IMMJPDA versus MHT and Kalman filterwith NN correlation:performance comparison
Marco de Feo, A. Graziano, R. Miglioli, Alfonso Maria Farina · IEE Proceedings - Radar Sonar and Navigation · 1997
Multitarget tracking systems in operational use today generally adopt Kalman filter (KF) techniques (coupled with a manoeuvre detector to introduce some kind of adaptivity), and nearest neighbour (NN) correlation. Today there are two new approaches to the tracking problem, namely: interacting multiple model joint probabilistic data association (IMMJPDA) and multiple hypothesis tracking (MHT) which promise improved tracking performance. The paper provides a performance comparison between these three tracking algorithms in terms of track maintenance probability and tracking errors. The NN + KF algorithm is used as reference because of its widespread use. Results show that MHT is superior to IMMJPDA and, as expected, both perform better than NN + KF; the cost of additional performance is increased, yet feasible, computing power.