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中文摘要：
针对调频连续波（frequency modulated continuous wave,FMCW）雷达信号在传播过程中会受到各种噪声影响的情况,提出了一种新型的基于自相关函数能量特性的经验模态分解（empirical mode decomposition,EMD）降噪算法。该算法首先对差频信号进行EMD分解,得到包含原信号不同尺度信息的本征模态函数（intrinsic mode function,IMF）分量;其次对每一IMF分量进行无偏自相关运算,并计算其能量;第三,根据IMF分量的自相关函数能量变化曲线,确定出有用信号贡献率最大的IMF分量;最后进行EMD重构。实验结果表明：该方法在各种信噪比条件下,能够准确判断出有用信号主导的IMF分量,对差频信号具有良好的去噪效果,同时该方法具有自适应性,不受主观因素的影响,适合应用在FMCW雷达系统中。
英文摘要：
For the case that FMCW（ frequency modulated continuous wave） radar signals will be affected by various noise in the communication process,a new kind of the EMD（ Empirical Mode Decomposition） denosing algorithm based on the energy characteristics of the autocorrelation function is proposed. First,the algorithm decomposes the differendial frequency signal into IMF（ Intrinsic Mode Function） components which contain different scale information of the original signal; second,for each IMF component,execute the unbiased self-relation operation,and calculate their energy; third,confirm the useful signal IMF component whose contribution rate is the maximum,finally reconstruct EMD. The results show that. The method under various SNR conditions,the ability to accurately determine IMF component which lead by the useful signal,has a good effect on denosing of differendial frequency signal,and the method is also adaptive,which is unaffected by subjective factors,and suitable for application in FMCW radar system.
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