SINS/GPS integrated navigation system based on improved grey forecasting model

被引：0
|
作者：
Ordnance Engineering College, Shijiazhuang [1 ]
050003, China
不详 [2 ]
714200, China
机构：
[1] Ordnance Engineering College, Shijiazhuang
[2] Huayin Ordnance Test Center of China, Huayin
来源：
Zhongguo Guanxing Jishu Xuebao | / 2卷 / 248-251 and 257期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Control and navigation; Failure forecast; Grey forecast model; Integrated navigation;
D O I：
10.13695/j.cnki.12-1222/o3.2015.02.019
中图分类号：
V355 [空中管制与飞行调度];
学科分类号：
摘要：
To forecast the GPS failure in SINS/GPS integrated navigation system, a forecast model based on improved grey prediction is presented based on the characteristics of GPS navigating and positioning information. Combining with the mathematical model of SINS/GPS integrated navigation system, the simulation based on the improved grey prediction model is carried out, and the results show that the predicted residual of GPS position data is less than 1.5 m, and during the transient failure of GPS, the anti-interference ability of SINS/GPS integrated navigation system can be improved by replacing the GPS failure data with the forecasted data. Based on the comparison of GPS failure data and prediction data, and according to the duration and changing characteristics of failure data, it is able to diagnose the GPS failure is whether a hardware failure or due to external factors, which helps to carry out the recognition and isolation of GPS failure. ©, 2015, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.
引用
收藏
页码：248 / 251and257
相关论文
共 9 条
  • [1] Jiang L.-X., Li H.-W., Yang G.-Q., A survey of spacecraft autonomous fault diagnosis research, Jounal of Astronautics, 30, 4, pp. 1320-1324, (2009)
  • [2] Zhou Z.-J., Hu C.-H., Zhou D.-H., Fault prediction techniques for dynamic systems based on nonanalytical model, Information and Control, 35, 5, pp. 608-612, (2006)
  • [3] Li X.-L., Li Y.-J., Zhang K., Improved grey fore-casting model of fault prediction in missile applications, Computer Simulation, 27, 8, pp. 33-39, (2010)
  • [4] Keller J.Y., Saute D., Restricted diagonal detection filter and updating strategy for multiple fault detection and isolation, International Journal of Adaptive Control and Signal Processing, 1210, 1, pp. 68-87, (2010)
  • [5] Weng J., Cheng Y., Qin Y.-Y., Yan G.-M., Application of vehicle constraints in SINS/OD system's fault detection, Journal of Chinese Inertial Technology, 21, 3, pp. 406-409, (2013)
  • [6] Yu M.J., Park H.W., Jeon C.B., Equivalent Nonlinear Error Models of Strapdown Inertial Navigation Systems, (1997)
  • [7] Bortz J.E., A new mathematical formulation for strapdown inertial navigation, IEEE Transactions on Aerospace and Electronic Systems, AES-7, 1, (1971)
  • [8] Wang Y., Chan C.W., Cheung K.C., On-line fault diagnosis based on b-spline neural networks using asymptotic local approach, Asian Journal of Control, 321, 1, pp. 73-78, (2008)
  • [9] Zhang Y.-W., Qin S.J., Improved nonlinear fault detection technique and statistical analysis, Aiche Journal, 17, 12, pp. 3207-3220, (2008)
1