桂林理工大学学报2017，Vol.37Issue(1)：125-130,6.DOI:10.3969/j.issn.1674-9057.2017.01.018
基于小波分解和遗传小波神经网络的卫星钟差预报
Prediction of satellite clock bias based on wavelet decomposition and genetic wavelet neural network
摘要
Abstract
Because of many uncertain factors in the space environment and influenced by the complex features of on-board atomic clock,satellite clock bias presents nonlinear and non-stationary.According to this question,this paper proposes a new method.First,this method uses wavelet decomposition to decompose the original SCB series into high frequency and low frequency components,and with the genetic wavelet neural network to predict low frequency and high frequency components respectively.Finally,the final prediction value of SCB is yielded by the linearity superposition for the respective prediction results.In comparison and analysis with the prediction results of gray model,the least squares support vector machine and genetic wavelet neural network.The test results show that the prediction accuracy of the new method is high and forecast residual is relatively more stable,and accordingly it can be used for SCB prediction.关键词
钟差预报/小波分解/最小二乘支持向量机/遗传小波神经网络Key words
satellite clock bias prediction/wavelet decomposition/least squares support vector machine/genetic wavelet neural network分类
天文与地球科学引用本文复制引用
蓝岚,任超,梁月吉,李飞达..基于小波分解和遗传小波神经网络的卫星钟差预报[J].桂林理工大学学报,2017,37(1):125-130,6.基金项目
国家自然科学基金项目(41461089) （41461089）
广西自然科学基金项目(2014GXNSFAA118288) （2014GXNSFAA118288）
广西空间信息与测绘重点实验室基金项目(桂科能1207115-07 （）
130511407) （）
