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Temporal Decomposition for Online Multisensor-Multitarget Tracking

In this work we develop a novel temporal decomposition scheme for solving data association in multisensormultitarget tracking problems. Given a set of noisy measurements from any number of sensors the data association problem is to determine which measurements originate from which targets. The problem is traditionally posed as an N -dimensional assignment problem, which is NP-hard for N ≥ 3 dimensions. Our approach limits the dimensionality of the assignment problem and scales well to all problem instances. The formulation is implemented as an online algorithm and results are compared to existing algorithms.