An ultrasonic positioning algorithm based on maximum correntropy criterion extended Kalman filter weighted centroid
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Ultrasonic positioning technology is being used in a wide range of application areas. In an ultrasonic positioning system, the noise of an ultrasound wave may not follow a Gaussian distribution but has a strong impulse because of many factors. A traditional extended Kalman filter based on the minimum mean square error would produce a linear estimation error and cannot handle a non-Gaussian noise effectively. Therefore, we propose a novel maximum correntropy criterion extended Kalman filter weighted centroid positioning algorithm based on a new Kalman gain formula to determine the maximum correntropy criterion. The maximum correntropy criterion maps the signal to a high-dimensional space and effectively deals with the non-Gaussian noise in ultrasonic positioning. In addition, the weighted centroid uses the results of the extended Kalman filter as inputs and reduces the impact of the linear estimation error on the positioning results. Experimental results show that the maximum correntropy criterion extended Kalman filter weighted centroid algorithm can improve the positioning accuracy by 60.06% over the extended Kalman filter and 22.83% compared with the maximum correntropy criterion extended Kalman filter. Overall, the proposed algorithm is more robust and effective.
KeywordsNon-Gaussian noise Maximum correntropy criterion (MCC) Extended Kalman filter (EKF) Weighted centroid Ultrasound
This research is supported by National Key R&D Program of China (2016YFB0700500). The authors would like to thank the reviewers for their comments.
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