소장자료
LDR | 05059cam a2200553Ii 4500 | ||
001 | 0100501026▲ | ||
003 | OCoLC▲ | ||
005 | 20210119132756▲ | ||
006 | m o d ▲ | ||
007 | cr cnu---unuuu▲ | ||
008 | 160402t20162016njua ob 001 0 eng d▲ | ||
019 | ▼a947803152▲ | ||
020 | ▼a9781523101757▼q(electronic bk.)▲ | ||
020 | ▼a152310175X▼q(electronic bk.)▲ | ||
020 | ▼z9781613532003▲ | ||
020 | ▼z1613532008▲ | ||
020 | ▼z9781613531990▼q(hardback)▲ | ||
020 | ▼z1613531990▼q(hardback)▲ | ||
029 | 1 | ▼aAU@▼b000057390688▲ | |
029 | 1 | ▼aGBVCP▼b871530635▲ | |
035 | ▼a(OCoLC)945612152▼z(OCoLC)947803152▲ | ||
040 | ▼aEBLCP▼beng▼erda▼epn▼cEBLCP▼dN$T▼dWAU▼dKNOVL▼dCN3GA▼dYDXCP▼dUIU▼dCOO▼dOCLCF▼dBUF▼dSTF▼dIDB▼dMERUC▼dOCLCQ▲ | ||
050 | 4 | ▼aTK6575▼b.M626 2016▲ | |
072 | 7 | ▼aTEC▼x009070▼2bisacsh▲ | |
082 | 0 | 4 | ▼a621.3848▲ |
245 | 0 | 0 | ▼aModern radar detection theory /▼cedited by Antonio De Maio, Maria Sabrina Greco.▲ |
264 | 1 | ▼aEdison, NJ :▼bScitech Publishing, an imprint of the IET,▼c[2016]▲ | |
264 | 4 | ▼c©2016▲ | |
300 | ▼a1 online resource (382 pages)▲ | ||
336 | ▼atext▼btxt▼2rdacontent▲ | ||
337 | ▼acomputer▼bc▼2rdamedia▲ | ||
338 | ▼aonline resource▼bcr▼2rdacarrier▲ | ||
504 | ▼aIncludes bibliographical references and index.▲ | ||
505 | 0 | 0 | ▼g1.▼tIntroduction to Radar Detection /▼rAntonio De Maio, Maria S. Greco, and Danilo Orlando --▼g2.▼tRadar Detection in White Gaussian Noise: A GLRT Framework /▼rErnesto Conte, Antonio De Maio, and Guolong Cui --▼g3.▼tSubspace Detection for Adaptive Radar: Detectors and Performance Analysis /▼rRam S. Raghavan, Shawn Kraut, and Christ D. Richmond --▼g4.▼tTwo-Stage Detectors for Point-Like Targets in Gaussian Interference with Unknown Spectral Properties /▼rAntonio De Maio, Chengpeng Hao, and Danilo Orlando --▼g5.▼tBayesian Radar Detection in Interference /▼rPu Wang, Hongbin Li, and Braham Himed --▼g6.▼tAdaptive Radar Detection for Sample-Starved Gaussian Training Conditions /▼rYuri I. Abramovich and Ben A. Johnson --▼g7.▼tCompound-Gaussian Models and Target Detection: A Unified View /▼rK. James Sangston, Maria S. Greco, and Fulvio Gini --▼g8.▼tCovariance Matrix Estimation in SIRV and Elliptical Processes and Their Applications in Radar Detection /▼rJean-Philippe Ovarlez, Frédéric Pascal, and Philippe Forster --▼g9.▼tDetection of Extended Target in Compound-Gaussian Clutter /▼rAugusto Aubry, Javier Carretero-Moya, Antonio De Maio, Antonio Pauciullo, Javier Gismero-Menoyo, and Alberto Asensio-Lopez.▲ |
520 | ▼a"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.▲ | ||
588 | 0 | ▼aPrint version record.▲ | |
590 | ▼aeBooks on EBSCOhost▼bAll EBSCO eBooks▲ | ||
650 | 0 | ▼aRadar.▲ | |
650 | 7 | ▼aTECHNOLOGY & ENGINEERING▼xMechanical.▼2bisacsh▲ | |
650 | 7 | ▼aRadar.▼2fast▼0(OCoLC)fst01086712▲ | |
655 | 4 | ▼aElectronic books.▲ | |
700 | 1 | ▼aDe Maio, Antonio▼c(College teacher),▼eeditor.▲ | |
700 | 1 | ▼aGreco, Maria▼q(Maria Sabrina),▼eeditor.▲ | |
776 | 0 | 8 | ▼iPrint version:▼tModern radar detection theory.▼dEdison, NJ : Scitech Publishing, [2016]▼z9781613531990▼w(OCoLC)900306413▲ |
856 | 4 | 0 | ▼uhttp://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1179782▲ |
938 | ▼aEBL - Ebook Library▼bEBLB▼nEBL4426680▲ | ||
938 | ▼aEBSCOhost▼bEBSC▼n1179782▲ | ||
938 | ▼aYBP Library Services▼bYANK▼n12866507▲ |

Modern radar detection theory
자료유형
국외eBook
서명/책임사항
Modern radar detection theory / edited by Antonio De Maio, Maria Sabrina Greco.
개인저자
형태사항
1 online resource (382 pages)
서지주기
Includes bibliographical references and index.
내용주기
1. 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 / 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 -- 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.
요약주기
"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.
기타형태저록
ISBN
9781523101757 152310175X
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