Journal of Jilin University(Engineering and Technology Edition) ›› 2021, Vol. 51 ›› Issue (4): 1482-1489.doi: 10.13229/j.cnki.jdxbgxb20200374

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Motion estimation for non-cooperative target based on strong tracking cubature Kalman filter

Shao-biao XIE1,2(),Yu ZHANG3,Kai-rui WEN3,Shuo ZHANG3,Zong-ming LIU3(),Nai-ming QI1   

  1. 1.School of Astronautics，Harbin Institute of Technology，Harbin 150090，China
    2.Shanghai Academy of Spaceflight Technology，Shanghai 201109，China
    3.Shanghai Institute of Spaceflight Control Technology，Shanghai 201109，China
  • Received:2020-05-28 Online:2021-07-01 Published:2021-07-14
  • Contact: Zong-ming LIU E-mail:boyish9747@outlook.com;zongmingliu@163.com

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Abstract:

In the estimation of the motion state of non-cooperative targets such as aircraft and satellites, due to changes in the features detected by the visual system, the system estimation error will increase or even diverge. This paper proposes a strong tracking volume Kalman filter algorithm (STCKF). When using the CW equation to describe the relative motion of the satellite, considering the eccentric installation of the visual measurement system, a suboptimal fading factor is introduced in the covariance matrix of the STCKF prediction state error, and the gain is adjusted online to ensure that the residual sequences are orthogonal to each other, which guarantee the reliability and stability of the system tracking when the state changes suddenly. The simulation results show that, compared with the standard UKF and CKF algorithms, STCKF can adapt to the time-varying characteristics of the target features, and significantly improve the accuracy and stability of target tracking.

Key words: aerospace engineering and mechanics, strong tracking filter, cubature Kalman filter, vision measurement, non-cooperative target, state estimation

CLC Number: 

  • V19

Fig.1

Relative motion of chaser and target"

Fig.2

Imaging schematic of stereo vision system"

Fig.3

Relative position errors"

Fig.4

Relative velocity errors"

Fig.5

Relative attitude errors"

Fig.6

Relative angular velocity errors"

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