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