Simultaneous feature-based identification and track fusion

A tactical pilot typically experiences difficulty in maintaining accurate identification on multiple-interacting targets in the presence of clutter. We propose a multilevel feature-based association (MFBA) algorithm to aid a pilot in a dynamic multi-target environment. We investigate MFBA for an air-to-ground scenario in which a plane, equipped with a high-range resolution radar sensor, processes kinematic and target features at different levels, and fuses these features to simultaneously track and identify targets.