The parameter estimation of LFM signal using generalized Versoria Wigner-Ville distribution in impulsive noise
Yuzi Dou, Sen Li, Bin Lin · 2023
In various engineering applications, nonstationary signal is a critical component. The bi-dimensional functions based on second-order statistics are commonly utilized to monitor the time and frequency evolution of nonstationary signals under Gaussian noise environments. However, non-Gaussian impulsive noise is ubiquitous in practice scenarios, and as a result, the effectiveness of these methods will be affected. In this paper, by introducing a generalized Versoria function with noise suppressing capability into the time-delay instantaneous autocorrelation function, we define a new time-frequency representation called generalized Versoria Wigner-Ville distribution (GVWVD). Next, by combining the GVWVD with the Radon transform, a robust Radon-GVWVD transform (GVRWT) is proposed for detecting a linear frequency modulated (LFM) signal under the impulsive noise environment. The superior performance of the proposed algorithm compared to its competitors is verified by simulations.