Target Tracking Using Probabilistic Data Association-Based Techniques with Applications to Sonar, Radar, and EO Sensors

In tracking targets with less-than-unity probability of detection in the presence of false alarms (clutter), data association - deciding which of the received multiple measurements to use to update each track - is crucial. A number of algorithms have been developed to solve this problem.