A New Modified Particle Filter With Application in Target Tracking

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HAVANGI R.

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Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF ELECTRICAL AND ELECTRONIC ENGINEERING Year:2020 | Volume:16 | Issue:4 Page(s): 449-460

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Title

A New Modified Particle Filter With Application in Target Tracking

Author(s)

HAVANGI R. | Issue Writer Certificate

Keywords

Particle Filter

Genetic Algorithm

Unscented Kalman Filter

Target Tracking

Abstract

The Particle Filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified Particle Filter called adaptive unscented Particle Filter (AUPF) to overcome these problems. The proposed method uses an adaptive Unscented Kalman Filter (AUKF) filter to generate the proposal distribution, in which the covariance of the measurement and process of the state are online adjusted by predicted residual as an adaptive factor based on a covariance matching technique. In addition, it uses the genetic operators based strategy to further improve the particle diversity. The results show the effectiveness of the proposed approach.

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APA: Copy

HAVANGI, R.. (2020). A New Modified Particle Filter With Application in Target Tracking. IRANIAN JOURNAL OF ELECTRICAL AND ELECTRONIC ENGINEERING, 16(4), 449-460. SID. https://sid.ir/paper/299921/en

Vancouver: Copy

HAVANGI R.. A New Modified Particle Filter With Application in Target Tracking. IRANIAN JOURNAL OF ELECTRICAL AND ELECTRONIC ENGINEERING[Internet]. 2020;16(4):449-460. Available from: https://sid.ir/paper/299921/en

IEEE: Copy

R. HAVANGI, “A New Modified Particle Filter With Application in Target Tracking,” IRANIAN JOURNAL OF ELECTRICAL AND ELECTRONIC ENGINEERING, vol. 16, no. 4, pp. 449–460, 2020, [Online]. Available: https://sid.ir/paper/299921/en

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