Abstract
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( N 3) of the conventional Hungarian type routines to O( N 2) provided that the bearings-only measurements from an array of passive sensors are free from cluttering and missing data.
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