An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking
College of Automation, Harbin Engineering University, No. 145 Nantong Street, Harbin 150001, China
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Academic Editor: Xue-Bo Jin
Sensors 2016, 16(6), 805; https://doi.org/10.3390/s16060805
Received: 9 April 2016 / Revised: 26 May 2016 / Accepted: 26 May 2016 / Published: 1 June 2016
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).
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Keywords:
target tracking; cubature Kalman filter; unscented Kalman filter; interacting multiple models
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MDPI and ACS Style
Zhu, W.; Wang, W.; Yuan, G. An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking. Sensors 2016, 16, 805.
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