Instantaneous Frequency Estimation for Nonlinear FM Signal Based on Modified Polynomial Chirplet Transform

Time-frequency analysis (TFA) is an effective tool to identify the signal frequency components and to reveal their time variant features. In this paper, a new instantaneous frequency (IF) estimation method is proposed for signals with heavy noise, which is based on a polynomial chirplet transform and a ridge curve extraction scheme. Based on this method, an iterative stepwise refinement algorithm is developed to generate a time-frequency distribution (TFD) with satisfactory energy concentration. Both simulated signals and experimental vibration signals are used to validate the performance of the proposed methods. The results demonstrate that the proposed TFA method is more effective in processing the nonstationary signals with heavy noise. Further, it can perform an accurate evaluation of the IF and obtain a clear TFD.