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Sensors 2016, 16(5), 629; doi:10.3390/s16050629

Feedback Robust Cubature Kalman Filter for Target Tracking Using an Angle Sensor

Information and Navigation College Air Force Engineering University, Fenghao east road No.1, Xi’an 710077, China
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Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 9 January 2016 / Revised: 20 February 2016 / Accepted: 29 February 2016 / Published: 9 May 2016
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Abstract

The direction of arrival (DOA) tracking problem based on an angle sensor is an important topic in many fields. In this paper, a nonlinear filter named the feedback M-estimation based robust cubature Kalman filter (FMR-CKF) is proposed to deal with measurement outliers from the angle sensor. The filter designs a new equivalent weight function with the Mahalanobis distance to combine the cubature Kalman filter (CKF) with the M-estimation method. Moreover, by embedding a feedback strategy which consists of a splitting and merging procedure, the proper sub-filter (the standard CKF or the robust CKF) can be chosen in each time index. Hence, the probability of the outliers’ misjudgment can be reduced. Numerical experiments show that the FMR-CKF performs better than the CKF and conventional robust filters in terms of accuracy and robustness with good computational efficiency. Additionally, the filter can be extended to the nonlinear applications using other types of sensors. View Full-Text
Keywords: angle sensor; DOA tracking; nonlinear system; cubature Kalman filter; robust estimation; feedback strategy angle sensor; DOA tracking; nonlinear system; cubature Kalman filter; robust estimation; feedback strategy
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wu, H.; Chen, S.; Yang, B.; Chen, K. Feedback Robust Cubature Kalman Filter for Target Tracking Using an Angle Sensor. Sensors 2016, 16, 629.

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