基于EMD和FFT的自适应X射线脉冲星信号降噪方法

      Adaptive denoising method of X-ray pulsar signal based on EMD and FFT

      • 摘要: X射线脉冲星导航是一种具有发展潜力的深空探测技术,其导航精度主要受X射线脉冲信号到达时间精度影响;X射线脉冲星信号降噪技术有望为X射线脉冲星导航提供良好的信号支撑。在有效抑制噪声的基础上,如何最大限度保留X射线脉冲星信号细节信息,一直是X射线脉冲星信号降噪处理中的难点。在经验模态分解(empirical mode decomposition, EMD)阈值降噪中,混叠内蕴模态分量的个数、阈值函数和阈值是影响降噪效果的三个主要因素。本文利用快速傅里叶变换对混叠内蕴模态分量进行分析,据其频域稀疏度筛选出含噪声的高频混叠内蕴模态分量;针对阈值函数和阈值的选择问题,提出了利用复合评价指标选择出阈值函数和阈值估计方法的最优组合,并通过数值仿真验证了该方法的有效性。仿真和测试结果表明本文方法在脉冲星导航方面可能具有应用前景。

         

        Abstract: X-ray pulsar navigation is a deep space exploration technology with promising development potential. Its navigation accuracy is primarily affected by the precision of time of arrival of X-ray pulsar signal. X-ray pulsar signal denoising technology is expected to provide strong signal support for X-ray pulsar navigation. A key challenge in X-ray pulsar signal denoising is to retain the detailed information of X-ray pulsar signals while effectively suppressing noise. In empirical mode decomposition (EMD) threshold denoising, the number of aliasing intrinsic mode functions (IMFs), threshold functions and thresholds are main factors affecting the denoising effect. This paper analyzes IMF components using fast fourier transform (FFT) and selects noisy high-frequency mixed IMFs based on the frequency domain sparsity of IMFs. For the problem of choosing threshold functions and thresholds, a composite evaluation index (CEI) is proposed to identify the optimal combination of threshold function and threshold estimation method. The effectiveness of the proposed method is verified by numerical simulation. Simulation and test results indicate that this method may have application prospects in pulsar navigation.

         

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