摘要
对正弦波信号的频率估计是雷达领域常见的问题。当真实频率接近量化频点时,I-Rife算法的频移因子的计算会产生较大误差,为提高频率估计的精度,本文通过分析Rife及I-Rife算法的性能及误差产生的原因,利用频谱细化的方法,提出了一种修正I-Rife算法,即用峰值频点左右各0.5点处的频谱幅值来替代频谱峰值点的幅值和次大值频点处的幅值进行插值计算,对频率偏移值进行更为准确的估计,在计算量与I-Rife算法几乎相同的情况下,有效地提高了频率的估计精度。仿真结果表明,改进后的I-Rife算法整体性能优于I-Rife算法,且估计的均方根误差更接近于克拉美-罗下界。
Frequency estimation of sine wave signals is a common problem in the radar field.When the true frequency approaches the quantization frequency points,the calculation of the frequency shift factor in the IRife algorithm can introduce significant errors.In order to improve the accuracy of frequency estimation,this paper analyzes the performance and error sources of the Rife and I-Rife algorithms.By utilizing a spectral refinement method,a modified I-Rife algorithm is proposed.It replaces the amplitude of the spectral peak point with the amplitudes at 0.5 points to the left and right of the peak point,and interpolates the amplitude using the second highest frequency point.This approach allows for a more accurate estimation of the frequency offset.The proposed algorithm effectively enhances the estimation accuracy of frequency while maintaining a similar computational complexity to the original I-Rife algorithm.Simulation results demonstrate that the improved I-Rife algorithm outperforms the original I-Rife algorithm in overall performance and achieves an estimated root mean square error closer to the Cramér-Rao lower bound.
作者
王哲文
许晖
易辉跃
黄浩
杨柳
邓鹤鸣
张武雄
顾豪爽
胡永明
WANG Zhewen;XU Hui;YI Huiyue;HUANG Hao;YANG Liu;DENG Heming;ZHANG Wuxiong;GU Haoshuang;HU Yongming(School of Microelectronics,Hubei University,Wuhan 430062,China;Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Science,Shanghai 200050,China;Zhongke WaterTech Research(Jiangxi)Technology Co.Ltd.,Nanchang 330006,China)
出处
《数据采集与处理》
CSCD
北大核心
2024年第2期471-480,共10页
Journal of Data Acquisition and Processing
基金
国家自然科学基金(U21A20500)。
关键词
Rife算法
频率估计
频谱细化
快速傅里叶变换
克拉美-罗下界
Rife algorithm
frequency estimation
spectrum subdivision
fast Fourier transform(FFT)
Cramér-Rao lower bound(CRLB)
