改进的相位梯度法解电离层相位污染的方法

为了修正由电离层时变特性而引起电波信号相位的污染,研究人员开发了大量的算法对回波信号进行去污染。相位梯度法解相位污染是目前一种主要的解电离层相位污染的算法,但是该算法在提取一阶Bragg峰的问题上缺乏自适应的提取算法。在相位梯度法的基础上利用局部熵最小算法和基于功率比的滑窗自适应信号提取算法来其进行优化,利用仿真信号对两种改进算法和原有相位梯度算法进行验证比较。结果表明两种改进后的算法提升了解电离层相位污染的性能,同时提升了整个解相位污染方法的自适应性。此外,根据仿真实验的结果,当信号离Bragg峰更近时,功率比算法优于局部最小熵算法,当信号远离Bragg峰时,两者效果基本一致。

Study on the Method of Correcting Ionospheric Phase Perturbation Based on Improved Phase Gradient Algorithm

In order to correct the perturbation of the phase of the radio wave signal caused by the time-varying characteristics of the ionosphere, researchers have developed a large number of algorithms to decontaminate the echo signal. The phase gradient algorithm (PGA) is one of algorithms widely used to correct phase perturbations of radio waves. However, this algorithm is not able to adaptively extract the first order Bragg peaks. In this paper, the minim local entropy algorithm and an adaptive sliding window filter based on power ratio were used to improve the performance of PGA.. In this study, model studies were carried out to compare the PGA with the PGA improved by the minim local entropy algorithm and the adaptive sliding window. filter Results show that the improved PGAs could perform better than the GPA to correct the perturbation of the phase of the radio wave signal. Moreover, the PGA with the adaptive sliding window filter performed better than that with the minim local entropy algorithm when the target signal is closed to the Bragg signal. However, there is no much difference between these two algorithms when the target signal is far away from the Bragg signal.