BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20251102T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20251203T193626Z UID:2D26EF99-1736-423D-A112-3A25B9516449 DTSTART;TZID=America/New_York:20251203T113000 DTEND;TZID=America/New_York:20251203T130000 DESCRIPTION:Abstract\n\nRadio Frequency (RF) signals are used in a multitud e of defense\, commercial\, and civilian applications\, which are critical for the safety and security of mankind. RF for radar includes the functio ns of target detection\, localization\, and tracking in the presence of in terference. In radar systems\, an RF transmitter sends out signals to illu minate a surveilled scenario for gathering information about the environme nt and the targets present based on the received radar echo. In an ideal w orld without any interfering signals\, accomplishing these tasks becomes t rivial. However\, in practice\, the radar returns at the receiver are almo st always corrupted by interfering signals. A major source of interference is reflections from ground clutter\, which are highly dependent on the si te-specific environment.\n\nTargets of interest can be obscured by these g round clutter returns\, which is a pressing problem for airborne radar see king to detect ground moving targets. Therefore\, the development of any n ew radar signal processing technique is heavily dependent on accurately mo deling the ground clutter reflections. There is a scarcity of publicly ava ilable measured data for RF applications. The measured data are expensive to collect and limited to very specific scenarios. Even when collected\, t he data are sensitive in nature and not readily available to test new algo rithms and techniques. Therefore\, most of the radar research\, developmen t\, and testing relies upon accurately modeling and simulating the data.\n \nIn this lecture\, a Green’s function impulse response (stochastic tran sfer function) approach to radar clutter modeling will be presented along with a comparison to traditional approximate statistical modeling. This al ternate approach enables high-fidelity site-specific physics-based clutter modeling to generate representative synthetic data. Various RF applicatio ns will be demonstrated using this approach along with the dissemination o f a new challenge dataset that can be downloaded to test and benchmark sta te-of-the-art cognitive radar algorithms and techniques.\n\nSpeaker(s): Dr . Gogineni\, \n\nAgenda: \n11:30 A.M. - Lunch (Free)\n\n12:00 P.M.-1:00 P. M. - Dr. Gogineni's Presentation\n\nRoom: GEM Sapphire 068A - Front desk c an help.\, The Hub\, 31 South Main Street\, Dayton\, Ohio\, United States\ , 45402 LOCATION:Room: GEM Sapphire 068A - Front desk can help.\, The Hub\, 31 Sout h Main Street\, Dayton\, Ohio\, United States\, 45402 ORGANIZER:michael.callahan.10@us.af.mil SEQUENCE:94 SUMMARY:High Fidelity RF Clutter Modeling and Simulation URL;VALUE=URI:https://events.vtools.ieee.org/m/516601 X-ALT-DESC:Description: <br /><div class="label field--label">Abstract</div >\n<div class="mx-auto break-words word-wrap prose font-serif">\n<p>Radio Frequency (RF) signals are used in a multitude of defense\, commercial\, a nd civilian applications\, which are critical for the safety and security of mankind. RF for radar includes the functions of target detection\, loca lization\, and tracking in the presence of interference. In radar systems\ , an RF transmitter sends out signals to illuminate a surveilled scenario for gathering information about the environment and the targets present ba sed on the received radar echo. In an ideal world without any interfering signals\, accomplishing these tasks becomes trivial. However\, in practice \, the radar returns at the receiver are almost always corrupted by interf ering signals. A major source of interference is reflections from ground c lutter\, which are highly dependent on the site-specific environment.&nbsp \;</p>\n<p>Targets of interest can be obscured by these ground clutter ret urns\, which is a pressing problem for airborne radar seeking to detect gr ound moving targets. Therefore\, the development of any new radar signal p rocessing technique is heavily dependent on accurately modeling the ground clutter reflections. There is a scarcity of publicly available measured d ata for RF applications. The measured data are expensive to collect and li mited to very specific scenarios. Even when collected\, the data are sensi tive in nature and not readily available to test new algorithms and techni ques. Therefore\, most of the radar research\, development\, and testing r elies upon accurately modeling and simulating the data.&nbsp\;</p>\n<p>In this lecture\, a Green&rsquo\;s function impulse response (stochastic tran sfer function) approach to radar clutter modeling will be presented along with a comparison to traditional approximate statistical modeling. This al ternate approach enables high-fidelity site-specific physics-based clutter modeling to generate representative synthetic data. Various RF applicatio ns will be demonstrated using this approach along with the dissemination o f a new challenge dataset that can be downloaded to test and benchmark sta te-of-the-art cognitive radar algorithms and techniques.</p>\n<p>&nbsp\;</ p>\n</div><br /><br />Agenda: <br /><p>11:30 A.M. - Lunch (Free)</p>\n<p>1 2:00 P.M.-1:00 P.M. - Dr. Gogineni's Presentation</p> END:VEVENT END:VCALENDAR