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UID:0-516@aerospace.technion.ac.il

DTSTART;TZID=Asia/Jerusalem:20150624T163000

DTEND;TZID=Asia/Jerusalem:20150624T173000

DTSTAMP:20230603T192746Z

URL:https://aerospace.technion.ac.il/events/tracking-in-the-presence-of-fi
 eld-of-view-constraints-using-probabilistic-data-association-2/

SUMMARY:Tracking in the Presence of Field-of-View Constraints Using Probabi
 listic Data Association
DESCRIPTION:Lecturer:Matan Yeger\n Faculty:Department of Aerospace Engineer
 ing\n Institute:Technion – Israel Institute of Technology\n Location:Cla
 ssroom 165\, ground floor\, Library\, Aerospace Eng.\n Zoom: \n Abstract: 
 \n Details: \n Modern tracking systems are required to estimate the distri
 bution of targets in a surveyed scene while coping with a variety of uncer
 tainties\, such as unknown number of targets\, unknown target motion model
 s\, missed detections and clutter (false measurements). An even more chall
 enging tracking scenario may occur when trying to track targets in a scene
  with Field-of-View (FOV) constraints. Such situations may arise in urban 
 environments including man-made occlusions (e.g.\, buildings)\, or in envi
 ronments involving topographic constraints (e.g.\, mountains). In such sit
 uations the tracking system needs to reason about information not readily 
 accessible\, when the target resides in unobserved regions of the environm
 ent.\n We address the problem of tracking a single\, non-maneuvering targ
 et\, moving through a scene containing unobserved regions that are a prior
 i known to the tracker. A modified Probabilistic Data Association (PDA) fi
 lter is developed\, that can take into account unobserved regions\, in add
 ition to target originated measurements\, missed detections\, and clutter.
  The modification is based on a "negative" information concept\, whereby e
 xpected but actually missing measurements in a scene containing unobserved
  regions may be regarded as useful information that can be exploited by th
 e tracking system. In order to use this kind of information it is formulat
 ed as a fictitious measurement that embodies the essence of the "negative"
  information. The fictitious measurement\, and its associated measurement 
 noise covariance\, are formulated based on the hidden region’s geometry.
  This measurement is used to update the target estimated state and error c
 ovariance by using a regular Kalman filter approach within the standard PD
 A framework.\n The performance of the modified PDA filter is studied via 
 numerical simulations. The simulations demonstrate track continuity when t
 he target resides in occluded regions\, with a controlled growth of the as
 sociated error covariance\, thus facilitating robust tracking when the tar
 get becomes detectable again.
CATEGORIES:Seminars
LOCATION:Classroom 165\, ground floor\, Library\, Aerospace Eng.

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DTSTART:20150327T030000

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