Probabilistic data association applications to data fusion
Carlo Quaranta, Giorgio Balzarotti · Optical Engineering · 2008
We describe a new approach to fusion techniques in a multiple target tracking system for an infrared search and track (IRST) system operating in the mid- and long-wave infrared (IR) bands. The use of the two IR bands allows better performances in terms of detection probability, lower number of false tracks, and shorter time for track declaration. To properly merge data from the two sensors, an enhancement of the probabilistic data association (PDA) technique is introduced in the process. A simplification of the approach used brings back the algorithm to the well-known PDA, allowing its use in conjunction with the interacting multiple model (IMM) with increased tracking ability of the system.