Target Track Prediction Method Based on Grey Residual Modification Theory

被引：0
|
作者：
Di Y. [1 ]
Gu X.-H. [1 ]
Long F. [2 ]
机构：
[1] School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu
[2] Institute of Intelligent Information Processing, Guizhou University, Guiyang, 550025, Guizhou
来源：
Gu, Xiao-Hui (gxiaohui@njust.edu.cn) | 2017年 / China Ordnance Industry Corporation卷 / 38期
关键词：
Grey residual modification model; Ordnance science and technology; Residual modification; Target tracking; Track prediction;
D O I：
10.3969/j.issn.1000-1093.2017.03.006
中图分类号：
学科分类号：
摘要：
Two grey residual modification models are proposed for the track prediction precision of brainpower antitank (BAT) submunition based on grey theory, which are grey residual modification model (GRMM) and grey Verhulst residual modification model (GVRMM). A grey model of target track prediction is established, and the limitations of this model are analyzed. GRMM and GVRMM are used to correct the grey forecast model on line, respectively. It shows that the proposed method based on real-time residual modification mechanism can be used to reduce the prediction error effectively, and GVRMM has better efficiency in improving track prediction precision. © 2017, Editorial Board of Acta Armamentarii. All right reserved.
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页码：454 / 459
页数：5
相关论文
共 14 条
  • [1] Kalman R.E., A new approach to linear filtering and prediction problems, Journal of Basic Engineering, 82, 1, pp. 35-45, (1960)
  • [2] Hlinomaz P., Hong L., A multi-rate multiple model track-before-detect particle filter, Mathematical and Computer Modeling, 49, 1, pp. 146-162, (2008)
  • [3] Lan J., Li X.R., Equivalent model augmentation for variable structure multiple-model estimation, IEEE Transactions on Aerospace and Electronic System, 49, 4, pp. 2615-2630, (2013)
  • [4] Sun B.-L., Jiang C.-L., Li M., Et al., Fuzzy logic-based interacting multiple model algorithm of networked munitions for target tracking, Acta Armamentarii, 36, 4, pp. 595-601, (2015)
  • [5] Kayacan E., Ulutas B., Kaynak O., Grey system theory-based models in time series prediction, Expert Systems with Applications, 37, 2, pp. 1784-1789, (2010)
  • [6] Kumar U., Jain V.K., Time series models (Grey-Markov, Grey model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India, Energy, 35, 4, pp. 1709-1716, (2010)
  • [7] Zhao J.-Z., Ye W., Zhang L., Failure prediction of missile equipment based on data fusion and AMUGM(1, 1) model, Acta Armamentarii, 35, 10, pp. 1689-1695, (2014)
  • [8] Gu X.-H., Wang X.-M., Zhao Y.-S., Prediction of helicopter tracks based on grey system theory, Acta Aeronautica et Asstronaytica Sineca, 22, 6, pp. 559-562, (2001)
  • [9] Xu J., Tan T., Tu M., Et al., Improvement of grey models by least squares, Expert Systems with Applications, 38, 11, pp. 13961-13966, (2011)
  • [10] Luo D., Liu S.-F., Dang Y.-G., The optimization of grey model GM(1,1), Engineering Science, 5, 8, pp. 50-53, (2003)
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