A new algorithm for the generalized multidimensional assignment problem
S. Deb, Krishna Rao Pattipati, Yaakov Bar‐Shalom, H. Tsaknakis · 2003
The authors present a fast near-optimal assignment algorithm to solve the generalized multidimensional assignment problem. Such problems arise in surveillance and tracking systems estimating the states of an unknown number of targets. The central problem in a multisensor-multitarget state estimation problem is that of data association-the problem of determining from which target, if any, a particular measurement originated. The data-association problem for tracking can be formulated as a generalized S-dimensional (S-D) assignment problem. However, the problem is NP-hard for three or more sensor scans (S>or=3). An efficient and recursive generalized S-D assignment algorithm (S>or=3) suitable for near-optimal track initiation of targets with ballistic trajectories in polynomial time is given. Complete algorithmic details and preliminary simulation results are presented.>