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EC4615 Advanced Radar

This course covers a comprehensive treatment of important state-of-the-art radar techniques. The objective of this course is to cover the fundamental concepts and methods of radar detection theory, radar estimation theory, target tracking, range-Doppler processing, space-time adaptive processing (STAP), synthetic aperture radar (SAR), inverse SAR (ISAR), and machine learning (ML) for radar.  This course primarily covers the concepts of advanced radar signal processing methods that are used in military and surveillance systems for the detection, classification, and identification of targets.

Prerequisite

EC3615 or instructor’s consent

Lecture Hours

3

Lab Hours

2

Course Learning Outcomes

  • The student shall be familiar with the advanced and emerging techniques for the transmission, reception, and processing of radar signals for defense applications. 
  • The student will understand the fundamental concepts of tomography that form the foundation of all imaging techniques in the radar domain.
  • The student will learn the essential components of synthetic aperture radar signal processing through the writing and modification of radar image processing algorithms.
  • The student will gain experience and insight into the subtle types of exquisite intelligence that can be extracted from radar data, including fine-level change detection, the extraction of terrain altitude information, and other types of target information.
  • The student will gain experience and understand the processing of autofocus algorithms through the execution of refinement of focusing algorithms of relevance for generating finely focused radar imagery of stationary scenes and challenging targets of interest.
  • The student will become familiar with the essential concepts of non-cooperative target radar signal location, which forms an integral component of electronic warfare.
  • The student will gain insight into the modalities and geometries conducive for non-cooperative target signal geolocation by executing signals intelligence algorithms for several possible scenarios.
  • The student will learn the essential components of machine learning convolutional neural networks applied to automatic and assisted target recognition in the radar imaging domain through the writing and modification of radar image processing algorithms.