Efficient multirate interacting multiple model particle filter(MRIMM-PF) for target tracking

Lang Hong; Michael Bakich; Jeffery R. Layne

doi:10.1117/12.665260

9 May 2006 Efficient multirate interacting multiple model particle filter (MRIMM-PF) for target tracking

Lang Hong, Michael Bakich, Jeffery R. Layne

Proceedings Volume 6229, Intelligent Computing: Theory and Applications IV; 62290S (2006) https://doi.org/10.1117/12.665260
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

In many cases, tracking ground targets can be formulated as a nonlinear filtering problem when terrain and road constraints are incorporated into system modeling and polar coordinate is used. Furthermore, when tracking ground maneuvering targets with an interacting multiple model (IMM) approach, a non-Gaussian problem exists due to an inherent mixing operation. A multirate interacting multiple model particle filter (MRIMM-PF) is presented in this paper to effectively solve the problem of nonlinear and non-Gaussian tracking, with an emphasis on computational savings.

Citation Download Citation

Lang Hong, Michael Bakich, and Jeffery R. Layne "Efficient multirate interacting multiple model particle filter (MRIMM-PF) for target tracking", Proc. SPIE 6229, Intelligent Computing: Theory and Applications IV, 62290S (9 May 2006); https://doi.org/10.1117/12.665260

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