Strong tracking SCKF based on adaptive CS model for manoeuvring aircraft tracking

A novel tracking algorithm is proposed by the integration of the adaptive current statistical (CS) model and the modified strong tracking (ST) square-root cubature Kalman filter (SCKF) for the manoeuvring aircraft tracking problem. Firstly, the acceleration recursion equation and the acceleration mean input estimation are combined in order to realise the adaptive adjustment of the CS model. Then, the introduced position of the fading factor is relocated from the orthogonality principle and a new formula is put forward. Additionally, the strong manoeuver detection function is established to adjust the manoeuvring frequency of the CS model. The simulation results show that the proposed algorithm possesses better tracking accuracy than the multiple-fading-factor SCKF based on the CS model, the SCKF-ST filter based on the modified CS model and the interacting-multiple-model (IMM)-SCKF. Moreover, the proposed algorithm decreases the runtime by 40% compared with the IMM-SCKF.

[1]  Naigang Cui,et al.  Maximum correntropy sparse Gauss–Hermite quadrature filter and its application in tracking ballistic missile , 2017 .

[2]  Xiaoguang Fan,et al.  AFAKF for manoeuvring target tracking based on current statistical model , 2016 .

[3]  Huiqi Li,et al.  State of charge estimation for LiMn2O4 power battery based on strong tracking sigma point Kalman filter , 2015 .

[4]  Jiancheng Fang,et al.  Implicit UKF and its observability analysis of satellite stellar refraction navigation system , 2016 .

[5]  Ming Xin,et al.  Sparse-grid quadrature nonlinear filtering , 2012, Autom..

[6]  Z. Hang.  A SUBOPTIMAL MULTIPLE FADING EXTENDED KALMAN FILTER , 1991 .

[7]  K. Mehrotra,et al.  A jerk model for tracking highly maneuvering targets , 1997, IEEE Transactions on Aerospace and Electronic Systems.

[8]  K. S. P. Kumar,et al.  A 'current' statistical model and adaptive algorithm for estimating maneuvering targets , 1984 .

[9]  Samrat L. Sabat,et al.  Adaptive sampling strong tracking scaled unscented Kalman filter for denoising the fibre optic gyroscope drift signal , 2015 .

[10]  Binfeng Yang,et al.  Range-parameterised orthogonal simplex cubature Kalman filter for bearings-only measurements , 2016 .

[11]  Hugh F. Durrant-Whyte,et al.  A new method for the nonlinear transformation of means and covariances in filters and estimators , 2000, IEEE Trans. Autom. Control..

[12]  Cheng-lin Wen,et al.  SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking , 2011, Journal of Zhejiang University SCIENCE C.

[13]  Z Guo,et al.  An Improved Strong Tracking UKF Algorithm and Its Application in SINS Initial Alignment Under Large Azimuth Misalignment Angles , 2014 .

[14]  Jonghoek Kim,et al.  Bearings-only target motion analysis of a highly manoeuvring target , 2017 .

[15]  Wei Huang,et al.  A robust strong tracking cubature Kalman filter for spacecraft attitude estimation with quaternion constraint , 2016 .

[16]  Ali Karimpour,et al.  An interacting Fuzzy-Fading-Memory-based Augmented Kalman Filtering method for maneuvering target tracking , 2013, Digit. Signal Process..

[17]  Liu Jinmang,et al.  MCS model based on Jerk input estimation and nonlinear tracking algorithm , 2013 .

[18]  Anirban Roy,et al.  Multi-target trackers using cubature Kalman filter for Doppler radar tracking in clutter , 2016, IET Signal Process..