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논문 기본 정보

자료유형
학술저널
저자정보
Khondker Rawan Hamid (Ahsanullah University of Science and Technology) Azzama Talukder (Ahsanullah University of Science and Technology) A. K. M. Ehtesanul Islam (Ahsanullah University of Science and Technology)
저널정보
한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.18 No.2
발행연도
2018.6
수록면
85 - 96 (12page)
DOI
10.5391/IJFIS.2018.18.2.85

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초록· 키워드

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The work presented in this paper deals with object tracking problem which has vast application prospects. Tracking of surrounding moving objects is important for the development of a navigation system with proper planning and motion techniques. Because of its accurate estimation characteristic, we have used Kalman filter to estimate the motion parameters of a moving object and then fuzzy logic technique is used to improve the performance of Kalman filter. The proposed fuzzy logic controller is a multiple input system with nine rules to adapt noise covariance matrices based on the innovation sequence of a Kalman filter. We have compared the results between conventional Kalman filter and fuzzy aided Kalman filter. The software based simulation results verified that this unique fuzzy aided Kalman filter has a positive effectiveness for the object tracking problem over conventional Kalman filter because of its capability to recover filter divergence problem.

목차

Abstract
1. Introduction
2. Theoretical Background
3. Problem Formulation
4. Application of Fuzzy Aided Kalman Filter in Moving Object Tracking Problem
5. Simulation Results and Discussion
6. Conclusions
References

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UCI(KEPA) : I410-ECN-0101-2018-003-002236806