基于经验模态分解的自适应噪声对消方法

针对飞行器试验中单通道遥测信号频率内容丰富、降噪困难的问题,提出了一种基于经验模态分解的自适应噪声对消方法。将信号利用经验模态分解(Empirical mode decomposition, EMD)方法分解为一系列本征模态函数(Intrinsic Mode Function,IMF),将第一阶IMF作为参考噪声,并将第二阶以后的IMF分量累加求和,作为待降噪信号,在此基础上利用自适应噪声对消系统完成降噪。该方法克服了直接将高阶IMF作为噪声消除后在降噪和细节信息损失之间的矛盾性问题,可以最大程度保护信号细节信息不受损失的情况下实现良好的降噪效果。计算机仿真和某次飞行器试验实测数据处理结果证明了这一方法的有效性。

Adaptive Noise Cancellation Method Based on Empirical Mode Decomposition

To solve the difficult problems of the noise suppression of the signle-channle telemetry for its rich frequency in vehicle test, an adaptive noise cancellation method based on empirical mode decomposition is proposed. The signal is decomposed into a series of Intrinsic Mode Functions (IMF) using the empirical mode decomposition (EMD) method. The first-order IMF is used as the reference noise, and the IMF components after the second order are summed as the signal to be noise-suppressed. Based on this, the adaptive noise cancellation system is used to complete the noise suppression. The proposed method overcomes the contradiction between the noise suppression and the loss of details after directly removing the high-order IMFs as noise. A good noise reduction effect can be achieved with maximum protection of signal detail information without loss. Computer simulation and the actual data processing results of an vehicle test show the effectiveness of the proposed method.