摘要
针对当前北斗卫星导航系统(BDS)精密卫星钟差预测模型精度不高、预测误差较大等问题,提出一种将鲸鱼优化算法(WOA)和径向基函数神经网络(RBF)相结合的钟差预测模型—鲸鱼算法优化的RBF组合模型(WOA-RBF):利用四分位法和分段线性插值法完成数据预处理,通过鲸鱼优化算法对RBF中的扩展速度和输出层线性权重进行寻优,得到最优参数,最终得到优化后的输出结果。实验结果表明:与二次多项式(QP)模型、灰色模型(GM)和径向基函数神经网络(RBF)模型相比,WOA-RBF模型优势明显。在预报时长为6 h时,均方根误差在0.25 ns以内;在预报时长为12 h时,均方根误差在0.27 ns以内,证明了WOA-RBF模型在精密卫星钟差短期预报中的准确性和可行性。
Aiming at the problems of low accuracy and large prediction errors in the current BeiDou navigation satellite system(BDS)precision satellite clock error prediction model,a clock error prediction model combining whale optimization algorithm(WOA)and radial basis function neural network(RBF)was proposed.Whale algorithm optimized RBF combination model(WOA-RBF)was that the quartile method and segmented linear interpolation method were used to complete data preprocessing.The whale optimization algorithm was used to optimize the expansion speed and linear weight of the output layer in RBF,obtain the optimal parameters,and finally obtain the optimized output result.The experimental results showed that compared with the quadratic polynomial(QP)model,grey model(GM),and radial basis neural network(RBF)model,the WOARBF model had significant advantages.When the forecast duration was 6 h,the root mean square error was within 0.25 ns;When the forecast duration was 12 h,the root mean square error was within 0.27 ns,which proved the accuracy and feasibility of the WOA-RBF model in short-term prediction of precision satellite clock errors.
作者
李特
杨振
田静
郭建春
郑伟
范舒畅
LI Te;YANG Zhen;TIAN Jing;GUO Jianchun;ZHENG Wei;FAN Shuchang(College of Surveying and Mapping Engineering,Heilongjiang Institute of Technology,Harbin 150050,China;South Surveying&Mapping Technology Co.,Ltd.,Guangzhou 510000,China;Heilongjiang First Institude of Technology,Harbin 150500,China;Guangdong Communication Planning&Design Institute Group Co.,Ltd.,Guangzhou 510507,China)
出处
《导航定位学报》
CSCD
北大核心
2024年第4期25-33,共9页
Journal of Navigation and Positioning
基金
黑龙江工程学院校青年基金项目(2021QJ02)。
关键词
北斗卫星导航系统(BDS)
钟差预报
鲸鱼优化算法
径向基函数神经网络
BeiDou navigation satellite system(BDS)
clock error prediction
whale optimization algorithm(WOA)
radial basis function neural network
