A faster data assignment algorithm for maximum likelihood-based multitarget motion tracking with bearings-only measurements Original Research Article

We have proved a new rotational sorting algorithm capable of reducing the complexity of data assignment process embedded in the maximum likelihood (ML)-based solution of a multitarget tracking problem from O(N3) of the conventional Hungarian type routines to O(N2) provided that the bearings-only measurements from an array of passive sensors are free from cluttering and missing data.