Developing Digital RF Memories and Transceiver Technologies for Electromagnetic Warfare

Description

This book provides a comprehensive resource and thorough treatment in the latest developments of Digital RF Memory (DRFM) technology and their key role in maintaining dominance over the electromagnetic spectrum. Part I discusses the use of advanced technology to design transceivers for spectrum sensing using unmanned systems to dominate the electromagnetic spectrum. Part II uses artificial intelligence and machine learning to enable modern spectrum sensing and detection signal processing for electronic support and electronic attack. Another key contribution is examination of counter-DRFM techniques. DRFM and transceiver design details and examples are provided along with the MATLAB software allowing the reader to construct their own embedded DRFM transceivers for unmanned systems. It examines the design trade-offs in developing multiple, structured, false target synthesis DRFM architectures and aids in developing counter-DRFM techniques and distinguish false target from real ones. Written by an expert in the field, and including MATLAB(TM) design software, this is the only comprehensive book written on the subject of DRFM. Contents Preface Chapter 1 Elecromagnetic Spectrum Dominance 1.1 INTRODUCTION 1.2 THE ELECTROMAGNETIC SPECTRUM DOMAIN 1.3 THE DEVELOPING ROLE OF DIGITAL RF MEMORIES 1.4 ELECTROMAGNETIC WARFARE 1.5 AIRBORNE ASSETS AND UNMANNED SYSTEMS 1.6 ELECTROMAGNETIC MANEUVER WARFARE 1.7 COMMERCIAL TECHNOLOGIES DRIVING A DIFFERENCE 1.8 THE MULTIFUNCTION DIGITAL RF MEMORY 1.9 ELECTRONICALLY SCANNED ANTENNAS 1.10 QUANTIFYING DRFM SPECTRUM DOMINANCE 1.11 DRFM SIGNAL PROCESSING TECHNIQUES 1.12 SUMMARY Chapter 2 Digital RF Memory Receiver Architectures 2.1 DRFM ARCHITECTURES 2.2 SUPERHETERODYNE KERNELS 2.3 CHANNELIZED KERNELS 2.4 PHASE SAMPLING ARCHITECTURES 2.5 USE OF DSP AND FPGA TECHNOLOGY 2.6 GLOBAL POSITIONING SYSTEM RECEIVERS 2.7 SUMMARY Chapter 3 Designing DRFM AESA Antennas 3.1 INTRODUCTION 3.2 BEAMFORMING CONCEPTS 3.3 ACTIVE-ELEMENT ELECTRONICALLY SCANNED ARRAYS 3.4 TRANSMIT / RECEIVE TECHNOLOGIES 3.5 PREDICTING IMPACT OF BEASMFORMING ON RX SENSITIVITY 3.6 AESA NOISE FIGURE AND DYNAMIC RANGE 3.7 A LOOK TO THE FUTURE 3.8 SUMMARY Chapter 4 Choosing the CorrectWideband Receiver 4.1 AESA ANTENNA-TO-RECEIVER INTERFACE 4.2 ANALOG-TO-INFORMATION SAMPLING 4.3 COMPRESSIVE SENSING RECEIVERS 4.4 BLIND COMPRESSIVE SENSING WITHOUT A PRIORI BASISMATRIX KNOWLEDGE 4.5 BANDPASS SAMPLING CHANNELIZER 4.6 POLYPHASE ANALYSIS SYNTHESIS CHANNELIZERS 4.7 DIGITAL RECEIVER / EXCITERS 4.8 SUMMARY APPENDIX 4A: INTERPOLATION FILTER OUTPUT (SECTION 4.3.1) Chapter 5 Transceiver Design and PracticalConsiderations 5.1 MATHEMATICAL MODELS OF THE TRANSCEIVER PROCESS 5.2 RECEIVE PROCESS 5.3 BASIC DEFINITIONS 5.4 ANALOG-TO-DIGITAL CONVERSION 5.5 ADC CIRCUIT CONCEPTS 5.6 ADC NOISE FLOOR WITH WINDOWING 5.7 FFT SPECTRUM ANALYSIS 5.8 DIGITAL-TO-ANALOG CONVERSION 5.9 TRANSFER FUNCTIONS TO DETERMINE LINEARITY 5.10 TECHNICAL ISSUES AND LIMITATIONS 5.11 PHASE ANGLE SAMPLING SYSTEM: QUANTIZATION NOISE 5.12 DIGITIZATION FIGURES OF MERIT 5.13 DRFM TRANSCEIVER DESIGN CHALLENGES 5.14 SUMMARY Chapter 6 High-Performance Transceiver Technologies 6.1 COMPARATOR DESIGNS 6.2 FLASH ADC EXAMPLES 6.3 TIME-INTERLEAVING FLASH TECHNIQUES 6.4 TIME-INTERLEAVING PIPELINE TECHNIQUES 6.5 TI-SUCCESSIVE APPROXIMATION REGISTER TECHNIQUES 6.6 FIGURE OF MERIT PLOTS FOR ADCS 6.7 FINFET TRANSISTOR TECHNOLOGIES 6.8 EMBEDDED DUAL-PORT MEMORY 6.9 PRACTICAL CONSIDERATIONS FOR DACS 6.10 MACHINE LEARNING CALIBRATION TECHNOLOGY 6.11 DIRECT DIGITAL SYNTHESIS 6.12 DRFM OSCILLATORS AND PHASE NOISE 6.13 SUMMARY Chapter 7 Microwave-Photonic TransceiverTechnologies 7.1 PHOTONIC RECEIVER DIGITAL ANTENNA COMPONENTS 7.2 LASERS 7.3 DETECTORS 7.4 OPTICAL LINK AND COMPONENTS 7.5 PHOTONIC LOCAL OSCILLATOR 7.6 ELECTRO-OPTICAL MODULATORS 7.7 SIGNAL PROCESSING 7.8 PHOTONIC RF MEMORY 7.9 DESIGNING MICROWAVE-PHOTONIC ANTENNAS 7.10 PHOTONIC ANALOG-TO-DIGITAL CONVERTERS 7.11 HIGH-RESOLUTION ENCODING PROCESS FOR PHOTONIC ADCS 7.12 CONFIGURING PHOTONIC COMPRESSIVE SAMPLING SYSTEMS 7.13 DESIGNING A PHOTONIC NYQUIST FOLDING RECEIVER 7.14 DESIGN OF PHOTONICS COMPRESSIVE SAMPLING SYSTEMS 7.15 WIDEBAND SPECTRUM SENSING AND ANALYSIS 7.16 SUMMARY Chapter 8 Modern Spectral Sensing and Detection 8.1 PERSISTENT SPECTRUM SENSING 8.2 CENTRALIZED OR DECENTRALIZED EMS SENSING 8.3 DETECTION METHODS: TIME-FREQUENCY 8.4 WAVELET DECOMPOSITION USING QUADRATURE MIRRORS 8.5 QMFB TREE RECEIVER 8.6 CYCLOSTATIONARY SPECTRAL ANALYSIS 8.7 DISCRETE TIME CYCLOSTATIONARY ALGORITHMS 8.8 ATOMIC DECOMPOSITION 8.9 SUMMARY Chapter 9 Machine Learning in ElectromagneticWarfare 9.1 MODERN AI CONCEPTS FOR DISTRIBUTED SENSING 9.2 NONLINEAR CLASSIFICATION NETWORKS 9.3 PRINCIPAL COMPONENTS ANALYSIS 9.4 ARTIFICIAL INTELLIGENCE 9.5 DEEP LEARNING ARCHITECTURES AND EMW APPLICATIONS 9.6 AUTOENCODER 9.7 CONVOLUTIONAL NEURAL NETWORK 9.8 RECURRENT NEURAL NETWORKS 9.9 LONG-, SHORT-TERM MEMORY 9.10 GATED RECURRENT UNITS 9.11 BOLTZMANN MACHINE 9.12 RESTRICTED AND DEEP BOLTZMANN MACHINES 9.13 DEEP BELIEF NETWORKS 9.14 GENERATIVE ADVERSARIAL NETWORK 9.15 TRANSFER LEARNING 9.16 ADDRESSING THE SECURITY IN DRFM NETWORKS 9.17 NEUROMORPHIC COMPUTING FOR DRFMS 9.18 WIRELESS COMMUNICATIONS AND NETWORKING WITHUNMANNED AERIAL VEHICLES 9.19 SUMMARY COMMENTS Chapter 10 Electronic Attack Using Deep Learning 10.1 SPECTRUM DOMINANCE WITH UAVS AND DRFMS 10.2 JOINT ELECTROMAGNETIC SPECTRUM OPERATIONS 10.3 TYPES OF ELECTRONIC ATTACK 10.4 RANGE-DOPPLER IMAGING EMITTER: SIGNAL PROCESSING 10.5 OBSCURATION-EA AND DEEP LEARNING 10.6 DECEPTION-EA AGAINST SYNTHETIC IMAGING APERTURES 10.7 TARGET EA AND DEEP LEARNING ALGORITHMS 10.8 COUNTERTARGETING THE IMAGING SENSOR 10.9 DIGITAL SYNTHESIS FOR STRUCTURED FALSE TARGETS 10.10 PROGRAMMABLE DIGITAL IMAGE SYNTHESIZER 10.11 AI AND DRFM DIS CONOPS 10.12 DERIVING THE SEA CLUTTER COEFFICIENTS 10.13 PHASE AND GAIN COEFFICIENTS FOR SEA CLUTTER 10.14 CONCLUDING REMARKS APPENDIX 10A: OBSCURATION WAVEFORMS APPENDIX 10B: TARGET DECEPTION REPEATER ALGORITHMS Chapter 11 Counter-DRFM Methods 11.1 PULSE DIVERSITY TECHNIQUES 11.2 SIGNAL PROCESSING TECHNIQUES 11.3 CONCLUDING REMARKS APPENDIX 11: PROOF OF THE NEYMAN-PEARSON LEMMA About the Author Index