噪声情况下的时变间谐波谱估计

间谐波幅值远小于基频或其它整数倍谐波的幅值，使其对噪声非常敏感，噪声往往会将这类微弱信号淹没。另一方面，实际间谐波频谱是随时间变化的，应看作随机信号来处理。该文提出一种基于4阶累积量的可变遗忘因子递推最小二乘法(cumulants recursive least square-variable forgetting factor，CRLS-VFF)，将间谐波信号看作一个时变自回归(auto-regressive，AR)模型，利用参数化谱估计方法分辨率高的优点，将间谐波谱估计问题转化为时变AR参数的估计。4阶累积量可抑制任何高斯噪声，保证算法的频率分辨率；可变遗忘因子提高了算法跟踪时变参数的能力。对根据间谐波特点构建的仿真模型及典型的间谐波源——变频装置产生的信号进行仿真，结果证明：该方法能在噪声情况下准确估计出时变间谐波的频谱。

Spectral Estimation of Time-varying Inter-harmonics in Noisy Environment

Interharmonics amplitudes are far less than the amplitudes of fundamental and harmonics components, so detection of interharmonics is sensitive to noise and they are always submerged by the noise. On the other hand, the real frequencies and amplitudes of interharmonics are time-varying. Interharmonics should be considered as random signals. In this paper, an improved recursive least square (RLS) algorithm was proposed to estimate the spectral of time-varying inter- harmonics. Its objective function based on fourth-order cumulants and its forgetting factor is variable. Interharmonics signal can be modeled as an auto-regressive (AR) model, the spectral estimation of interharmonics can be given by the estimated time-varying AR parameters. Fourth-order cumulants can suppress the Gauss noise and ensure the high frequency resolution. Variable forgetting factor (VFF) can improve the tracking ability of the RLS algorithm. Two tests were used to validate the proposed method, an interharmonics digital simulation model whose frequencies closed to fundamental frequency and amplitudes were low and an AC/DC/AC conversion system simulation model whose input side frequencies and output side frequencies were time-varying. The results of simulation proved that in noisy environments, this proposed method can get the spectral estimation of time- varying interharmonics accurately.