摘要
针对传统预测方法存在的不足,建立一种基于小波神经网络的陀螺漂移预测模型。重点研究利用小波分析理论对陀螺输出信号的漂移趋势识别提取方法,结合小波神经网络建立漂移信号的非线性预测模型,并以某陀螺实测信号为例预测其漂移趋势。结果表明:该模型能降低人为因素影响,提高漂移预报效果和导航系统精度。
Aiming at the shortage of tradition prediction method, established a new prediction model of gyro drift based on wavelet neural network. This paper mainly studies recognition and abstraction method of gyro output signal's drift trend using wavelet analysis theory, set up the non-linear prediction model of drift signal combining the wavelet neural network, and predicts the drift trend taking certain gyro measured signal as example. Result shows that the model can reduce human factor influence, advance drift prediction effect and navigation system precision.
出处
《兵工自动化》
2012年第2期82-84,96,共4页
Ordnance Industry Automation
基金
国家自然科学基金"基于尺度的综合导航系统信息融合算法研究"(60874112)
"泰山学者"建设工程专项经费资助
关键词
小波神经网络
陀螺漂移
预测模型
导航精度
wavelet neural network
gyro drift
prediction model
navigation precision