基于子空间分解类算法的高精度频率估计

High-Accuracy Frequency Estimation Based on the Class of Subspace Decomposition Algorithms

针对高速全数字解调器中频率估计算法的高精确度及实时性要求,该文深入分析了基于子空间分解类算法的特点,提出了将求根多重信号分类(RMUSIC)法和旋转不变技术估计信号参数(ESPRIT)法分别与快速傅里叶变换(FFT)法相结合的高精度频率估计算法。首先应用RMUSIC或ESPRIT算法对信号频率进行预估计,确定粗略的窄带频率区间后,再应用加窗FFT算法对细化域内的频率进行精估计。此外,为满足不同信噪比条件的需求,提出了一种具有可选结构的高精度频率估计方法。仿真结果与分析表明,该算法极大地提高了已有频率估计算法的精度,具有较快的信号处理速度和良好的抗噪声性能。

To meet the requirements of high-accuracy and real-time frequency estimation in high-speed digital demodulators, this paper analyzes the characteristics of subspace decomposition algorithms and proposes a novel high-accuracy frequency estimation algorithm that the root multiple signal classification( root-MUSIC)algorithm and the estimation of signal parameters via rotational invariance techniques(ESPRIT) combined with fast Fourier transform(FFT) algorithm, respectively. Firstly, the root-MUSIC or the ESPRIT algorithm is applied to pre-estimate the signal frequency;then, the narrowband spectrum interested is determined;finally, the Hanning window with FFT algorithm is used to complete the accurate frequency search by the method of frequency refinement. In addition, in order to satisfy the conditions of different signal to noise ratios(SNRs) for highaccuracy frequency estimation, a new algorithm based on the optional construction is proposed. Simulation results show that not only is the estimation accuracy greatly improved compared to pre-existing algorithms because of notable anti-noise performance but also the processing time of the demodulator is reduced.