Instantaneous Frequency Estimation of Nonlinear Frequency-Modulated Signals Under Strong Noise Environment

Abstract

Instantaneous frequency (IF) is the most important parameter of a signal, which is an important representation of non-stationary signals, such as frequency-modulated signals. Usually, signals are received with noises. Under noise environment, the conventional IF estimation methods for nonlinear frequency-modulated (NLFM) signal cannot work. In this paper, we focus on how to extract IF of NLFM signal under strong noise environment. First, a modified S-method (SM) is proposed to represent the time---frequency (TF) characteristic. The modified SM uses an adaptive smooth window. The symmetric window is used for multi-component signals and asymmetric window for mono-component signals. The modified SM enhances the TF energy concentration and suppresses the cross-terms effectively. Then, the Viterbi algorithm is used to extract the IF from the TF plane. Viterbi algorithm is a hidden Markov chain approach, which is proposed here as the IF estimator. The proposed method is utilized for various types of NLFM signals. Simulation results demonstrate the efficiency and validity of the proposed method under strong noise environment.