摘要
在对雷达跟星校飞试验测量数据进行分析的基础上,利用BP神经网络方法建立了丢失帧数据和野值帧数据的估算模型。通过实例计算、分析、比较,证明BP神经网络方法估算精度要优于三次样条插值。
Based on analysis of measurement data of a calibration flight test by tracking a satellite,this paper establishes estimation models for data of lost frames and exceptional value frames with back propagation(BP) neural network estimation approach.It is proved through calculation, analysis and comparison of data drawn from samples that BP neural network estimation approach has a higher precision in estimating data of lost frames and outlier frames than the cubic spline interpolation approach.
出处
《飞行器测控学报》
2009年第2期32-35,共4页
Journal of Spacecraft TT&C Technology
关键词
跟星校飞试验
BP神经网络
三次样条插值
Calibration Flight Test by Satellite
Back Propagation(BP) Neural Network
Cubic Spline Interpolation