L:OMEM-A fast filter to track maneuvering extended objects

In this work a new class of filters, called Lambda:Omicron Multiplicative Error Model (L:OMEM), is introduced with the aim to efficiently address tracking of maneuvering extended objects. In this context, two main challenges have to be tackled: (1) the tracked object moves with unknown time-varying speed and turning rate; (2) the tracked object can produce a large amount of measurements. Closed-form formulas and a novel method to reduce extended object tracking to a conventional point object tracking problem are derived, so that the novel filter results into an accurate and computationally cheap algorithm. Numerical simulations are presented to validate the effectiveness of the proposed approach, where the L:OMEM filter is compared to state-of-the-art filters for extended objects.