基于频移修正的奎因频率估计算法

分析了奎因(Quinn)算法的性能,针对Quinn算法在信号频率接近离散傅里叶变换(DFT)量化频率时估计误差较大的问题,提出了一种改进的算法。改进算法在Quinn算法基础上通过对信号进行频移以使信号频率位于DFT量化频率中心区域,然后再用Quinn算法估计频率。仿真结果表明:改进算法估计性能不随被估计信号的频率分布而产生波动,在整个频段内估计均方根误差接近克拉美-罗限,而且具有较低信噪比门限,整体性能优于Quinn算法。在信噪比为6dB时,改进算法估计性能优于基于FFT滑动平均极大似然法。

Modified Quinn Frequency Estimation Algorithm Based on Frequency Shift

Quinn algorithm has a disadvantage of the large variance of frequency estimation when the signal frequency is closed to the DFT(Discrete Fourier Transform) discrete frequency.Aimed at the problems of Quinn algorithm,an improved frequency estimation algorithm was presented by moving the signal frequency to the midpoint of two neighboring DFT discrete frequencies.The computer simulation showed that the performance of the improved algorithm did not fluctuate with the distribution of signal frequency,the RMSE(Root Mean Square Error) approached to CRLB(Cramer-Rao Lower Bound) throughout whole frequency range.the improved algorithm also had a low SNR(Signal Noise Ratio) threshold.The performance of the improved algorithm was better than Quinn algorithm.Compared with FFT-based moving average maximum likelihood(MAML)single-tone frequency estimation,the performance of the improved algorithm was better than MAML when SNR was 6 dB.