Knowledge based radar detection, tracking, and classification:
Gespeichert in:
| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Hoboken, NJ
Wiley
c2008
|
| Schriftenreihe: | Adaptive and learning systems for signal processing, communications, and control
|
| Schlagworte: | |
| Online-Zugang: | FRO01 TUM01 Volltext |
| Beschreibung: | "A Wiley-Interscience publication." Includes bibliographical references and index 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 |
| Beschreibung: | 1 Online-Ressource (xii, 268 p.) |
| ISBN: | 0470283149 0470283157 9780470149300 9780470283141 9780470283158 |
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| 500 | |a 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 -- | ||
| 500 | |a - 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 -- | ||
| 500 | |a - 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 -- | ||
| 500 | |a - 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 | ||
| 650 | 7 | |a TECHNOLOGY & ENGINEERING / Electrical |2 bisacsh | |
| 650 | 4 | |a Tracking radar | |
| 650 | 4 | |a Expert systems (Computer science) | |
| 650 | 4 | |a Automatic tracking | |
| 650 | 4 | |a Target acquisition | |
| 650 | 4 | |a Adaptive signal processing | |
| 650 | 4 | |a TECHNOLOGY & ENGINEERING / Electrical / bisacsh | |
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Datensatz im Suchindex
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| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
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| id | DE-604.BV040769114 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T00:33:32Z |
| institution | BVB |
| isbn | 0470283149 0470283157 9780470149300 9780470283141 9780470283158 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025747532 |
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| record_format | marc |
| series2 | Adaptive and learning systems for signal processing, communications, and control |
| spelling | Knowledge based radar detection, tracking, and classification edited by Fulvio Gini and Muralidhar Rangaswamy Hoboken, NJ Wiley c2008 1 Online-Ressource (xii, 268 p.) txt rdacontent c rdamedia cr rdacarrier Adaptive and learning systems for signal processing, communications, and control "A Wiley-Interscience publication." Includes bibliographical references and index 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 TECHNOLOGY & ENGINEERING / Electrical bisacsh Tracking radar Expert systems (Computer science) Automatic tracking Target acquisition Adaptive signal processing TECHNOLOGY & ENGINEERING / Electrical / bisacsh Expertensystem (DE-588)4113491-6 gnd rswk-swf Radar (DE-588)4176765-2 gnd rswk-swf Zielverfolgung (DE-588)4190799-1 gnd rswk-swf Radar (DE-588)4176765-2 s Zielverfolgung (DE-588)4190799-1 s Expertensystem (DE-588)4113491-6 s 1\p DE-604 Gini, Fulvio Sonstige oth Rangaswamy, Muralidhar Sonstige oth Wiley InterScience (Online service) Sonstige oth Erscheint auch als Druckausgabe 0-470-14930-2 https://onlinelibrary.wiley.com/doi/book/10.1002/9780470283158 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Knowledge based radar detection, tracking, and classification TECHNOLOGY & ENGINEERING / Electrical bisacsh Tracking radar Expert systems (Computer science) Automatic tracking Target acquisition Adaptive signal processing TECHNOLOGY & ENGINEERING / Electrical / bisacsh Expertensystem (DE-588)4113491-6 gnd Radar (DE-588)4176765-2 gnd Zielverfolgung (DE-588)4190799-1 gnd |
| subject_GND | (DE-588)4113491-6 (DE-588)4176765-2 (DE-588)4190799-1 |
| title | Knowledge based radar detection, tracking, and classification |
| title_auth | Knowledge based radar detection, tracking, and classification |
| title_exact_search | Knowledge based radar detection, tracking, and classification |
| title_full | Knowledge based radar detection, tracking, and classification edited by Fulvio Gini and Muralidhar Rangaswamy |
| title_fullStr | Knowledge based radar detection, tracking, and classification edited by Fulvio Gini and Muralidhar Rangaswamy |
| title_full_unstemmed | Knowledge based radar detection, tracking, and classification edited by Fulvio Gini and Muralidhar Rangaswamy |
| title_short | Knowledge based radar detection, tracking, and classification |
| title_sort | knowledge based radar detection tracking and classification |
| topic | TECHNOLOGY & ENGINEERING / Electrical bisacsh Tracking radar Expert systems (Computer science) Automatic tracking Target acquisition Adaptive signal processing TECHNOLOGY & ENGINEERING / Electrical / bisacsh Expertensystem (DE-588)4113491-6 gnd Radar (DE-588)4176765-2 gnd Zielverfolgung (DE-588)4190799-1 gnd |
| topic_facet | TECHNOLOGY & ENGINEERING / Electrical Tracking radar Expert systems (Computer science) Automatic tracking Target acquisition Adaptive signal processing TECHNOLOGY & ENGINEERING / Electrical / bisacsh Expertensystem Radar Zielverfolgung |
| url | https://onlinelibrary.wiley.com/doi/book/10.1002/9780470283158 |
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