A Student's t Poisson multi-Bernoulli mixture filter in the presence of heavy-tailed noise
ZHAO Zi-wen
CHEN Hui
LIAN Feng
ZHANG Guang-hua
Abstract：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.
Keywords：random finite setmulti-target trackingStudent's t mixtureheavy-tail noisePoisson multi-Bernoulli mixture
Publication Date：2024-09-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：12( 1598-1609 )