Abstract
IMM (Interacting Multiple Model) and MHT (Multiple Hypothesis Tracking) are today interesting techniques in the tracking field. Specifically, IMM is a filtering technique where r standard filters cooperate to match the true target model; MHT is a multiscan correlation logic, which defers data association until more data are available so to reduce the risk of mis-correlation. The combination of IMM and MHT promise improved tracking performance: we shall term such algorithm as IM3HT. The paper provides a theoretical formulation of this new algorithm; also, the results of performance comparison with a "classical" MHT in terms of tracking errors are included.
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