【作者】 李杨； 张宁； 杨强；

【Author】 LI Yang,ZHANG Ning,YANG Qiang Research Institute of Electronic Engineering,Harbin Institute of Technology,Harbin 150001,China

【机构】 哈尔滨工业大学电子工程技术研究所；

【摘要】 加窗将对信号频率估计的性能产生影响,因此必须通过修正常数来校正误差。当噪声污染下的信号的频率位于离散频谱两采样点之间不同位置时,频率估计的精度将相差很大。此时分别考虑各个位置的估计偏差和均方根误差很难得出一个全局最优的修正常数。为此,提出了一种使用最大偏差准则来选择修正常数的方法。该方法综合考虑了不同采样位置的估计偏差和均方根误差,并结合准则构造了适用于信号频率估计修正常数选择的性能量化准则。通过仿真分析了该算法的性能,结果表明,使用基于最大偏差准得出的修正常数可以提高信号频率估计的整体性能。更多还原

【Abstract】 Weighting window may have effect on the performance of signal frequency estimation,thus corrected constant should be used for revising the error.Frequency estimation accuracy varies with different position between two samples in spectrum when the frequency of a tone is contaminated with noise.Only considering bias and Root Mean Square Error(RMSE) at each position cannot give a global optimization corrected constant. Maximum Deviation Criterion(MDC) is proposed for selecting the corrected constant.This method constructs a performance quantitative criterion considering bias and RMSE at different sampling locations with criterion which fits for signal frequency estimation.Performance of MDC is analyzed by Monte Carlo simulation. The result shows that using the corrected constant based on MDC can increase the whole performance of signal frequency estimation.更多还原