Title :
Multiple hypothesis tracking for multiple target tracking
Author :
Blackman, Samuel S.
Author_Institution :
Raytheon Co., El Segundo, CA, USA
Abstract :
Multiple hypothesis tracking (MHT) is generally accepted as the preferred method for solving the data association problem in modern multiple target tracking (MTT) systems. This paper summarizes the motivations for MHT, the basic principles behind MHT and the alternative implementations in common use. It discusses the manner in which the multiple data association hypotheses formed by MHT can be combined with multiple filter models, such as used by the interacting multiple model (IMM) method. An overview of the studies that show the advantages of MHT over the conventional single hypothesis approach is given. Important current applications and areas of future research and development for MHT are discussed.
Keywords :
Kalman filters; covariance matrices; military radar; reviews; sensor fusion; target tracking; tracking filters; Gaussian mixture; Kalman filter; alternative implementations; data association problem; global nearest neighbor; interacting multiple model method; missile defense systems; multiple filter models; multiple hypothesis tracking; multiple target tracking systems; surveillance systems; Filters; Infrared sensors; Nearest neighbor searches; Radar clutter; Radar measurements; Radar tracking; Research and development; Sensor systems; Surveillance; Target tracking;
Journal_Title :
Aerospace and Electronic Systems Magazine, IEEE
DOI :
10.1109/MAES.2004.1263228
