Open AccessUnbiased converted measurement manoeuvering target tracking under maximum correntropy criterion
Author(s) -
Wang Guoyong,
Feng Xiaoliang
Publication year - 2020
Publication title -
cognitive computation and systems
Language(s) - English
Resource type - Journals
ISSN - 2517-7567
DOI - 10.1049/ccs.2020.0010
Subject(s) - cartesian coordinate system , computer science , kalman filter , noise (video) , radar tracker , tracking (education) , radar , kinematics , acceleration , polar coordinate system , gaussian , basis (linear algebra) , gaussian noise , algorithm , control theory (sociology) , mathematics , artificial intelligence , physics , telecommunications , psychology , pedagogy , geometry , control (management) , classical mechanics , quantum mechanics , image (mathematics)
In this study, the manoeuvering target tracking problem is addressed by using the unbiased converted measurements from a two‐dimensional radar system. Due to the fact that radar measurements are usually expressed in polar coordinates while the target motion is described in the Cartesian coordinates, the unbiased converted measurements are utilised to linearise the system model of the manoeuvering target tracking problem in the Cartesian coordinates. The manoeuver acceleration is modelled as the unknown input of the constant velocity kinematic model of the target. First, it is pointed out that the converted measurement noise no longer satisfies Gaussian distribution, even if the raw radar measurement noise is Gaussian noise. In order to solve the manoeuvering target tracking problem with non‐Gaussian disturbances, a joint estimation method for the target state and the unknown input is presented under the maximum correntropy criterion. In the simulation, the proposed manoeuvering target tracking method is compared with the one developed on the basis of the traditional Kalman filter. The simulation results verify the effectiveness of the method proposed in this study.