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논문 기본 정보

자료유형
학술저널
저자정보
Jaechan Lim (Pohang University of Science and Technology)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.8 No.6
발행연도
2013.11
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1,520 - 1,529 (10page)

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초록· 키워드

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In this paper, we propose and assess the performance of “H infinity filter ( H<SUB>∞</SUB> , HIF)” and “cost reference particle filter (CRPF)” in the problem of tracking a target based on the measurements of the range and the bearing of the target. HIF and CRPF have the common advantageous feature that we do not need to know the noise statistics of the problem in their applications. The performance of the extended Kalman filter (EKF) is also compared with that of the proposed filters, but the noise information is perfectly known for the applications of the EKF. Simulation results show that CRPF outperforms HIF, and is more robust because the tracking of HIF diverges sometimes, particularly when the target track is highly nonlinear. Interestingly, when the tracking of HIF diverges, the tracking of the EKF also tends to deviate significantly from the true track for the same target track. Therefore, CRPF is very effective and appropriate approach to the problems of highly nonlinear model, especially when the noise statistics are unknown. Nonetheless, HIF also can be applied to the problem of timevarying state estimation as the EKF, particularly for the case when the noise statistcs are unknown. This paper provides a good example of how to apply CRPF and HIF to the estimation of dynamically varying and nonlinearly modeled states with unknown noise statistics.

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Abstract
1. Introduction
2. System Model
3. Filtering Methods
4. Simulations
5. Summary and Conclusion
References

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