BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/London BEGIN:DAYLIGHT DTSTART:20260329T020000 TZOFFSETFROM:+0000 TZOFFSETTO:+0100 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:BST END:DAYLIGHT BEGIN:STANDARD DTSTART:20251026T010000 TZOFFSETFROM:+0100 TZOFFSETTO:+0000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:GMT END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260209T164627Z UID:5065BD0B-C3B9-4525-934D-89559569B8AE DTSTART;TZID=Europe/London:20260207T143000 DTEND;TZID=Europe/London:20260207T153000 DESCRIPTION:Detection in the maritime domain requires the radar return from targets to be distinguishable from the background interference. These rad ars traditionally use non-coherent processing due to the time-varying and range-varying nature of the Doppler spectra. However\, as radar platforms fly higher and look down at steeper angles\, the sea clutter power will in crease and traditional methods will not be as effective. This talk covers several new approaches for target detection in the maritime domain. These include the use of sparse signal separation algorithms\, including diction ary learning\, two machine learning algorithms and the application of the single snapshot coherent detector. Each of these techniques is demonstrate d using either real or realistic simulated sea clutter and shows good pote ntial when compared to traditional processing methods.\n\nSpeaker(s): Luke \, \n\nRoom: Marconi Room\, Bldg: Roberts Building\, Torrington Place\, Un iversity College London\, London\, England\, United Kingdom\, WC1E 7JE\, V irtual: https://events.vtools.ieee.org/m/536559 LOCATION:Room: Marconi Room\, Bldg: Roberts Building\, Torrington Place\, U niversity College London\, London\, England\, United Kingdom\, WC1E 7JE\, Virtual: https://events.vtools.ieee.org/m/536559 ORGANIZER:m.ritchie@ucl.ac.uk SEQUENCE:39 SUMMARY:New concepts in Maritime Detection URL;VALUE=URI:https://events.vtools.ieee.org/m/536559 X-ALT-DESC:Description: <br /><p>Detection in the maritime domain requires the radar return from targets to be distinguishable from the background in terference. These radars traditionally use non-coherent processing due to the time-varying and range-varying nature of the Doppler spectra. However\ , as radar platforms fly higher and look down at steeper angles\, the sea clutter power will increase and traditional methods will not be as effecti ve. This talk covers several new approaches for target detection in the ma ritime domain. These include the use of sparse signal separation algorithm s\, including dictionary learning\, two machine learning algorithms and th e application of the single snapshot coherent detector. Each of these tech niques is demonstrated using either real or realistic simulated sea clutte r and shows good potential when compared to traditional processing methods .</p> END:VEVENT END:VCALENDAR