Interactive-Multiple-Model Algorithm Based on Minimax Particle Filtering

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Abstract
In this paper, we propose a new approach for tracking a target maneuvering based on the multiple-constant-turns model. Usually, the interactive-multiple-model (IMM) algorithm based on the extended Kalman filter (EKF) is employed for this problem with successful tracking performance. Recently proposed IMM-particle filter (PF) shows outperforming results for this nonlinear problem. The proposed approach is a new framework of particle filtering (PF) that adopts the minimax strategy to standard PF. The minimax strategy results in the decreased variance of the weights of particles that provides the robustness against degeneracy phenomenon that is a common problem of generic particle filtering. In this paper, we show outperforming results by IMM-MPF over IMM-PF besides the IMM-EKF in terms of various aspects.
Funding Information
  • National Research Foundation of Korea
  • Ministry of Education (NRF-2016R1D1A1A09918304, NRF-2019R1I1A1A01058976)

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