Special Design Topics in Digital Wideband Receivers -- Contents -- Preface -- Chapter 1 Introduction -- 1.1 Introduction -- 1.2 Purpose of This Book -- 1.3 Predicated Requirements on Receiver Performance -- 1.4 Overall EW Receiver System Operation -- 1.5 Encoder Designs -- 1.6 Approaches and References -- 1.7 Criterion of the Software Approaches -- 1.8 Organization of the Book -- References -- Chapter 2 Amplification Required in Front of the ADC -- 2.1 Introduction -- 2.2 Basic Design Criterion -- 2.3 Inputs to the Computer Program -- 2.3.1 The Inputs Related to the RF Amplifier -- 2.3.2 The Inputs Related to the ADC -- 2.3.3 The Inputs Related to the FFT Operator -- 2.4 Constants Generation -- 2.5 Equations Derived -- 2.6 Modification from the Previous Program -- 2.7 An Example -- 2.8 Nominal Sensitivity and Single Signal Dynamic Range -- 2.9 Generate Nominal Values for ADC with Different Numbers of Bits -- 2.10 Noise Floor and the Number of Bits -- 2.11 Another Example -- 2.12 Discussions of Results -- References -- Chapter 3 Dynamic Range Study Through Eigenvalue and MUSIC Methods -- 3.1 Introduction -- 3.2 Basic Definitions of Dynamic Range -- 3.3 Prerequisite for Dynamic Range Measurements -- 3.4 Single Signal Receiver Dynamic Range (SDR) -- 3.5 Dynamic Range for Receiver with Multiple Signal Capability -- 3.5.1 Single-Signal Dynamic Range -- 3.5.2 Two-Signal Third-Order Intermodulation Spur Free Dynamic Range -- 3.5.3 The Two-Signal Instantaneous Dynamic Range (IDR) -- 3.6 A Brief Discussion on the Eigenvalue Decomposition and MUSIC Methods -- 3.7 Define the Processing Procedure -- 3.8 Eigenvalues Generated with Noise and Noise Plus Signals -- 3.9 IDR Determination Through Eigenvalues -- 3.10 MUSIC Method -- 3.11 IDR Determined by Frequency Identification -- 3.12 Amplification Required in Front of the ADC.

3.13 Digitization Effect on Sensitivity as a Function of a Number of Bits -- 3.14 Digitization Effect in the Instantaneous Dynamic Range Calculation -- 3.15 Curve Fitting for the Instantaneous Dynamic Range -- 3.16 IDR Calculated with 128 Data Points and Digitization -- 3.17 Generating Very High IDR Using Long Data Length -- 3.18 Conclusion -- References -- Chapter 4 Dynamic Range Study Through Fast Fourier Transform (FFT) -- 4.1 Introduction -- 4.2 Using Simulation Approach to Find the IDR -- 4.3 Local Peaks -- 4.4 Simulation Procedure -- 4.5 Threshold Determination -- 4.6 Windows and Input Frequencies -- 4.7 IDR Results -- 4.8 IDR with a Rectangular Window -- 4.9 IDR with a Rectangular Window and Close Spaced Frequencies -- 4.10 IDR with Hamming Window -- 4.11 IDR with Blackman Window -- 4.12 IDR with a Chebyshev Window -- 4.13 IDR with a Park-McClellan Window -- 4.14 Data Length and IDR -- 4.15 Receiver Design Considerations -- 4.16 Conclusion -- 4.17 Remarks -- References -- Chapter 5 In-Phase and Quadrature Phase (IQ) Study -- 5.1 Introduction -- 5.2 Approach to Find the IQ Imbalance -- 5.3 FFT Output Imbalance Measurement Procedure -- 5.4 Results from Measuring FFT -- 5.5 Imbalance Results of FFT Outputs -- 5.6 FFT Outputs from Imbalanced Inputs -- 5.7 Windowed FFT Output Imbalance Study -- 5.8 Procedure for Finding Phase Tracking After the FFT Operation -- 5.9 Procedure for Finding an IQ Imbalance of the Hilbert Transform -- 5.10 Results of an IQ Imbalance of a Hilbert Transform with a Rectangular Window -- 5.11 Results of IQ Imbalance of the Hilbert Transform with a Blackman Window -- 5.12 IQ Imbalance of Polyphase Filters -- 5.13 IQ Imbalance from a Special Sampling Downconversion Scheme -- 5.14 Conclusion -- Reference -- Chapter 6 Signal Detection from Fast Fourier Transform (FFT) Outputs -- 6.1 Introduction.

6.2 Rayleigh Distribution Obtained from Noise Output -- 6.3 Signal-to-Noise (S/N) Distribution -- 6.4 Probability of Detection -- 6.5 Probability of Detection with a Blackman Window -- 6.6 Threshold Through the Convolution Approach -- 6.7 Threshold Obtained by a Gaussian Approximation -- 6.8 Probability of Detection with Summations -- 6.9 Threshold and Probability of Detection of the Polyphase Filter Approach -- 6.10 Summary of Sensitivity Calculations and Discussion and Final Adjustment by Considering the Number of Channels -- 6.11 Approach for Phase Comparison -- 6.12 Results from the 64-FFT Operation and Phase Comparison Aided with Amplitude Comparison -- 6.13 Create Additional Artificial Output Frequency Bins -- 6.14 Polyphase Phase Comparison Study and Basic Idea -- 6.15 Frequency Measurement Through Phase Comparison of a Polyphase Filter -- 6.16 Added Artificial Frequency Bins for the Polyphase Filter -- 6.17 Decrease Shifting Time for Polyphase Filter (Long Short Shift) -- 6.18 Comparison of the Three Approaches for Finding a Fine Frequency of a Polyphase Filter -- 6.19 Conclusions -- References -- Chapter 7 Time-Domain Detection with 1-Bit ADC -- 7.1 Introduction -- 7.2 Reduce Time Resolution and the Number of Windows -- 7.3 Conventional Time-Domain Measurement with Amplitude Information -- 7.4 Using Phase to Detect the Presence of a Signal -- 7.5 The Amplitude of the Correlation Output Is a Function of Frequency -- 7.6 Correlation Amplitude Change with a Specific Frequency and an Initial Phase -- 7.7 Moving Average Method with Different Window Lengths -- 7.8 Differential Moving Window -- 7.9 TOA and PW Calculation -- 7.10 Threshold Setting -- 7.11 Detailed Output Shape -- 7.12 Matched Window Determination -- 7.13 Ratio Method to Determine a Matched Window -- 7.14 Selecting a Short Window from the Match Window -- 7.15 TOA and PW Results.

7.16 Sensitivity Test Results -- 7.17 Conclusion -- References -- Chapter 8 Eigenvalue and Related Operations -- 8.1 Introduction -- 8.2 Input Parameters to the Eigenvalue Problem -- 8.3 Simplified Approach -- 8.4 Matrix Formulation and Noise Eigenvalue Distribution -- 8.5 One Complex Signal and Noise Eigenvalue Distributionand the Probability of Detection -- 8.6 Matrix Order Effect -- 8.7 Two Complex Input Signals -- 8.8 Data Length Effect -- 8.9 Data Length Increase Through Summations of Shorter Matrices -- 8.10 Analytic Eigenvalue Solutions of a Low-Order Matrix -- 8.11 Eigenvalues Versus Initial Phase Difference -- 8.12 Eigenvalues and Frequency Separation -- 8.13 Eigenvalue Threshold Method to Determine the Number of Signals -- 8.14 AIC and MDL Approaches -- 8.15 False Alarm Test -- 8.16 Input with One Signal and Two Signals -- 8.17 Effect of IQ Imbalance on Number of Signal Detection -- 8.18 Time-Domain Detection Using the Eigenvalue Method -- 8.19 Simulation of the Time-Domain Detection Using Eigenvalues Method -- 8.20 Conclusion -- References -- Chapter 9 Signals Close in Frequency Study and the MUSIC Method -- 9.1 Introduction -- 9.2 Input Signal Frequency Separation and Signal-to-Noise Ratio (S/N) -- 9.3 Study of the Order of the MUSIC Method for One Signal -- 9.4 Study of Order of the MUSIC Method for Two Signals -- 9.5 Using the FFT Approach to Read Signals with a Close Frequency Separation -- 9.6 Detection of the Existence of Two Signals Close in Frequency from FFT Outputs -- 9.7 Detection of the Existence of Two Signals Close in Frequency from Eigenvalues -- 9.8 Frequency Identification with Close Frequency Separation -- 9.9 Conventional MUSIC Method -- 9.10 Low-Order MUSIC Method -- 9.11 Results from the Low-Order MUSIC Method -- 9.12 Frequency Selection for MUSIC Method -- 9.13 Conclusion -- Reference.

Chapter 10 Digital Instantaneous Frequency Measurement (IFM) Receiver -- 10.1 Introduction -- 10.2 Basic Concept of an Analog IFM Receiver -- 10.3 Basic Digital IFM Receiver Hardware and Concept -- 10.4 1-Bit ADC Effect -- 10.5 Number of Phase Difference Counts and Manipulations -- 10.6 Signal-to-Noise (S/N) Effect on Angle -- 10.7 Ambiguity Resolution -- 10.8 Simulation Results -- 10.9 Threshold and Confirmation -- 10.10 Performance of Two Simultaneous Signals -- 10.11 Frequency Folding -- 10.12 Time Resolution Improvement and Threshold with Hysteresis -- 10.13 Imbalance of IQ Channels -- 10.14 Hilbert Transform Converting a Real Signal to Complex -- 10.15 Special Sampling Downconversion Transform -- 10.16 Conclusion -- References -- Chapter 11 Receiver Designed Through a Conventional FFT Approach -- 11.1 Introduction -- 11.2 Requirements -- 11.3 FFT Length Selection and Frequency Resolution -- 11.4 Threshold Determined by the Probability of False Alarm Rate and the Probability of Detection -- 11.5 Threshold Adjusting -- 11.6 Frequency Reading Improvement Through Amplitude Comparison -- 11.7 Frequency Resolution on Two Signals -- 11.8 Detection of a Second Signal in a Receiver -- 11.9 PA Measurement -- 11.10 TOA and PW Measurements -- 11.11 Combine All the Information on One Input Pulse -- 11.12 Some Possible Improvements on an FFT-Based Receiver -- 11.13 Receiver Measurements -- 11.14 Summary -- References -- Chapter 12 Receiver Designed Through a Multiple FFT Operation -- 12.1 Introduction -- 12.2 Cascaded Filter Banks Through FFT Operations -- 12.3 Cascaded Filter Banks Through Polyphase Filters -- 12.4 Half Band Filter -- 12.5 Selection of FFT Lengths -- 12.6 Threshold Determination and Probability of Detection -- 12.7 Additional Detection Scheme to Improve Pulse Width Capability -- 12.8 Short Pulse -- 12.9 Long Weak Signal.

12.10 Signals Detected by Multiple Numbers of Windows.