techniques described in the book contributions.
Experimental Acoustic Inversion Methods For Exploration Of The Shallow Water Environment
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Author : Andrea Caiti
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Experimental Acoustic Inversion Methods For Exploration Of The Shallow Water Environment written by Andrea Caiti and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
In recent years, research on acoustic remote sensing of the ocean has evolved considerably, especially in studying complex physical and biological processes in shallow water environments. To review the state of the art, an international workshop was held at Carvoeiro, Portugal, in March 1999, bringing together leading international researchers in the field. In contrast to much of the recent theoretical work, emphasis was placed on the experimental validation of the techniques. This volume, based on presentations at this workshop, summarizes a range of diverse and innovative applications. The invited contributions explore the use of acoustics to measure bottom properties and morphology, as well as to probe buried objects within the sediment. Within the water column, sound is applied to imaging of oceanographic features such as currents and tides or monitoring of marine life. Another key theme is the use of sound to solve geometric inverse problems for precise tracking of undersea vehicles. Audience: This volume should be useful both to the novice seeking an introduction to the field and to advanced researchers interested in the latest developments in acoustic sensing of the ocean environment. The workshop was sponsored by the Fundação para a Ciêcia e a Tecnologia (Portuguese Foundation for Science and Technology).
Full Field Inversion Methods In Ocean And Seismo Acoustics
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Author : Orest Diachok
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Full Field Inversion Methods In Ocean And Seismo Acoustics written by Orest Diachok and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Technology & Engineering categories.
Recent advances in the power of inversion methods, the accuracy of acoustic field prediction codes, and the speed of digital computers have made the full field inversion of ocean and seismic parameters on a large scale a practical possibility. These methods exploit amplitude and phase information detected on hydrophone/geophone arrays, thereby extending traditional inversion schemes based on time of flight measurements. Full field inversion methods provide environmental information by minimising the mismatch between measured and predicted acoustic fields through a global search of possible environmental parameters. Full Field Inversion Methods in Ocean and Seismo-Acoustics is the formal record of a conference held in Italy in June 1994, sponsored by NATO SACLANT Undersea Research Centre. It includes papers by NATO specialists and others. Topics covered include: · speed and accuracy of acoustic field prediction codes · signal processing strategies · global inversion algorithms · search spaces of environmental parameters · environmental stochastic limitations · special purpose computer architectures · measurement geometries · source and receiving sensor technologies.
Model Based Processing
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Author : James V. Candy
language : en
Publisher: John Wiley & Sons
Release Date : 2019-03-15
Model Based Processing written by James V. Candy and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-15 with Technology & Engineering categories.
A bridge between the application of subspace-based methods for parameter estimation in signal processing and subspace-based system identification in control systems Model-Based Processing: An Applied Subspace Identification Approach provides expert insight on developing models for designing model-based signal processors (MBSP) employing subspace identification techniques to achieve model-based identification (MBID) and enables readers to evaluate overall performance using validation and statistical analysis methods. Focusing on subspace approaches to system identification problems, this book teaches readers to identify models quickly and incorporate them into various processing problems including state estimation, tracking, detection, classification, controls, communications, and other applications that require reliable models that can be adapted to dynamic environments. The extraction of a model from data is vital to numerous applications, from the detection of submarines to determining the epicenter of an earthquake to controlling an autonomous vehicles—all requiring a fundamental understanding of their underlying processes and measurement instrumentation. Emphasizing real-world solutions to a variety of model development problems, this text demonstrates how model-based subspace identification system identification enables the extraction of a model from measured data sequences from simple time series polynomials to complex constructs of parametrically adaptive, nonlinear distributed systems. In addition, this resource features: Kalman filtering for linear, linearized, and nonlinear systems; modern unscented Kalman filters; as well as Bayesian particle filters Practical processor designs including comprehensive methods of performance analysis Provides a link between model development and practical applications in model-based signal processing Offers in-depth examination of the subspace approach that applies subspace algorithms to synthesized examples and actual applications Enables readers to bridge the gap from statistical signal processing to subspace identification Includes appendices, problem sets, case studies, examples, and notes for MATLAB Model-Based Processing: An Applied Subspace Identification Approach is essential reading for advanced undergraduate and graduate students of engineering and science as well as engineers working in industry and academia.