Synthetic Aperture Radar

Course length:

3 Days

Cost:

$2,090.00

Course dates

Interested in attending? Have a suggestion about running this course near you?
Register your interest now

Want to run this event on-site? Enquire about running this event in-house

Description

This 3-day course provides an overview of synthetic aperture radar, a RF imaging technique.  The course will examine why there are limiting design considerations for real aperture radar for imaging, and how a synthetic aperture can overcome these limitations to create a high-resolution radar image. Stripmap and spotlight SAR as well as quadrature demodulation and dechirp-on-receive, will be compared and contrasted. Spotlight SAR technology will be compared to computerized axial tomography (CAT). Signal processing of the SAR data will be covered, including motion compensation, Range-Doppler Algorithm, polar formatting, aperture weighting (or apodization), and autofocus. Application topics will include interferometric processing of SAR data, moving targets in SAR, and the difficulty in estimating motion of targets in single-channel SAR.

The course is valuable to engineers and scientists who are entering the field or as a review for employees who want a system level overview

What You Will Learn:

  • History of synthetic aperture radar (SAR) and its current renaissance in the commercial market
  • Concepts of high-resolution imaging with radar using a synthetic aperture
  • Algorithm to “focus” the SAR image and which algorithms are associated with demodulation or dechirp
  • Techniques to improve image quality, including autofocus and aperture weighting
  • Characteristics of SAR evident in imagery, such as layover, as well as the ability to visually interpret a SAR scene
  • Applications of SAR, including interferometry and moving objects

Course Outline:

Day 1:  SAR Basics

  • Introduction to SAR
  • Linear Frequency Modulation (LFM)
  • Ranging
  • Quadrature Demoduation/Dechirp
  • The Synthetic Aperture
  • What Is Doppler in SAR?

Day 2:  Image Processing

  • Overview of Image Formation/Processing
  • Range-Doppler Algorithm
  • Omega-K
  • Polar Formatting
  • Backprojection
  • Autofocus
  • Image Quality

Day 3:  Applications

  • Polarimetry
  • Ocean Remote Sensing (Wakes, Ice, Oil)
  • Deep Learning
  • Interferometry:  Terrain, Coherent Change Detection, Earthquakes
  • Moving Objects

Instructor(s):

Dr. E. David Jansing is a Principal Remote Sensing Scientist at Johns Hopkins University Applied Physics Laboratory.  He has more than 20 years’ experience in remote sensing, including synthetic aperture radar, hyperspectral imaging, and infrared imaging.  His research focuses on gleaning actionable information from remotely sensed data, particularly through automatic target recognition techniques and machine learning.  Earned 2018 "Exceptional Online Course Design" award from Johns Hopkins University Engineering for Professional program. Patent #10235589 awarded for "Small Maritime Target Detector" using synthetic aperture radar. Author of the textbook, Introduction to Synthetic Aperture Radar: Concepts and Practice.

Scheduling:

REGISTRATION: There is no obligation or payment required to enter the Registration for an actively scheduled course. We understand that you may need approvals but please register as early as possible or contact us so we know of your interest in this course offering.

SCHEDULING: If this course is not on the current schedule of open enrollment courses and you are interested in attending this or another course as an open enrollment, please contact us at (410)956-8805 or ati@aticourses.com. Please indicate the course name, number of students who wish to participate. and a preferred time frame. ATI typically schedules open enrollment courses with a 3-5 month lead-time. To express your interest in an open enrollment course not on our current schedule, please email us at ati@aticourses.com.

For on-site pricing, you can use the request an on-site quote form, call us at (410)956-8805, or email us at ati@aticourses.com.