Parameter-Estimation of LFM Signal Based on Combined Short Time Fourier Transform and Iteratively Reweighted Fit

To solve the problems that the estimation accuracy and the speed of the existing Linear Frequency Modulation (LFM) signal parameters estimation methods are mutually exclusive and sensitive to signal distortion, a parameters estimation method based on combined improved Short Time Fourier Transform (STFT) with Rife interpolation and Iteratively Reweighted Least Squares Linear Fit (IRLSF) is proposed. The improved STFT with Rife interpolation which is used to extract the instantaneous frequency of LFM signal can keep the linear feature of the instantaneous frequency well and the iterative reweighted process which is used to fit the instantaneous frequency curve can reduce the impact of exceptional values on parameter estimation accuracy. With no need of complex calculation and parameters searching, this method has a good real-time performance. The results of Monte Carlo simulation experiment show that the low limit of Signal-to-Noise Ratio (SNR) is reduced 4dB comparing with the Conventional Least Squares Linear Fit (CLSF) method and the parameter estimation performance approaches to the Cramer-Rao Lower Bound (CRLB) at a high SNR. At last, the lake experimental results verify its validity and feasibility.