A Comparative Study of FFT Based Frequency Estimation Using Different Interpolation Techniques

Fast Fourier Transform (FFT) is a commonly used method in electronic support systems for frequency parameter estimation. If the frequency of the radar signal is not an exact multiple of the frequency resolution, the frequency of this signal will usually appear in an inter-line position when FFT is applied. To improve the accuracy of the estimated frequency, interpolation techniques are used to find the peak between two spectral lines. In this study, the frequency of the radar signal is estimated by employing three different interpolation techniques (Ding, Voglewede and Hanning window based interpolation) to the output obtained by applying N-point FFT to the intermediate frequency (IF) signal. In addition, unlike the literature, the behavior of signals contaminated with Laplace noise as well as Gaussian noise were analyzed with these three techniques and their performances were compared. From the analysis results, Ding and Voglewede techniques reduced error rate at all frequency. However, the Hanning window-based interpolation method improved the frequency accuracy values at 500MHz and 750MHz, but it increased the error at 250MHz and 1000MHz frequencies. The error rates of the estimated frequencies can be sorted from the lowest to the highest as follows: Ding, Voglewede and Hanning window based interpolation.