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

机译:强噪声环境下非线性调频信号的瞬时频率估计

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摘要

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.
机译:瞬时频率(IF)是信号的最重要参数,它是非平稳信号(例如调频信号)的重要表示。通常,接收到的信号带有噪声。在噪声环境下,用于非线性调频(NLFM)信号的常规IF估计方法无法使用。在本文中,我们着重于在强噪声环境下如何提取NLFM信号的IF。首先,提出了一种改进的S方法(SM)来表示时频(TF)特性。修改后的SM使用自适应平滑窗口。对称窗口用于多分量信号,非对称窗口用于单分量信号。改进的SM提高了TF能量集中并有效地抑制了交叉项。然后,使用维特比算法从TF平面提取IF。维特比算法是一种隐式马尔可夫链方法,在此作为IF估计器提出。所提出的方法用于各种类型的NLFM信号。仿真结果证明了该方法在强噪声环境下的有效性和有效性。

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