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Cognitive Radar: the Knowledge-Aided Fully Adaptive Approach

Guerci, J. R.
ISBN-10: 159693364X
ISBN-13: 9781596933644

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Cognitive radar (CR) refers to radar that is capable of interacting intelligently with its environment by adapting both its transmit and receive functions based on contextual awareness and expert reasoning. Chronicling the new field, this cutting-edge resource provides an accessible introduction to the theory and applications of CR, and presents a comprehensive overview of the latest developments in this emerging area.
The first book on the subject, this unique volume covers important breakthroughs in advanced radar systems, and offers new and powerful methods for combating difficult clutter environments. Professionals find details on specific algorithmic and real-time high-performance embedded computing (HPEC) architectures. This practical book is supported with numerous examples that clarify key topics, and includes more than 370 equations.
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Preface
Introduction
Why "Cognitive" Radar?
Functional Elements and Characteristics of a Cognitive Radar Architecture
Adaptive Transmit Capability
Knowledge-Aided Processing
Book Organization
References
Optimum Multi-Input Multioutput (MIMO) Radar
Introduction
Jointly Optimizing the Transmit and Receive Functions Case I: Maximizing SINR
Multipath Interference
Jointly Optimizing the Transmit and Receive Functions Case II: Maximizing Signal-to-Clutter
Sidelobe Target Suppression: "Sidelobe Nulling on Transmit"
Optimal Pulse Shape for Maximizing SCR
Optimum Space-Time MIMO Processing for Clutter Suppression in Airborne MTI Radar
Optimum MIMO Target Identification
Two-Target Identification Example
Multitarget Identification Example
Constrained Optimum MIMO Radar
Prenulling on Transmit
Relaxed Projection Example
Nonlinear FM (NLFM) to Achieve Constant Modulus
Matched Subspace Example
Infinite Duration (Steady State) Case
References
Adaptive Multi-Input Multioutput (MIMO) Radar
Introduction
Transmit-Independent Channel Estimation
Adaptive Multipath Interference Mitigation
Dynamic MIMO Calibration
MIMO Cohere-on-Target
Transmit-Dependent Channel Estimation
STAP-on-Transmit (STAP-Tx) Example
DDMA MIMO STAP Clutter Mitigation Example for GMTI Radar
Theoretical Performance Bounds of the DDMA MIMO STAP Approach
References
Introduction to Knowledge-Aided (KA) Adaptive Radar
The Need for KA Radar
Introduction to KA Radar: Back to "Bayes-ics"
Indirect KA Radar: Intelligent Training and Filter Selection
Intelligent Filter Selection: Matching the Adaptive DoFs (ADoFs) to the Available Training Data
Direct KA Radar: Bayesian Filtering and Data Prewhitening
Using Past Observations as a Prior Knowledge Source
Real-Time KA Radar: The DARPA KASSPER Project
Solution: Look-Ahead Scheduling
Balancing Throughput in a KASSPER HPEC Architecture
Examples of a KA Architectures Developed by the DARPA/AFRL KASSPER Project
KA Radar Epilogue
References
Putting It All Together
Cognitive Radar: The Fully Adaptive Knowledge-Aided Approach
A Cognitive Radar Architecture
Informal Operational Narrative for a GMTI Radar
Areas for Future Research and Development
References
About the Author
Index
J. R. Guerci earned his Ph.D. in system engineering at the Polytechnic University, New York. Dr. Guerci is deputy director, special projects office for The Defense Advanced Research Projects Agency (DARPA). A Senior Member of the IEEE and a Member of the IEEE Radar Systems Panel.

Edition: 2010
Publisher: Artech House, Incorporated
Binding: Trade Cloth
Pages: 180
Size: 6.25" wide x 9.00" long x 0.75" tall
Weight: 0.84 lbs.
Language: English

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