Jin-hua Wang
Lanzhou University of Technology

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Acoustic Source Localization Based on Iterative Unscented Particle Filter Jie cao; Jia-qi Liu; Di Wu; Jin-hua Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 5: May 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

To solve the problem of tracking an acoustic source in noise and reverberation environment, a new method is proposed in pursuit of higher accuracy. First, this paper improves the unscented particle filter, which can add the latest measurement information to optimize the proposal distribution. Then, the likelihood function is constructed by calculating the microphone arrays’ output energy in the framework of the improved algorithm. Finally, the experiment results indicate that the proposed localization method can not only improves the accuracy of location estimation, but also can enhance the ability to resist noise and reverberation in the acoustic source localization system. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4816
Object Tracking Method Based on a New Multi-Feature Fusion Strategy Jie Cao; Lei-lei Guo; Jin-hua Wang; Di Wu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 9: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i9.pp6811-6818

Abstract

In order to solve the poor robustness problem due to partial occlusionof target, we propose an adaptive particle filter tracking method based on thefusion of the multiple features. First, we regard information fusion as aprocess of information loss, loss coefficient is defined based on this idea.Then the credibility of feature can be obtained by weighted distance and themean of particle filter, and we use the features’ credibility to reallocate theloss coefficient. An extensive number of comparative experiments show theproposed algorithm is more stable and robust than multiplicative fusion andadditive fusion tracking algorithms.