A new IMM interacting approach for unequal dimension states for multitarget tracking in cluttered environments

Citations

SCOPUS

1

초록

Since it is unknown in advance whether the target is maneuvering in practical target tracking environments, multiple model tracking techniques are introduced by applying various target dynamic models. Among the multiple model tracking techniques, interacting multiple model (IMM) method has shown excellent performance with low complexity due to the interaction process of each state of mode. When various dynamic models are designed, the dimension of each state may be unequal, which may cause biased estimate. To deal with this problem, mode interacting approaches to two dynamic models of unequal dimensions have been studied in other literatures. Here, a new interacting approach for the case of three dynamic models with unequal dimensions is proposed to reduce the bias in the extra state estimates of the higher dimensional modes, and it is shown that the tracking performance is better than the existing IMM algorithm with the conventional interaction step through Monte Carlo simulation for multi-target tracking in cluttered environments.

키워드

Interacting approachInteracting Multiple ModelMultitarget tracking cluttered environmentsUnequal dimensionsClutter (information theory)Intelligent systemsMonte Carlo methodsTarget trackingCluttered environmentsDynamics modelsInteracting approachInteracting multiple modelMulti-target-trackingMultiple model trackingMultitarget tracking cluttered environmentTargets trackingTracking techniquesUnequal dimensionDynamic models
제목
A new IMM interacting approach for unequal dimension states for multitarget tracking in cluttered environments
저자
Park, Seung HyoSong, Taek LyulOh, RaegeunChoi, Jee Woong
DOI
10.1109/ICCAIS52680.2021.9624630
발행일
2021-12
유형
Conference Paper
저널명
10th International Conference on Control, Automation and Information Sciences, ICCAIS 2021 - Proceedings
페이지
28 ~ 33