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 multi-scan 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 promises improved tracking performance. This paper provides a theoretical formulation of a joint IMM plus MHT algorithm, which we shall term IM3HT; also, the paper includes the results of performance comparison with a ‘classical’ MHT in terms of tracking errors.