Multitarget tracking algorithm based on finite mixture models and equivalent measurement

In this paper the multitarget tracking (MTT) under a cluttered environment is considered. The proposed approach contains two steps: The first step is based on clustering algorithm of finite mixture models (FMM). The second step first obtain equivalent measurement (EQM) and then the EQM is used to estimate state of target. In fact, The first step is the parametric estimation of the FMM and the second step is the state estimation of the target. Compared with the traditional algorithm, the proposed approach has several characteristics. First, it dose not use validation gate. Second, it can deal with the uncertain number of targets, especially when the target number is large.