BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Adaptive time-frequency detection and filtering for imaging in str
 ongly heterogeneous background media - Tsogka\, C (University of Crete)
DTSTART:20110805T130000Z
DTEND:20110805T134500Z
UID:TALK32243@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:We consider the problem of detecting and imaging the location 
 of compactly supported reflectors embedded in strongly heterogeneous backg
 round media. Imaging in such regimes is quite challenging as the incoheren
 t wave field that is produced from reflections by the background medium ov
 erwhelms the scattered field from the object that wish to image. To detect
  the presence of a reflector in such regimes we introduce an adaptive time
 -frequency representation of the array response matrix followed by a Singu
 lar Value Decomposition (SVD). The detection is adaptive because the time 
 windows that contain the primary echoes from the reflector are not determi
 ned in advance. Their location and width is determined by searching throug
 h the time-frequency binary tree of the LCT. After detecting the presence 
 of the reflector we filter the array response matrix to retain information
  only in the time windows that have been selected. We also project the fil
 tered array response matrix to the subspace associated with the top singul
 ar value and then image using travel time migration. We show with extensiv
 e numerical simulations that this approach to detection and imaging works 
 well in heavy clutter that is calibrated using random matrix theory so as 
 to simulate regimes close to experiments. While the detection and filterin
 g algorithm that we present works well in general clutter it has been anal
 yzed theoretically only for the case of randomly layered media. \n
LOCATION:Seminar Room 1\, Newton Institute
END:VEVENT
END:VCALENDAR