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Guidance Instrumentation Systematic Error Separation Method Based on Particle Swarm Optimization

  • Zhen-xing LiEmail author
  • Zhao-gang Wang
  • Dong Li
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)

Abstract

A new separation method of guidance instrumentation systematic error of vehicle based on particle swarm optimization (PSO) was proposed. The telemetry environment function matrix is seriously ill-conditioned, which results in the performance degradation of guidance instrumentation systematic error separation. Hereby the problem of guidance instrumentation systematic separation is transformed into an optimization problem and PSO is used to estimate the systematic error coefficients. Furthermore, the guidance instrumentation systematic error is separated from the vehicle trajectory measurement data. The measured data processing results show that the accuracy of the separation of guidance instrumentation systematic error based on PSO is better than that of the traditional Bayesian estimation and principal component estimation methods. The proposed method has practical engineering application value in vehicle test.

Keywords

Vehicle test Particle swarm optimization Guidance instrumentation systematic error Telemetry environment function matrix 

Notes

Acknowledgement

This work was supported in part by The National Natural Science Foundation of China (61703408, 61801482).

References

  1. 1.
    Xie, Y.Z.: The research of combining ridge and principal components estimate in separating guidance instrument systematicatic error. J. Proj. Rocket. Missiles Guid. 33(3), 189–191 (2013)Google Scholar
  2. 2.
    Yang, H.B., Zhang, S.F., Cai, H., Hu, Y.Z.: Modeling and parameters of guidance instrumentation systematicatic error and initial launched parameters error for marine-missile. J. Astronaut. 28(6), 1638–1642 (2017)Google Scholar
  3. 3.
    Xie, Y.Z., Li, Z.X.: Influence factors of guidance instrumentation systematic error linear model estimation. Aerosp. Control 31(5), 46–49 (2013)Google Scholar
  4. 4.
    Yao, J., Duan, X.J., Zhou, H.Y.: Modeling and parameters estimation of marine guidance instrumentation systematicatic error. J. Ballist. 17(1), 33–39 (2005)Google Scholar
  5. 5.
    Luo, S.W., Wei, K.H.: Effect of guidance instrument error on reentry point’s parameters. Inf. Electron. Eng. 3(2), 101–104 (2005)Google Scholar
  6. 6.
    Chai, X.D., Liu, L.W., Chang, B.X., Jiang, T., Wang, Z.: On a batch matching systematic with impatient servers and boundedly rational customers. Appl. Math. Comput. 354, 308–328 (2019)MathSciNetGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.PLA 92124 UnitDalianChina

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