Introduction to Radar Using Python and MATLAB

Lee Andrew (Andy) Harrison

ISBN 10: 1630815977 / ISBN 13: 9781630815974

Published by Artech House Publishers, US, 2019

About this Item

"A well-constructed and concisely written book, incorporating a balanced combination of textual explanations and well-presented mathematical descriptions, which serves both as an introduction to many important aspects of radar but also as an extensive exercise in the usage and application of both the MATLAB and Python programming applications. It is eminently readable and understandable. I assess that it is probably most relevant to post graduate student scientists and engineers requiring a moderately detailed understanding of aspects of radar with a view to practical applications"Aerospace Magazine This comprehensive resource provides readers with the tools necessary to perform analysis of various waveforms for use in radar systems. It provides information about how to produce synthetic aperture (SAR) images by giving a tomographic formulation and implementation for SAR imaging. Tracking filter fundamentals, and each parameter associated with the filter and how each affects tracking performance are also presented. Various radar cross section measurement techniques are covered, along with waveform selection analysis through the study of the ambiguity function for each particular waveform from simple linear frequency modulation (LFM) waveforms to more complicated coded waveforms. The text includes the Python tool suite, which allows the reader to analyze and predict radar performance for various scenarios and applications. Also provided are MATLAB® scripts corresponding to the Python tools. The software includes a user-friendly graphical user interface (GUI) that provides visualizations of the concepts being covered. Users have full access to both the Python and MATLAB source code to modify for their application. With examples using the tool suite are given at the end of each chapter, this text gives readers a clear understanding of how important target scattering is in areas of target detection, target tracking, pulse integration, and target discrimination.

Seller Inventory # LU-9781630815974

Bibliographic Details

• Title: Introduction to Radar Using Python and MATLAB
• Publisher: Artech House Publishers, US
• Publication Date: 2019
• Language: English
• ISBN 10: 1630815977
• ISBN 13: 9781630815974
• Binding: Hardback
• Condition: New

About this title

Synopsis

Provides readers with the necessary tools to analyze waveforms for use in radar systems, how to produce synthetic aperture radar (SAR) images by giving a tomographic formulation and implementation, and how tracking-filter parameters affect tracking performance.

Review

Dr. Harrison has put forward a future classic. A compendium on the subject of Radar. It provides enough background in Electromagnetic Theory including propagation, reflection, and radiation to help readers in other related areas of Radar technology such as signal processing and electronics. While the book is ideal for an introductory graduate level radar class, the text can be used as a desk reference by the seasoned engineer looking for quick information. --Vince Rodriguez, Ph.D. AMTA Fellow, ACES Fellow Staff Engineer, NSI-MI Technologies, LLC.

One of the best radar references I have ever come across; an outstanding blend of both theoretical and practical applications for all levels. Each chapter provides the detailed radar theory to grow the knowledge of the reader, followed by numerous examples of real-world radar problems, solved using the provided Python and Matlab scripts. Every problem is clearly defined and solved in an easy to understand fashion. --Earl Reed Chief Systems Engineer, deciBel Research, Inc.

This book provides a broad coverage of radar topics from basic concepts to recent developments in advanced waveforms, processing techniques and RF countermeasures. Dr. Harrison provides excellent references to allow the reader to explore topics at deeper levels if desired. The questions at the end of the chapters provide great review and reinforce the understanding of the topics covered. Finally, the examples provided in both MATLAB and Python are extremely beneficial and can form the basis for a suite of tools that are useful in the practical application of the concepts. The inclusion of Python is especially helpful as it provides an open source path to leverage the example code and to visualize the results. This book is a great reference for students and practitioners alike. --Jeff Gronberg President/CEO deciBel Research, Inc