Parameter estimation of linear frequency modulation signals based on sampling theorem and fractional broadening

Linear frequency modulation (LFM) signals are a class of important radar signals, but it is difficult to estimate their parameters in electronic warfare. Fractional Fourier transform (FRFT) is one of the most important methods for estimating the parameters of LFM signals, but the computational efficiency is strongly influenced by the search range and evaluation of the optimum FRFT order. To improve the estimation speed, we present a novel method for the parameter estimation of LFM signals using sampling theorem and fractional broadening. First, sampling theorem is used to calculate the search range of the optimum FRFT transform order. Then, the LFM signals are transformed by FRFT in the search range. Finally, the fractional broadening of the LFM signals is calculated, and the optimum FRFT order is obtained according to the relationship between the fractional broadening and the FRFT order. Experiments are performed to compare the proposed method and the traditional FRFT method. The results show that the proposed method is six times faster than the traditional FRFT method while preserving the accuracy. Moreover, it can quickly and accurately achieve the parameter estimation of multi-component LFM signals in the case of white Gaussian noise with a low signal-to-noise ratio.