Episodic Processing for Radar Image Characterization

#RADAR #Tracking #Ranging #rf #radio #aerospace
Share

Air-to-ground radar imaging via synthetic aperture radar provides an all-weather, day-night capability to deliver fine-resolution imagery at long range. Due to the unique phenomenology of RF scattering, interpretation of SAR imagery can be nuanced even for trained analysts. As radar systems have begun to explore wide-angle or even staring synthetic aperture radar, where the system dwells on a scene for a much longer period of time, the resultant data has new elements of spatial diversity that can be exploited to improve SAR image interpretability. We explore several techniques for characterizing and visualizing SAR image content based on wide-angle data. We present results with simulated and measured data sets.



  Date and Time

  Location

  Hosts

  Registration



  • Date: 24 Oct 2023
  • Time: 06:45 PM to 08:30 PM
  • All times are (UTC-04:00) Eastern Time (US & Canada)
  • Add_To_Calendar_icon Add Event to Calendar
If you are not a robot, please complete the ReCAPTCHA to display virtual attendance info.
  • Contact Event Hosts
  •  

     

  • Starts 12 September 2023 04:50 PM
  • Ends 24 October 2023 08:15 PM
  • All times are (UTC-04:00) Eastern Time (US & Canada)
  • No Admission Charge


  Speakers

Brian D. Rigling Brian D. Rigling of University Of Dayton

Topic:

Episodic Processing for Radar Image Characterization

Air-to-ground radar imaging via synthetic aperture radar provides an all-weather, day-night capability to deliver fine-resolution imagery at long range. Due to the unique phenomenology of RF scattering, interpretation of SAR imagery can be nuanced even for trained analysts. As radar systems have begun to explore wide-angle or even staring synthetic aperture radar, where the system dwells on a scene for a much longer period of time, the resultant data has new elements of spatial diversity that can be exploited to improve SAR image interpretability. We explore several techniques for characterizing and visualizing SAR image content based on wide-angle data. We present results with simulated and measured data sets.

Biography:

Brian Rigling received the B.S. degree in physics-computer science from the University of Dayton in 1998 and received the M.S. and Ph.D. degrees in electrical engineering from The Ohio State University in 2000 and 2003, respectively. From 2000 to 2004, he was a radar systems engineer for Northrop Grumman Electronic Systems in Baltimore, Maryland. In 2004, Dr. Rigling joined the Department of Electrical Engineering, Wright State University, and was promoted to associate professor in 2009, professor in 2013, department chair in 2014, and Dean of Engineering and Computer Science in 2018. In 2010, he was employed at Science Applications International Corporation as a chief scientist while on leave from Wright State University. In 2022, Dr. Rigling accepted an appointment in the Department of Electrical and Computer Engineering at the University of Dayton as a professor and the Ohio Research Scholar for Sensor Exploitation and Fusion. He has authored chapters for 4 textbooks, has authored more than 120 conference and journal papers, and has received nearly $60M in collaborative research funding in his career. Dr. Rigling served on the IEEE Radar Systems Panel 2009-2018, and was an associate editor for IEEE Transactions on Image Processing 2009-2013. He was the general chair for the 2014 IEEE Radar Conference, was awarded the 2015 IEEE Fred Nathanson Memorial Radar Award, and was elevated to IEEE Fellow in 2018.

Email:

Address:300 College Park, , Dayton, United States, 45469





Agenda

The talk will be virtual by Zoom on Oct. 24, 2023 between 7:00 PM and 8:30  PM EST. There is no fee and everybody is invited. Please use the following link to participate.

Zoom Link:

AuresTech Inc. is inviting you to a scheduled Zoom meeting.

Topic: My Meeting
Time: Oct 24, 2023 06:30 PM Eastern Time (US and Canada)

Join Zoom Meeting
https://us06web.zoom.us/j/81231685922?pwd=97Bt1r7dE7Ucax4hh8b2A1XbNYkdJe.1

Meeting ID: 812 3168 5922
Passcode: 551777

---

One tap mobile
+16468769923,,81231685922#,,,,*551777# US (New York)
+16469313860,,81231685922#,,,,*551777# US

---

Meeting ID: 812 3168 5922
Passcode: 551777

Find your local number: https://us06web.zoom.us/u/kouza195a