SIMM method based on acceleration extraction for nonlinear maneuvering target tracking

Hyun Seung Son, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


This paper presents the smart interacting multiple model (SIMM) using the concept of predicted point and maximum noise level. Maximum noise level means the largest value of the mere noises. We utilize the positional difference between measured point and predicted point as acceleration. Comparing this acceleration with the maximum noise level, we extract the acceleration to recognize the characteristics of the target. To estimate the acceleration, we propose an optional algorithm utilizing the proposed method and the Kalman filter (KF) selectively. Also, for increasing the effect of estimation, the weight given at each sub-filter of the interacting multiple model (IMM) structure is varying according to the rate of noise scale. All the procedures of the proposed algorithm can be implemented by an on-line system. Finally, an example is provided to show the effectiveness of the proposed algorithm.

Original languageEnglish
Pages (from-to)255-263
Number of pages9
JournalJournal of Electrical Engineering and Technology
Issue number2
Publication statusPublished - 2012 Mar

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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