Preprint Article Version 1 This version is not peer-reviewed

IMM Fifth-Degree Spherical Simplex-Radial Cubature Filter for Maneuvering Target Tracking

Hua Liu * ORCID logo and Wen Wu *
Version 1 : Received: 17 April 2017 / Approved: 18 April 2017 / Online: 18 April 2017 (03:35:28 CEST)

A peer-reviewed article of this Preprint also exists.

Liu, H.; Wu, W. Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking. Sensors 2017, 17, 1374. Liu, H.; Wu, W. Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking. Sensors 2017, 17, 1374.

Journal reference: Sensors 2017, 17, 1374
DOI: 10.3390/s17061374

Abstract

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named interacting multiple model fifth-degree spherical simplex-radial cubature filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and fifth-degree spherical simplex-radial cubature 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 IMMUKF, IMMCKF and IMM5thCKF.

Subject Areas

maneuvering target tracking; interacting multiple model; fifth-degree spherical simplex-radial rule; Markov process

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