Premium
An EM‐based adaptive multiple target tracking filter
Author(s) -
Jeong Hong,
Park JeongHo
Publication year - 2002
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.661
Subject(s) - kalman filter , tracking (education) , radar tracker , computer science , tracking system , position (finance) , filter (signal processing) , radar , control theory (sociology) , extended kalman filter , computer vision , artificial intelligence , algorithm , telecommunications , psychology , pedagogy , control (management) , finance , economics
Tracking targets of interest is one of the major research areas in radar surveillance systems. We formulate the problem as incomplete data estimation and apply EM to the MAP estimate. The resulting filter has a recursive structure analogous to the Kalman filter. The advantage is that the measurement‐update deals with multiple measurements in parallel and the parameter‐update estimates the system parameters on the fly. Experiments tracking separate targets in parallel show that tracking maintenance ratio of the proposed system is better than that of NNF and RMS position error is smaller than that of PDAF. Also, the system parameters are correctly obtained even from incorrect initial values. Copyright © 2001 John Wiley & Sons, Ltd.