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The Resource Modern radar detection theory, edited by Antonio De Maio, Maria Sabrina Greco, (electronic book)

Modern radar detection theory, edited by Antonio De Maio, Maria Sabrina Greco, (electronic book)

Label
Modern radar detection theory
Title
Modern radar detection theory
Statement of responsibility
edited by Antonio De Maio, Maria Sabrina Greco
Contributor
Editor
Subject
Language
eng
Summary
"Recently, various algorithms for radar signal detection that rely heavily upon complicated processing and/or antenna architectures have been the subject of much interest. These techniques owe their genesis to several factors. One is revolutionary technological advances in high-speed signal processing hardware and digital array radar technology. Another is the stress on requirements often imposed by defence applications in areas such as airborne early warning and homeland security. This book explores these emerging research thrusts in radar detection with advanced radar systems capable of operating in challenging scenarios with a plurality of interference sources, both man-made and natural. Topics covered include: adaptive radar detection in Gaussian interference with unknown spectral properties; invariance theory as an instrument to force the Constant False Alarm Rate (CFAR) property at the design stage; one- and two-stage detectors and their performances; operating scenarios where a small number of training data for spectral estimation is available; Bayesian radar detection to account for prior information in the interference covariance matrix; and radar detection in the presence of non-Gaussian interference. Detector design techniques based on a variety of criteria are thoroughly presented and CFAR issues are discussed. Performance analyses representative of practical airborne, as well as ground-based and shipborne, radar situations are shown. Results on real radar data are also discussed. Modern Radar Detection Theory provides a comprehensive reference on the latest developments in adaptive radar detection for researchers, advanced students and engineers working on statistical signal processing and its applications to radar systems"--Provided by publisher
Cataloging source
EBLCP
Dewey number
621.3848
Illustrations
illustrations
Index
index present
LC call number
TK6575
LC item number
.M626 2016
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • De Maio, Antonio
  • Greco, Maria
http://library.link/vocab/subjectName
Radar
Label
Modern radar detection theory, edited by Antonio De Maio, Maria Sabrina Greco, (electronic book)
Instantiates
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Ram S. Raghavan, Shawn Kraut, and Christ D. Richmond
  • 4.
  • Two-Stage Detectors for Point-Like Targets in Gaussian Interference with Unknown Spectral Properties
  • Antonio De Maio, Chengpeng Hao, and Danilo Orlando
  • 5.
  • Bayesian Radar Detection in Interference
  • Pu Wang, Hongbin Li, and Braham Himed
  • 6.
  • Adaptive Radar Detection for Sample-Starved Gaussian Training Conditions
  • Yuri I. Abramovich and Ben A. Johnson
  • 1.
  • 7.
  • Compound-Gaussian Models and Target Detection: A Unified View
  • K. James Sangston, Maria S. Greco, and Fulvio Gini
  • 8.
  • Covariance Matrix Estimation in SIRV and Elliptical Processes and Their Applications in Radar Detection
  • Jean-Philippe Ovarlez, Frédéric Pascal, and Philippe Forster
  • 9.
  • Detection of Extended Target in Compound-Gaussian Clutter
  • Augusto Aubry, Javier Carretero-Moya, Antonio De Maio, Antonio Pauciullo, Javier Gismero-Menoyo, and Alberto Asensio-Lopez
  • Introduction to Radar Detection
  • Antonio De Maio, Maria S. Greco, and Danilo Orlando
  • 2.
  • Radar Detection in White Gaussian Noise: A GLRT Framework
  • Ernesto Conte, Antonio De Maio, and Guolong Cui
  • 3.
  • Subspace Detection for Adaptive Radar: Detectors and Performance Analysis
Control code
KNOVEL945612152
Dimensions
unknown
Extent
1 online resource (382 pages)
File format
unknown
Form of item
online
Isbn
9781523101757
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
Label
Modern radar detection theory, edited by Antonio De Maio, Maria Sabrina Greco, (electronic book)
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Ram S. Raghavan, Shawn Kraut, and Christ D. Richmond
  • 4.
  • Two-Stage Detectors for Point-Like Targets in Gaussian Interference with Unknown Spectral Properties
  • Antonio De Maio, Chengpeng Hao, and Danilo Orlando
  • 5.
  • Bayesian Radar Detection in Interference
  • Pu Wang, Hongbin Li, and Braham Himed
  • 6.
  • Adaptive Radar Detection for Sample-Starved Gaussian Training Conditions
  • Yuri I. Abramovich and Ben A. Johnson
  • 1.
  • 7.
  • Compound-Gaussian Models and Target Detection: A Unified View
  • K. James Sangston, Maria S. Greco, and Fulvio Gini
  • 8.
  • Covariance Matrix Estimation in SIRV and Elliptical Processes and Their Applications in Radar Detection
  • Jean-Philippe Ovarlez, Frédéric Pascal, and Philippe Forster
  • 9.
  • Detection of Extended Target in Compound-Gaussian Clutter
  • Augusto Aubry, Javier Carretero-Moya, Antonio De Maio, Antonio Pauciullo, Javier Gismero-Menoyo, and Alberto Asensio-Lopez
  • Introduction to Radar Detection
  • Antonio De Maio, Maria S. Greco, and Danilo Orlando
  • 2.
  • Radar Detection in White Gaussian Noise: A GLRT Framework
  • Ernesto Conte, Antonio De Maio, and Guolong Cui
  • 3.
  • Subspace Detection for Adaptive Radar: Detectors and Performance Analysis
Control code
KNOVEL945612152
Dimensions
unknown
Extent
1 online resource (382 pages)
File format
unknown
Form of item
online
Isbn
9781523101757
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote

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