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
| 
