数据缺损条件下基于关联度的跳频频率预测

FH Frequency Prediction Based on Incidence Degree Under Data Loss

对于跳频频率预测,由于硬件和测量等原因,在某些时刻会出现缺损数据现象。忽略这些数据,会导致真实跳频频率序列动力学出现变化并影响预测。因此,缺损数据的预测问题是跳频频率预测的一个重要课题。分析了数据缺损条件下基于关联度的跳频频率预测方法性能,提出了相应解决措施,仿真结果表明了所提方法的有效性。

For reasons like hardware and measurement,data loss phenomenon sometimes appears on FH frequency prediction.Ignoring the data will lead to real FH sequence dynamics to change and impact prediction.Thus data loss prediction problem is an important subject of FH frequency prediction.Under the condition of data loss,the performance of FH frequency prediction method based on incidence degree is analyzed,and corresponding solutions are presented.The simulation result shows the effectiveness of the proposed method.