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嵌入式大气数据传感系统及其校正

宋秀毅，陆宇平   

  1. 南京航空航天大学 自动化学院， 江苏 南京210016
  • 收稿日期:2007-11-05 修回日期:2008-01-30 出版日期:2008-05-31 发布日期:2008-05-31

Flush Air Data Sensing and Its Calibration

Song Xiu-yi, Lu Yu-ping   

  1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2007-11-05 Revised:2008-01-30 Online:2008-05-31 Published:2008-05-31

被引次数

12

摘要： 对嵌入式大气数据传感（flush airdata sensing,FADS）系统进行设计和改进。提出了避免形压系数参与迭代的卡尔曼滤波算法，形压系数通过压力修正系数得到。设计了模块化神经网络校正算法，迎角和侧滑角由模块MRCa和模块MRCb独立校正。提出校正过程中确定迎角和侧滑角最优解的方法，解决了三点组合多解的问题。最后给出计算结果和校正结果，算法的精度和实时性都有所提高，表明对系统的设计和改进是可行的。

关键词: 嵌入式大气数据传感系统, 卡尔曼滤波, 三点法, 神经网络

Abstract: An algorithm for flush air data sensing system is designed and improved. A Kalman algorithm is proposed in which iterative computation for the shape and compressibility parameters are avoided. Instead, these parameters are obtained from pressure modification coefficient. A neural network basing algorithm for the modularization is described, and the attack angle and sideslip angle are calibrated by modularization MRCa and MRCb respectively. Methods for getting optimal attack and sideslip angles are developed, solving the multiple solution problem. Calculation and calibration results are presented with improved precision and real-time characteristic, indicating that the design method is feasible.

Key words:

FADS system, Kalman algorithm, triples algorithm, neural network