摘要
为提高高斯白噪声背景中正弦信号的频率估计精度,对基于自相关运算的频率估计算法的相关长度m进行了推导,得到了m的优化值与信噪比的关系式.当信噪比较高时,m的最优值为N/3(N为信号采样点数);信噪比较低时,m的最优值为N/2.通过对自相关法及分段FFT(Fast Fourier Transforms)相位差法特性的分析,提出了一种性能更优的频率估计综合算法.Monte Carlo仿真实验表明:新算法吸收了两种算法的优点,克服了其不足,在更大的信噪比范围内具有较高的频率估计精度,且计算量也较小.
In order to improve the frequency estimation accuracy of sinusoidal signal in white Gaussian noise,the correlation length m of the algorithm based on the autocorrelation operation was derived,and the equation representing the relationship of m and signal-to-noise ratio（SNR） was acquired.Given the data length N,the optimum value of m was N/3 when the SNR was large and it was N/2 when the SNR was small.The performance of segmented-FFT phase difference method and autocorrelation method were analyzed,and a new frequency estimation algorithm was proposed.The Monte Carlo simulation results verify that the new algorithm combines the advantages of the two methods previously mentioned,and avoid the disadvantages of them.It can fetch the highly accurate frequency of a signal in a wide range of SNR,and the computational cost is small.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2011年第8期1030-1033,1043,共5页
Journal of Beijing University of Aeronautics and Astronautics
基金
北京航空航天大学青年创新基金资助项目(911901341)
关键词
频率估计
自相关
快速傅里叶变换
误差分析
frequency estimation
autocorrelation
fast Fourier transforms（FFT）
error analysis
