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Robust Interacting Multiple Model Filter Based on Student's t-Distribution for Heavy-Tailed Measurement Noises
2019
Sensors
In maneuvering target tracking applications, the performance of the traditional interacting multiple model (IMM) filter deteriorates seriously under heavy-tailed measurement noises which are induced by outliers. A robust IMM filter utilizing Student's t-distribution is proposed to handle the heavy-tailed measurement noises in this paper. The measurement noises are treated as Student's t-distribution, whose degrees of freedom (dof) and scale matrix are assumed to be governed by gamma and inverse
doi:10.3390/s19224830
fatcat:zd3arjcajzgebmdxvyor64t7n4