An Adaptive Interacting Multiple Model Algorithm for Maneuvering Targets Tracking

DOI

10.2991/eeeis-17.2017.10How to use a DOI?

Keywords

Keyword: Maneuvering target tracking, IMM, CS model, Model transition probability

Abstract

Current Statistical (CS) model is a good adaptive filtering model for maneuvering target tracking. While, the performance of CS model depends on the maneuvering frequency, and becomes poor when tracking weak maneuvering targets. Firstly, the innovation of the filtering is used to reduce the dependence on the constant of maneuvering frequency. Secondly, in order to improve the performance for weak maneuvering targets, Constant Velocity (CV) model is used to compete with CS model in the framework of Interacting Multiple Model (IMM) algorithm. Thirdly, to avoid the over-competition and enhance the probability of superior model, a time-varying model transition probability function is proposed with the current measure. Simulation results show that this method greatly improves the performance for weak maneuvering targets, and the performance for strong maneuvering targets is similar to that of the CS model.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shu-Liang WANG
AU  - Da-Ping BI
AU  - Ming-Yang DU
PY  - 2017/09
DA  - 2017/09
TI  - An Adaptive Interacting Multiple Model Algorithm for Maneuvering Targets Tracking
BT  - Proceedings of the 3rd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2017)
PB  - Atlantis Press
SP  - 58
EP  - 65
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-17.2017.10
DO  - 10.2991/eeeis-17.2017.10
ID  - WANG2017/09
ER  -