Cognitive Radar: 本帖最后由 bandwidth 于 2013-12-13 16:13 编辑
- Hardcover: 180 pages
- Publisher: Artech House; 1 edition (April 30, 2010)
- Language: English
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
Optimum Multi-Input Multioutput (MIMO) Radar 35
2.1 Introduction 35
2.2 Jointly Optimizing the Transmit and Receive Functions
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 Prenulling 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 Introduction 89
3.2 Transmit-Independent Channel 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 Channel 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 Bounds 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
Contents
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