The Impact of Cognition on Radar Technology
Cognitive dynamic systems are inspired by the computational capability of the brain and the viewpoint that cognition is a supreme form of computation. The key idea behind this new paradigm is to mimic the human brain as well as that of other mammals with echolocation capabilities which continuously...
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| Main Authors | , , |
|---|---|
| Format | eBook |
| Language | English |
| Published |
Stevenage
The Institution of Engineering and Technology
2018
Institution of Engineering and Technology (The IET) Institution of Engineering & Technology SciTech Publishing |
| Edition | 1 |
| Series | Electromagnetics and Radar |
| Subjects | |
| Online Access | Get full text |
| ISBN | 9781785615801 1785615807 |
| DOI | 10.1049/SBRA520E |
Cover
Table of Contents:
- Chapter 1: Introduction to cognitive radar with an industrial point of view -- Chapter 2: Cognitive radar inspired by the brain -- Chapter 3: Cognitive radar and its application to CFAR detection and receiver adaptation -- Chapter 4: Cognitive radar waveform design for spectral compatibility -- Chapter 5: Cognitive optimization of the transmitter-receiver pair -- Chapter 6: Cognitive control theory with an application -- Chapter 7: Cognition in radar target tracking -- Chapter 8: Anticipative target tracking with related study cases -- Chapter 9: An overview on the exploitation of cognition in MIMO radar, electronic warfare, and synthetic aperture radar -- Chapter 10: A cross-disciplinary overview with potential application and examples for cognitive radar
- Title Page Notation Table of Content 1. Introduction to Cognitive Radar with an Industrial Point of View 2. Cognitive Radar Inspired by the Brain 3. Cognitive Radar and its Application to CFAR Detection and Receiver Adaptation 4. Cognitive Radar Waveform Design for Spectral Compatibility 5. Cognitive Optimization of the Transmitter-Receiver Pair 6. Cognitive Control Theory with an Application 7. Cognition in Radar Target Tracking 8. Anticipative Target Tracking with Related Study Cases 9. An Overview on the Exploitation of Cognition in MIMO Radar, Electronic Warfare, and Synthetic Aperture Radar 10. A Cross-Disciplinary Overview with Potential Application and Examples for Cognitive Radar Index Color Plates
- 2.10.2 Tracking accuracy -- 2.11 Experimental results: practical considerations -- 2.12 Conclusion -- References -- 3. Cognitive radar and its application to CFAR detection and receiver adaptation - A. De Maio, A. Farina, A. Aubry, V. Carotenuto, and L. Pallotta -- 3.1 Introduction -- 3.2 Existing examples of cognitive properties in modern radars -- 3.3 Cognitive CFAR-processing techniques -- 3.4 Exploiting multiple a priori spectral models for detection -- 3.5 Selected reference list on cognitive radar -- 3.6 Conclusion -- References -- 4. Cognitive radar waveform design for spectral compatibility - A. De Maio, A. Farina, A. Aubry, V. Carotenuto, and L. Pallotta -- 4.1 Introduction -- 4.2 System and problem formulation -- 4.2.1 System model -- 4.2.2 Code design optimization formulation -- 4.2.3 Cognitive spectrum awareness -- 4.3 Solution algorithm and performance analysis -- 4.3.1 Local design solution technique -- 4.4 Conclusion -- Appendix A -- A.1 Waveform design algorithm for global interference requirements -- A.2 Waveform design algorithm for local interference requirements -- References -- 5. Cognitive optimization of the transmitter-receiver pair - A. De Maio, A. Farina, A. Aubry, V. Carotenuto, and L. Pallotta -- 5.1 Introduction -- 5.2 System model and problem formulation -- 5.2.1 System model -- 5.2.2 The role of cognition for environmental awareness -- 5.2.3 Code and receive filter bank optimization problem formulation -- 5.3 Joint transmit receive design: solution-technique and analysis -- 5.3.1 Performance analysis -- 5.4 Conclusion -- Appendix A -- Alternating optimization procedure to jointly design transmit signal and receive filter bank -- A.1 Filter bank optimization: solution to problem Pw (n) -- A.2 Radar code optimization: solution to problem Ps (n) -- A.3 Transmit-receive system design: optimization procedure -- References
- Intro -- Content -- Foreword -- Acknowledgments -- Notation -- About the Editors -- 1. Introduction to cognitive radar with an industrial point of view - A. Farina -- 1.1 Introduction -- 1.2 Why cognition in radar? The role of human operators and of a computer-based radar task scheduler -- 1.2.1 Use of the phased-array antenna in radar systems -- 1.2.2 Use of variable dwell time -- 1.2.3 Use of variable data rate -- 1.2.4 The system manager -- 1.3 To what extent can today's phased-array radars be considered cognitive? -- 1.4 What's next -- 1.5 Operational requirements -- 1.6 Enabling key technologies: just a taste -- 1.7 Adaptivity and brain -- 1.7.1 Brain… few basic notions -- 1.8 Brain inspired radar design -- 1.9 Conclusion -- Acknowledgments -- References -- 2. Cognitive radar inspired by the brain - Simon Haykin, Yanbo Xue, and Peyman Setoodeh -- 2.1 Introduction -- 2.2 Fuster's paradigm of cognition -- 2.3 Engineering perspective of cognition -- 2.4 Perception-action cycle -- 2.4.1 Bayesian filtering for optimal perception in the receiver -- 2.4.2 Shannon's entropy vs. Fisher information -- 2.4.3 Posterior Cramér-Rao lower bound -- 2.4.4 Sensitivity analysis -- 2.4.5 Dynamic programming for control in the transmitter -- 2.5 Memory -- 2.5.1 Perceptual memory -- 2.5.2 Executive memory -- 2.5.3 Working memory -- 2.6 Attention -- 2.7 Intelligence -- 2.8 Cyclic-directed information flow -- 2.8.1 Perceptual pathway -- 2.8.2 Executive pathway -- 2.8.3 How can we build on the directed information-flow graph to better understand the role of memory in cognition? -- 2.9 Experimental groundwork -- 2.9.1 State-space model -- 2.9.2 Construction of the two libraries -- 2.9.3 Performance metric -- 2.9.4 Track initialization -- 2.9.5 Memory -- 2.10 Experimental results: theoretical considerations -- 2.10.1 Posterior Cramér-Rao lower bound
- 9. An overview on the exploitation of cognition in MIMO radar, electronic warfare, and synthetic aperture radar - A. Aubry, V. Carotenuto, A. De Maio, A. Farina, G. Fornaro, L. Pallotta, and A. Pauciullo -- 9.1 Introduction -- 9.2 Cognitive MIMO radar beampattern shaping -- 9.3 Cognition in EW systems -- 9.4 Advanced concepts in SAR: exploitation of cognition -- 9.4.1 3D localization and monitoring of displacements with interferometry -- 9.4.2 SAR tomography and complex domain analysis of the scattering in multibaseline SAR -- 9.4.3 Knowledge-based and cognitive concepts in SAR -- 9.5 Conclusion -- References -- 10. A cross-disciplinary overview with potential application and examples for cognitive radar - A. Farina -- 10.1 Introduction -- 10.2 From information to intelligence…to exploit in cognitive radar -- 10.2.1 Birth certificate of the information age: the Annus Mirabilis 1948 -- 10.2.2 Path forward to intelligence theory: perhaps! -- 10.3 Modeling everything with the new science of network -- 10.3.1 Some mathematical properties of networks -- 10.4 Bioinspired collective processing -- 10.4.1 Potential applications to cognitive radar -- 10.5 Mirror neurons: one of the most exciting events in neuroscience. Does it matter to cognitive radar? -- 10.5.1 Who discovered the mirror neuron phenomenon? -- 10.5.2 Potential impact of research on adaptive radar signal processing -- 10.6 Additional recent researchers on neurosciences -- 10.7 Memristors: the missing fourth element of circuits -- 10.7.1 Potential modeling of synapse and axon via memristors -- 10.8 The cybersecurity issue of a radar network -- 10.9 Conclusion -- Acknowledgments -- References -- Index
- 6. Cognitive control theory with an application - Mehdi Fatemi and Simon Haykin -- 6.1 Introduction -- 6.2 The two-state model -- 6.3 Formalism of the learning process in cognitive control -- 6.4 Cognitive-control-learning algorithm viewed as a special case of Bellman's dynamic programming -- 6.5 Optimality vs. convergence-rate in online implementation -- 6.6 Formalism of the planning process in cognitive control -- 6.6.1 Predicting the entropic reward in a Gaussian environment -- 6.7 Structural composition of the cognitive controller -- 6.8 Computational experiment: cognitive-tracking radar -- 6.8.1 Scenario 1: the impact of planning on cognitive control -- 6.8.2 Scenario 2: comparison of learning curves of three different cognitive controllers -- 6.9 Conclusion -- 6.9.1 Cognitive processing of information -- 6.9.2 Linearity, convergence, and optimality -- 6.9.3 Engineering application -- Appendix A -- References -- 7. Cognition in radar target tracking - A. De Maio, A. Farina, A. Aubry, V. Carotenuto, and L. Pallotta -- 7.1 Introduction -- 7.2 Cognitive multitarget tracking system -- 7.2.1 General architecture of the tracking filter -- 7.2.2 Cognitive tracker architecture -- 7.3 Waveform selection for target tracking -- 7.3.1 Waveform scheduling strategy -- 7.3.2 Case study -- 7.4 Conclusion -- References -- 8. Anticipative target tracking with related study cases - A. Farina -- 8.1 Introduction -- 8.1.1 Anticipative target tracking -- 8.1.2 The case of MH370 -- 8.2 Coordination of fore-active control and optimal guidance law for an interceptor study case -- 8.2.1 List of symbols -- 8.2.2 Introduction -- 8.2.3 Theoretical framework -- 8.2.4 Case study -- 8.2.5 Simulation results -- 8.2.6 Discussion -- 8.3 Conclusion -- References