A Student’s t Poisson multi-Bernoulli mixture filter in the presence of heavy-tailed noise

Aiming at the complex uncertainty multi-target tracking where both the motion process and observation process are disturbed by anomalous noise, this paper innovatively proposes a Student’s t mixture Poisson multi-Bernoulli mixture filter. First, the anomalous noise characteristics of the wide-area distribution are directly modeled as the Student’s t distribution. Subsequently, the probability density parameters of the Poisson point process (PPP) and the multi-Bernoulli mixture (MBM) of the Poisson multi-Bernoulli mixture filter are reasonably approximated by the Student’s t mixture form. Moreover, based on the Student’s t mixture model which approximates the multi-target probability density, the Student’s t mixture conjugate prior form of Poisson multi-Bernoulli mixture filter is derived in detail and a closed-form recursive framework of Student’s t mixture Poisson multi-Bernoulli mixture is established. Finally, the effectiveness of the proposed filtering algorithm is verified by complex multi-target tracking simulation experiments under the joint interference of process noise and measurement noise with significant trailing distribution characteristics. © 2024 South China University of Technology. All rights reserved.