Fusion Processing That Adapts to Disparate or Degraded Sensor Data

In 1995, Streit and Luginbuhl introduced a new tracking algorithm, which offered a balance between the single frame approach of the Probabilistic Data Association Filter (PDAF) and the multiple frame approach of the Multiple Hypothesis Tracker (MHT). With single-frame tracking algorithms, only information that has been received to date is used to determine the association between tracks and measurements. These decisions are made based on available data and are not changed even when future data may indicate that the decision was incorrect. On the other hand, in multiple-frame algorithms, hard decisions are delayed until some time in the future, thus allowing the possibility that incorrect association decisions may be corrected with more data. We are proposing to use the PMHT as a composite tracker on several sensor platforms in the Ballistic Missile Defense (BMD) Benchmark. We think that this approach, along with new techniques, will improve the single integrated air picture (SIAP); reduce or eliminate redundant, spurious, and broken tracks; better maintain tracks throughout the missile flight; reduce communication loads; and deal with out-of-sequence measurements. In addition, we propose to use the PMHT in the process of target typing.