This book bridges the gap between theoretical signal processing and practical radar applications. It presents cutting-edge Fourier-based methods for analyzing, decomposing, and extracting information from complex radar signals that change over time and space.
Introduction to Multidimensional Nonstationary Radar Signal Analysis Using Fourier Transforms provides the first comprehensive treatment of time-frequency and multidimensional signal analysis specifically tailored for radar applications, It features proprietary algorithms for one-, two-, and multidimensional signal decomposition using advanced techniques like the windowed two-dimensional Fourier transform (W2DFT). The text includes numerous real-world radar examples, datasets, and visualization results that demonstrate practical implementation, while the accompanying MATLAB © toolbox enables immediate hands-on application. By combining classical Fourier methods with recent advances such as synchrosqueezing and adaptive decompositions, the book helps readers transform raw radar data into meaningful information about objects, motion, and environmental conditions. End of chapter exercises and questions are included to promote practical and theoretical comprehension.
This book is specifically designed for senior undergraduate and graduate students studying electrical engineering, signal processing, radar, sonar, or related fields, as well as practicing engineers, researchers, and specialists involved in radar system design, development, or analysis. The content is particularly valuable for professionals working in defense applications, civilian radar systems, and communication technologies who need to understand how mathematical concepts translate into real-world signal processing solutions.
A solutions manual is available to adopting professors.