Coverart for item
The Resource Knowledge based radar detection, tracking, and classification, edited by Fulvio Gini and Muralidhar Rangaswamy, (electronic resource)

Knowledge based radar detection, tracking, and classification, edited by Fulvio Gini and Muralidhar Rangaswamy, (electronic resource)

Label
Knowledge based radar detection, tracking, and classification
Title
Knowledge based radar detection, tracking, and classification
Statement of responsibility
edited by Fulvio Gini and Muralidhar Rangaswamy
Creator
Contributor
Subject
Language
eng
Member of
http://library.link/vocab/creatorName
Gini, Fulvio
Dewey number
621.389/28
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Rangaswamy, Muralidhar
  • Wiley InterScience (Online service)
Series statement
Adaptive and learning systems for signal processing, communications, and control
http://library.link/vocab/subjectName
  • Tracking radar
  • Expert systems (Computer science)
  • Automatic tracking
  • Target acquisition
  • Adaptive signal processing
Label
Knowledge based radar detection, tracking, and classification, edited by Fulvio Gini and Muralidhar Rangaswamy, (electronic resource)
Instantiates
Publication
Note
"A Wiley-Interscience publication."
Bibliography note
Includes bibliographical references and index
Color
multicolored
Contents
Cover -- Copyright -- Contents -- Contributors -- 1 Introduction -- 1.1 Organization of the Book -- Acknowledgments -- References -- 2 Cognitive Radar -- 2.1 Introduction -- 2.2 Cognitive Radar Signal-Processing Cycle -- 2.3 Radar-Scene Analysis -- 2.3.1 Statistical Modeling of Statistical Representation of Clutter- and Target-Related Information -- 2.4 Bayesian Target Tracking -- 2.4.1 One-Step Tracking Prediction -- 2.4.2 Tracking Filter -- 2.4.3 Tracking Smoother -- 2.4.4 Experimental Results: Case Study of Small Target in Sea Clutter -- 2.4.5 Practical Implications of the Bayesian Target Tracker -- 2.5 Adaptive Radar Illumination -- 2.5.1 Simulation Experiments in Support of Adjustable Frequency Modulation -- 2.6 Echo-Location in Bats -- 2.7 Discussion -- 2.7.1 Learning -- 2.7.2 Applications -- Acknowledgments -- References -- 3 Knowledge-Based Radar Signal and Data Processing: A Tutorial Overview -- 3.1 Radar Evolution -- 3.2 Taxonomy of Radar -- 3.3 Signal Processing -- 3.4 Data Processing -- 3.5 Introduction to Artificial Intelligence -- 3.5.1 Why Robotics and Knowledge-Based Systems? -- 3.5.2 Knowledge Base Systems (KBS) -- 3.5.3 Semantic Web Technologies -- 3.6 A Global View and KB Algorithms -- 3.6.1 An Airborne Autonomous Intelligent Radar System (AIRS) -- 3.6.2 Filtering, Detection, and Tracking Algorithms and KB Processing -- 3.7 Future work -- 3.7.1 Target Matched Illumination -- 3.7.2 Spectral Interpolation -- 3.7.3 Bistatic Radar and Passive Coherent Location -- 3.7.4 Synthetic Aperture Radar -- 3.7.5 Resource Allocation in a Multifunction Phased Array Radar -- 3.7.6 Waveform Diversity and Sensor Geometry -- Acknowledgments -- References -- 4 An Overview of Knowledge-Aided Adaptive Radar at DARPA and Beyond -- 4.1 Introduction -- 4.1.1 Background on STAP -- 4.1.2 Examples of Real-World Clutter -- 4.2 Knowledge-Aided STAP (KA-STAP) -- 4.2.1 Knowledge-Aided STAP: Back to "Bayes-ics" -- 4.3 Real-Time KA-STAP: The DARPA KASSPER Program -- 4.3.1 Obstacles to Real-Time KA-STAP -- 4.3.2 Solution: Look-Ahead Scheduling -- 4.4 Applying KA Processing to the Adaptive MIMO Radar Problem -- 4.5 The Future: Next-Generation Intelligent Adaptive Sensors -- References -- 5 Space-Time Adaptive Processing for Airborne Radar: A Knowledge-Based Perspective -- 5.1 Introduction -- 5.2 Problem Statement -- 5.3 Low Computation Load Algorithms -- 5.3.1 Joint Domain Localized Processing -- 5.3.2 Parametric Adaptive Matched Filter -- 5.3.3 Multistage Wiener Filter -- 5.4 Issues of Data Support -- 5.4.1 Nonhomogeneity Detection -- 5.4.2 Direct Data Domain Methods -- 5.5 Knowledge-Aided Approaches -- 5.5.1 A Preliminary Knowledge-Based Processor -- 5.5.2 Numerical Example -- 5.5.3 A Long-Term View -- 5.6 Conclusions -- References -- 6 CFAR Knowledge-Aided Radar Detection and its Demonstration Using Measured Airborne Data -- 6.1 Introduction -- 6.2 Problem Formulation and Design Issues -- 6.3 KA Data Selector -- 6.4 2S-DSP Data Selection Procedure -- 6.4.1 Two-Step Data Selection Procedure (2S-DSP) -- 6.5 RP-ANMF Detector -- 6.6 Performance Analysis -- 6.7 Conclusions -- References -- Appendix 6A: Registration Geometry -- 7 STAP via Knowledge-Aided Covariance Estimation and the FRACTA Meta-Algorithm
Control code
ocn264714652
Dimensions
unknown
Extent
1 online resource (xii, 268 pages)
Form of item
online
Isbn
9780470283158
Note
Wiley
Other control number
10.1002/9780470283158
Other physical details
illustrations (some color)
Specific material designation
remote
System control number
(OCoLC)264714652
Label
Knowledge based radar detection, tracking, and classification, edited by Fulvio Gini and Muralidhar Rangaswamy, (electronic resource)
Publication
Note
"A Wiley-Interscience publication."
Bibliography note
Includes bibliographical references and index
Color
multicolored
Contents
Cover -- Copyright -- Contents -- Contributors -- 1 Introduction -- 1.1 Organization of the Book -- Acknowledgments -- References -- 2 Cognitive Radar -- 2.1 Introduction -- 2.2 Cognitive Radar Signal-Processing Cycle -- 2.3 Radar-Scene Analysis -- 2.3.1 Statistical Modeling of Statistical Representation of Clutter- and Target-Related Information -- 2.4 Bayesian Target Tracking -- 2.4.1 One-Step Tracking Prediction -- 2.4.2 Tracking Filter -- 2.4.3 Tracking Smoother -- 2.4.4 Experimental Results: Case Study of Small Target in Sea Clutter -- 2.4.5 Practical Implications of the Bayesian Target Tracker -- 2.5 Adaptive Radar Illumination -- 2.5.1 Simulation Experiments in Support of Adjustable Frequency Modulation -- 2.6 Echo-Location in Bats -- 2.7 Discussion -- 2.7.1 Learning -- 2.7.2 Applications -- Acknowledgments -- References -- 3 Knowledge-Based Radar Signal and Data Processing: A Tutorial Overview -- 3.1 Radar Evolution -- 3.2 Taxonomy of Radar -- 3.3 Signal Processing -- 3.4 Data Processing -- 3.5 Introduction to Artificial Intelligence -- 3.5.1 Why Robotics and Knowledge-Based Systems? -- 3.5.2 Knowledge Base Systems (KBS) -- 3.5.3 Semantic Web Technologies -- 3.6 A Global View and KB Algorithms -- 3.6.1 An Airborne Autonomous Intelligent Radar System (AIRS) -- 3.6.2 Filtering, Detection, and Tracking Algorithms and KB Processing -- 3.7 Future work -- 3.7.1 Target Matched Illumination -- 3.7.2 Spectral Interpolation -- 3.7.3 Bistatic Radar and Passive Coherent Location -- 3.7.4 Synthetic Aperture Radar -- 3.7.5 Resource Allocation in a Multifunction Phased Array Radar -- 3.7.6 Waveform Diversity and Sensor Geometry -- Acknowledgments -- References -- 4 An Overview of Knowledge-Aided Adaptive Radar at DARPA and Beyond -- 4.1 Introduction -- 4.1.1 Background on STAP -- 4.1.2 Examples of Real-World Clutter -- 4.2 Knowledge-Aided STAP (KA-STAP) -- 4.2.1 Knowledge-Aided STAP: Back to "Bayes-ics" -- 4.3 Real-Time KA-STAP: The DARPA KASSPER Program -- 4.3.1 Obstacles to Real-Time KA-STAP -- 4.3.2 Solution: Look-Ahead Scheduling -- 4.4 Applying KA Processing to the Adaptive MIMO Radar Problem -- 4.5 The Future: Next-Generation Intelligent Adaptive Sensors -- References -- 5 Space-Time Adaptive Processing for Airborne Radar: A Knowledge-Based Perspective -- 5.1 Introduction -- 5.2 Problem Statement -- 5.3 Low Computation Load Algorithms -- 5.3.1 Joint Domain Localized Processing -- 5.3.2 Parametric Adaptive Matched Filter -- 5.3.3 Multistage Wiener Filter -- 5.4 Issues of Data Support -- 5.4.1 Nonhomogeneity Detection -- 5.4.2 Direct Data Domain Methods -- 5.5 Knowledge-Aided Approaches -- 5.5.1 A Preliminary Knowledge-Based Processor -- 5.5.2 Numerical Example -- 5.5.3 A Long-Term View -- 5.6 Conclusions -- References -- 6 CFAR Knowledge-Aided Radar Detection and its Demonstration Using Measured Airborne Data -- 6.1 Introduction -- 6.2 Problem Formulation and Design Issues -- 6.3 KA Data Selector -- 6.4 2S-DSP Data Selection Procedure -- 6.4.1 Two-Step Data Selection Procedure (2S-DSP) -- 6.5 RP-ANMF Detector -- 6.6 Performance Analysis -- 6.7 Conclusions -- References -- Appendix 6A: Registration Geometry -- 7 STAP via Knowledge-Aided Covariance Estimation and the FRACTA Meta-Algorithm
Control code
ocn264714652
Dimensions
unknown
Extent
1 online resource (xii, 268 pages)
Form of item
online
Isbn
9780470283158
Note
Wiley
Other control number
10.1002/9780470283158
Other physical details
illustrations (some color)
Specific material designation
remote
System control number
(OCoLC)264714652

Library Locations

    • InternetBorrow it
      Albany, Auckland, 0632, NZ
Processing Feedback ...