Joint State Estimation and System Classification Using Particle Filtering and Interacting Multiple-Model for Maneuvering Target Tracking

In this paper, the problem of joint tracking and system calcification for a maneuvering target has been investigated. The system classification could improve performance of a tracking algorithm in a majority of applications. For instance, it is very crucial to determine the class of target in caring systems like air traffic control, marine care, and air defense at any time. In contrast to the existing solutions, which consider a separate filter for each class, we propose a single particle filter to estimate the class of target leading to a considerable reduction in computation complexity. Simulation results show that the proposed algorithm can estimate the class of target efficiently.