A novel interacting multiple model algorithm

Authors:
HongQuan Qu;LiPing Pang;ShaoHong Li
Affiliations:
College of Information Engineering, North China University of Technology, Beijing 100144, China;School of Electronics and Information Engineering, Beihang University, Beijing 100191, China;School of Electronics and Information Engineering, Beihang University, Beijing 100191, China
Venue:
Signal Processing
Year:
2009

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Abstract

For maneuvering target tracking, the interacting multiple model (IMM) algorithm employs a fixed model set. The performance of this algorithm depends on the model set adopted. The result of using too many models is as bad as the case of too few models. Therefore, a variable structure IMM (VSIMM) was presented and applied to ground target tracking. This algorithm improves performance and reduces computational load with using auxiliary information. But it is difficult to extend the VSIMM to other scenario (for example, aerial target), where there is not auxiliary information such as a map. A novel interacting multiple model (Novel-IMM) algorithm was presented to solve the problem of model set adaptation without auxiliary information. The Novel-IMM algorithm consists of N independent IMM filters operating in parallel, and each independent IMM filter also consists of multiple sub-filters, which operate interactively. In every time index, only one IMM output of a certain model set is used; but for a long time, the algorithm will alternatively choose an output of the model set to be the optimum final output. The Novel-IMM approach was illustrated in detail with an aerial complex maneuvering target tracking example.