Parameter Estimation of LFM Signals Based on Scaled Ambiguity Function

A method based on the scaled ambiguity function for parameter estimation of LFM signals under noncooperative conditions is presented. In the proposed algorithm, the scaling principle is employed to remove the linear frequency migration brought by the coupling between the time variable and the lag variable. Afterward, the Fourier transform is performed for feature extraction of LFM signals on the centroid frequency versus chirp rate plane. The method avoids centroid frequency information loss, which is almost inevitable in the Radon-ambiguity transform. Furthermore, fractional lower-order statistics and the scaled ambiguity transform are combined to improve the performance in practical impulsive noise environments. Simulation results show that the fractional lower-order scaled ambiguity transform is robust for both Gaussian and impulsive noise, and it achieves significant performance improvement in a heavy noise environment.