Interacting multiple model methods in target tracking: A survey

E. Mazor*, A. Averbuch, Y. Bar-Shalom, J. Dayan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The Interacting Multiple Model (IMM) estimator is a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation schemes. The main feature of this algorithm is its ability to estimate the state of a dynamic system with several behavior modes which can "switch" from one to another. In particular, the IMM estimator can be a self-adjusting variable-bandwidth filter, which makes it natural for tracking maneuvering targets. The importance of this approach is that it is the best compromise available currently between complexity and performance: its computational requirements are nearly linear in the size of the problem (number of models) while its performance is almost the same as that of an algorithm with quadratic complexity. The objective of this work is to survey and put in perspective the existing IMM methods for target tracking problems. Special attention is given to the assumptions underlying each algorithm and its applicability to various situations.

Original languageEnglish
Pages (from-to)103-123
Number of pages21
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume34
Issue number1
DOIs
StatePublished - 1998

Funding

FundersFunder number
Office of Naval ResearchN00014-91-J-01950
Air Force Office of Scientific ResearchF49620-95-1-0229
University of Connecticut
Tel Aviv UniversityU157
Technion-Israel Institute of Technology

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