A novel adaptive filtering for LFM signal in FRFT domain

A novel adaptive filtering scheme based on Fractional Fourier Transform (FRFT) for time-varying linear frequency modulated (LFM) signal is introduced and characterized using the characteristic of good energy concentration on LFM signal in FRFT domain. Grading iterative calculation method is used to obtain the best rotation angle with low computational complexity. Leakage factor is introduced for adaptation to remove the memory effects and the step size is normalized by the power of input signals. In case of LFM signal in low SNR environment, the proposed normalized leakage LMS (NL-LMS) algorithm provides less error and faster convergence. In the end, effects of different parameters on convergence are studied and simulation results present the proposed algorithm has good convergence properties and small mean square error in fast time-varying and low SNR (SNR=-10dB) environment.