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UID:0-527@aerospace.technion.ac.il

DTSTART;TZID=Asia/Jerusalem:20150112T163000

DTEND;TZID=Asia/Jerusalem:20150112T173000

DTSTAMP:20230603T193312Z

URL:https://aerospace.technion.ac.il/events/state-estimation-in-systems-wi
 th-random-coefficients/

SUMMARY:State Estimation in Systems with Random Coefficients
DESCRIPTION:Lecturer:Daniel Sigalov\n Faculty:The Interdepartmental Program
  for Applied Mathematics\,\n Institute:Technion – Israel Institute of Te
 chnology\n Location:Classroom 165\, ground floor\, Library\, Aerospace Eng
 .\n Zoom: \n Abstract: \n Details: \n State estimation in dynamical system
 s with randomly switching coefficients is an important problem with a var
 iety of applications. The most commonly met problems that are formulated 
 within the random coefficients state-space approach\, are maneuvering targ
 et tracking and fault-tolerant filtering. A related class of problems is r
 eferred to as data association or data ambiguity.\nIn this family\, the es
 timation process is further complicated by the fact that the acquired data
  has uncertain origin. Typical applications include target tracking in cl
 utter and multiple target tracking.  In this talk we aim at deriving a u
 nified framework for state estimation problems under data and model uncer
 tainties. First\, we present the problem of tracking a maneuvering target
  restricted to perform a bounded number of maneuvers and show that\, despi
 te the inherent deviation from the standard Markov switching assumption u
 nderlying most state-of-the-art algorithms\, it may be reformulated and s
 olved using a generalized version of such tools. We proceed with an overv
 iew of linear minimum mean-square error (LMMSE) algorithms for state esti
 mation in systems with random coefficients. We show that the novel formul
 ation allows treatment of problems that have not been addressed in the LMM
 SE sense in the past. These include target tracking in clutter and multip
 le target tracking. Finally\, we present a general framework\, accompanie
 d by a variety of applications\, which allows a utilization of a single IM
 M-like algorithm to solve a variety of state estimation problems.  These 
 include maneuvering target tracking\, clutter and data association\, multi
 ple target tracking\, tracking of splitting targets and more. In some case
 s it will be shown that the resulting unified IMM-like filter reduces to 
 some classical algorithms such as PDA and JPDA.
CATEGORIES:Seminars
LOCATION:Classroom 165\, ground floor\, Library\, Aerospace Eng.

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