接收机钟差灰色马尔可夫预测模型研究

Research on Grey Markov Model for Predicting Receiver Clock Bias

将灰色理论与马尔可夫链相结合,提出了基于灰色马尔可夫链的接收机钟差预测模型。首先根据灰色理论对钟差序列数据进行拟合以及初步预测,然后以拟合曲线为基础划分状态空间,通过马尔可夫状态转移概率矩阵对初步预测值进行修正。在预测过程中,不断引入最新数据并剔除最旧数据,对模型进行实时更新,以进一步提高预测精度。实例计算验证了该模型的有效性与可行性。

By combining the advantages of both grey theory and Markov chains, a new grey Markov model for predicting receiver clock bias is presented in this paper. The grey theory is utilized to fit the sequence of receiver clock bias and calculate the initial predicted values. Then the state space is divided according to the fitting values. Finally, the initial predicted values are revised by means of Markov state change probability matrix. Meanwhile, the newest data is gradually added while the oldest one is removed from the original data sequence. In this way, the presented model can be updated in real time and the forecasting precision can be further improved. Test results are presented to demonstrate the validity and feasibility of the model.