Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking
Ministerial Key Laboratory of JGMT, Nanjing University of Science and Technology, Nanjing 210094, China
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Academic Editor: Ba-Ngu Vo
Sensors 2017, 17(6), 1374; https://doi.org/10.3390/s17061374
Received: 17 April 2017 / Revised: 30 May 2017 / Accepted: 6 June 2017 / Published: 13 June 2017
(This article belongs to the Section Physical Sensors)
For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).
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Keywords:
maneuvering target tracking; interacting multiple model; fifth-degree spherical simplex-radial rule; Markov process
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MDPI and ACS Style
Liu, H.; Wu, W. Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking. Sensors 2017, 17, 1374.
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