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Adaptive Signal Processing for Radar

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ISBN-10: 0890065861

ISBN-13: 9780890065860

Edition: 1991

Authors: Ramon Nitzberg

List price: $161.00
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Description:

Explains the particular problems of applying adaptive signal processing, used in many fields, to radar. Emphasizes antennas, thresholding (also called "constant false alarm rate processing"), and doppler processing, noting the effects that limit the technique's performance, and some of the exotic methods still being developed. Annotation copyrighted by Book News, Inc., Portland, OR
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Book details

List price: $161.00
Copyright year: 1991
Publisher: Artech House, Incorporated
Binding: Hardcover
Pages: 328
Size: 6.50" wide x 9.50" long x 1.00" tall
Weight: 1.342
Language: English

Ramon Nitzberg received his Ph.D. in Electrical Engineering from Syracuse University. Nitzberg is President of RAYN Associates in Fayetteville, New York, and worked previously as the Senior Consulting Engineer for Advanced Development Radar Engineering at General Electric, and is a member of the IEEE.

Preface
Acknowledgments
Radar Fundamentals
Introduction
Maximum Detection Range
Conceptual System Implementation
System Performance Equations
Probability of Target Detection
Data Processor Tracking Constraints
Range Ambiguity
Detection of Targets in Clutter by Doppler Processing
Delay Line Canceller
Doppler Filter Bank
Noncoherent Summing
Operational Environments
Introduction
Thermal Noise
Clutter
Receiving Antenna Characteristics
Jamming Noise
False Target Jamming (Pulse Jamming)
Combined Environments
Quantitative Environmental Considerations
Ground Clutter
Weather Clutter
Noise Jamming
Target Characteristics and Detection Probability
Nonadaptive (Conventional) Receiving Antennas
Introduction
Linear Arrays
Array Factor
Beam Steering
Sidelobe Reduction Weighting
Effect of Weighting Errors
Planar Arrays
Reflector Antennas
Sidelobe Canceller (SLC)
Introduction
Sidelobe Cancellation Concept
Residue Power Minimization
Cancellation Degradation Effects
Propagation Delay Effect on Cancellation
Channel Mismatch Effect on Jammer Cancellation
Multiple-Sidelobe Canceller (MSLC)
Introduction
MSLC Concept
Minimum Required Number of Auxiliary Antennas
Two-Jammer Cancellation Performance as a Function of Number and Spacing of Auxiliary Antennas
Two Auxiliary Antennas
Four Auxiliary Antennas
Residue Minimization
Optimum Weights Derivation
Simplified Examples of Optimum Weight Vector Performance
Thermal-Noise Environment
Single Narrowband Jammer
Multiple Orthogonal Direction Vector Jammers
Nonzero Bandwidth Jammers
Optimum Weight Vector Performance
Performance Results
Optimum MSLC Weight Vector Estimation
Introduction
Analog Implementation of the LMS Algorithm
Multiplication by Mixing and Filtering
Residue-Auxiliary Correlation
MSLC Weight Computation Using LMS Algorithm
MSLC Weight Computation Using LMS Algorithm with Hard Limiter
Weight Computation for Single Auxiliary System Using Normalized LMS Algorithm (NLMS)
Digital Implementation of the LMS Algorithms
MSLC Digital LMS Algorithm
Digital LMS Single-Auxiliary Analysis
Single-Auxiliary Analysis of Digital LMS Algorithm with Hard Limiting
Single-Auxiliary Analysis of Digital NLMS Algorithm
Additional Residue Power due to Weight Noise for Single Auxiliary Systems
LMS Algorithm
LMS Algorithm with Limiter
NLMS Algorithm
Multiple Auxiliary Antenna Algorithm Analysis
Introduction
LMS Algorithm
MSLC LMS Convergence Analysis
Eigenvector Review
Decoupled MSLC LMS Convergence Equations
LMS Algorithm Convergence Example
Additional LMS Algorithm Convergence Examples
Normalized LMS Algorithm
Preferred NLMS Algorithm Derivations
Gradient Descent Equation Solutions and NLMS
NLMS Algorithm Convergence Analysis
Multiple Antenna NLMS Convergence Analysis
Additional NLMS Algorithm Convergence Examples
LMS Algorithm Weight Noise
Thermal-Noise Environment
Jammer Environment
Detailed Analysis of LMS Weight Noise
LMS Algorithm Weight Noise Dependence on Eigenvalue Distribution
NLMS Algorithm Weight Noise
Thermal-Noise Environment
Jammers Environment
Comparison of NLMS and LMS Convergence Characteristics
Detailed Analysis of NLMS Weight Noise
Sidelobe Blanking
Fundamental Sidelobe Blanker Analysis
Output Signal-to-Interference-plus-Noise (SINR) Maximization Criterion
Introduction
SINR Maximization Criterion Derivation
Lagrangian Multiplier Derivation
Covariance Matrix Decomposition Derivation
Square Root Matrix
SINR Maximization via Square Root Matrix
Performance Example
Similarity of the Residue Minimization and SINR Maximization Criteria
Performance Examples Analysis
Thermal-Noise Environment
Single Narrowband Jammer
Additional Environments
Adaptive Array Architectures
Element-Based Partial Adaptivity
Beam-Based Architecture
Algorithms
LMS Algorithm
Direct Matrix Estimation or Sample Matrix Inversion (SMI) Algorithm
Maximum Likelihood Estimation of a Covariance Matrix for Gaussian Statistics
Computational Procedures
LMS Formulation for Non-Gaussian Statistics
Implementation Issues
SMI Performance Analysis
Constant False-Alarm Rate (CFAR) Processors
Introduction
CFAR Concept
Cell-Averaging CFAR (CACFAR)
Performance Analysis of Cell-Averaging CFAR (CACFAR) Processor
CFAR Loss of the CACFAR Technique in Homogeneous Environments
Nonhomogeneous Environments
CACFAR Performance in Mismatched Environments
Mismatched Environment Analysis
Mismatched Environment Example
Ramp CFAR Techniques Environment
Performance Analysis of Geometric Mean Normalizer
Step Function Environment CFAR Tecniques
GOCFAR Performance Analysis for Homogeneous Environments
Mulitple-Target CFAR Techniques
Multiple-Target Effect on CACFAR
Censored CACFAR Performance Analysis in Homogeneous Environments
Performance Evaluation of the Order Statistic CFAR in Homogeneous Environments
Clutter-Map CFAR
Sea and Weather Clutter CFAR Techniques
Log-Normal Clutter CFAR
Composite Clutter Model
Multiple-Carrier-Frequency CFAR Techniques
Nonfluctuating Target Analysis
Swerling 2 Target Analysis
Hierarchal CFAR Techniques
Hierarchal CFAR Analysis
Implementation Effects on CFAR Techniques
Effect of Correlated Reference Cells
Analysis of Correlated Reference Cells
Additional CFAR Loss due to Magnitude Detection
CFAR Technique Summary
Target Detection in Clutter-plus-Noise Environments
Introduction
Clutter Discriminants
Definition of Parameters for Ground and Sea Clutter
Sea Clutter
Ground Clutter
Weather Clutter
Doppler Filtering Techniques
MTI Delay Line Cancellers
Doppler Filter Banks
Optimum Doppler Filter Weights
Approximate Performance of Nonadaptive and Adaptive Doppler Weighting
Optimum Doppler Filter Weights--Equation Details
Relative Performance of Nonadaptive and Adaptive Doppler Filters
MTI Implementation Details and MTD
Combined CFAR-SMI Algorithm
Application of Modern Spectral Estimation Techniques to Doppler Processing
Introduction
Maximum Entropy Spectral Estimation
Theoretical Mismatch Loss
Estimation Loss
MEM Estimation Equations
Operations Count Implementation Considerations
Index