Interacting algorithm is widely used in multi-model target tracking, but it is rarely used in multi-system target tracking. In this paper, the interacting idea is used as a reference, and an interacting multi-system tracking algorithm is proposed. The direct interaction between systems is finished based on their former state estimation. Then system probabilities are updated using innovation and its covariance from the parallel filters. Finally, weighted fusing results are achieved on the updated probabilities. The simulation result of tracking a maneuvering target shows that system probability can be adjusted based on its performance immediately, and the tracking performance can be improved effectively.
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