Guerci J.R. Cognitive radar: the knowledge-aided fully adaptive approach (Boston; London, 2010). - ОГЛАВЛЕНИЕ / CONTENTS

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ОбложкаGuerci J.R. Cognitive radar: the knowledge-aided fully adaptive approach. - Boston; London: Artech House, 2010. - 175 p.: ill. - (Artech House radar series). - Bibliogr. at the end of the chapters. - Ind.: p.169-175. - ISBN 978-1-59693-364-4
 

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Оглавление / Contents
 
Preface ......................................................... 9

Chapter 1. Introduction ........................................ 13
1.1  Why "Cognitive" Radar? .................................... 13
1.2  Functional Elements and Characteristics of a Cognitive
     Radar Architecture ........................................ 14
     1.2.1  Adaptive Transmit Capability ....................... 17
     1.2.2  Knowledge-Aided Processing ......................... 23
1.3  Book Organization ......................................... 30
References ..................................................... 31

Chapter 2. Optinnum Multi-Input Multioutput (MIMO) Radar ....... 35
2.1  Introduction .............................................. 35
2.2  Jointly Optimizing the Transmit and Receive Fimctions
     Case I: Maximizing SINR ................................... 36
     Example 2.1  Multipath Interference ....................... 42
2.3  Jointly Optimizing the Transmit and Receive Functions
     Case II: Maximizing Signal-to-Clutter ..................... 47
     Example 2.2  Sidelobe Target Suppression: "Sidelobe
     Nulling on Transmit" ...................................... 49
     Example 2.3  Optimal Pulse Shape for Maximizing SCR ....... 51
     Example 2.4  Optimum Space-Time MIMO Processing for
        Clutter Suppression in Airborne MTI Radar .............. 54
2.4  Optimum MIMO Target Identification ........................ 62
     Example 2.5 Two-Target Identification Example ............. 64
     Example 2.6  Multitarget Identification Example ........... 69
2.5  Constrained Optimum MIMO Radar ............................ 69
     Example 2.7 PrenuUing on Transmit ......................... 71
     Example 2.8 Relaxed Projection Example .................... 74
     Example 2.9 Nonlinear FM (NLFM) to Achieve Constant
        Modulus ................................................ 77
     Example 2.10  Matched Subspace Example .................... 84
Appendix 2.A: Infinite Duration (Steady State) Case ............ 86
References ..................................................... 87

Chapter 3. Adaptive Multi-Input Multioutput (MIMO) Radar ....... 89
3.1  Intiroduction ............................................. 89
3.2  Transmit-Independent Charmel Estimation ................... 90
     Example 3.1  Adaptive Multipath Interference
        Mitigation ............................................. 91
3.3  Dynamic MIMO Calibration .................................. 93
     Example 3.2 MIMO Cohere-on-Target ......................... 93
3.4  Transmit-Dependent Charmel Estimation ..................... 96
     Example 3.3  STAP-on-Transmit (STAP-Tx) Example ........... 97
     Example 3.4  DDMA MIMO STAP Clutter Mitigation Example 
        for GMTI Radar ........................................ 102
3.5  Theoretical Performance Boimds of the DDMA MIMO STAP 
     Approach ................................................. 104
References .................................................... 110

Chapter 4. Introduction to Knowledge-Aided (KA) Adaptive
Radar ......................................................... 113
4.1  The Need for KA Radar .................................... 113
4.2  Introduction to KA Radar: Back to "Bayes-ics" ............ 118
     4.2.1  Indirect KA Radar: Intelligent Training and
            Filter Selection .................................. 121
     Example 4.1   Intelligent Filter Selection: Matching
        the Adaptive DoFs (ADoFs) to the Available Training
        Data .................................................. 123
     4.2.2  Direct KA Radar: Bayesian Filtering and Data
            Prewhitening ...................................... 127
     Example 4.2  Using Past Observations as a Prior
        Knowledge Source ...................................... 131
4.3  Real-Time KA Radar: The DARPA KASSPER Project ............ 135
     4.3.1  Solution: Look-Ahead Scheduling ................... 137
     Example 4.3  Balancing Throughput in a KASSPER
        HPEC Architecture ..................................... 141
     4.3.2  Examples of a KA Architectures Developed by
            the DARPA/AFRL KASSPER Project .................... 144
4.4  KA Radar Epilogue ........................................ 153
References .................................................... 154

Chapter 5. Putting It All Together ............................ 159
5.1  Cognitive Radar: The Fully Adaptive Knowledge-Aided
     Approach ................................................. 159
     Example 5.1  A Cognitive Radar Architecture .............. 160
     5.1.1  Informal Operational Narrative for a GMTI Radar ... 162
5.2  Areas for Future Research and Development ................ 164
References .................................................... 165

About the Author .............................................. 167
Index ......................................................... 169


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