信号等长情况下频率估计的降频域迭代分析法

Frequency-shift-domain iterative analysis for frequency estimation of equilong signals

从特征识别角度分析了现有频率估计方法的信号分解结构的特点,提出了一种降频域分解结构,将对应不同时间的多个单频信号融合构成一个组合信号,以利用时域已知信息并形成信息积累作用,能有效抑制干扰频率和削弱冲击噪声且计算量增加较少。为配合降频域分解结构的使用,采用了适用于信号等长情况的降频等长迭代处理算法。仿真表明该方法抗噪性和实时性好,频率估计精度比现有方法有较大提高。

From the view of trick recognition, features of signal decomposition structure in existing frequency estimation methods were analyzed, based on which, a frequency-shift-domain decomposition structure was proposed. A compound signal was constructed by combining several simple signals corresponding to different times. The given information in the time domain can be adopted to form an information accumulation effect, such that the interference frequency and noise can be suppressed effectively by decreasing the calculation. To match the use of a frequency-shift-domain decomposition structure, a frequency-shift equilong iterative algorithm suitable for equilong signals was proposed. Simulated experiments were carried out in numerous application environments. The results show better noise immunity and real-time performance as well as higher frequency estimation precision.