现代电子对抗环境下雷达信号脉内参数估计算法研究及优化方案

In the modern electronic warfare environment, the dense signals, complex modulation types, and variable modulation parameters pose great challenges to electronic reconnaissance. Therefore, conventional pulse parameter descriptions cannot effectively characterize the essential features of radar. In order to adapt to and cope with the complex electronic warfare environment of the present and future, research on radar signal intra-pulse parameter estimation becomes increasingly important. This paper focuses on the study of intra-pulse parameter estimation methods for two common radar signals: frequency-modulated (FM) signals and phase-coded signals. For the estimation of parameters of FM signals, linear frequency-modulated signals are studied. Three commonly used time-frequency domain methods, namely Wigner-Ville Distribution (WVD) Hough method, Radon-Wigner method, and fractional Fourier transform method, are investigated. Then, the relationships between these three methods and the maximum likelihood method are presented. Maximum likelihood estimation is optimal but computationally complex, so this paper provides two fast algorithms to improve its computational speed, which are demonstrated to be real-time and effective through simulations. Regarding the parameter estimation of phase-coded signals, two estimation algorithms for binary phase-coded signals are studied: parameter estimation based on wavelet transform and parameter estimation based on cyclic spectrum. Each algorithm has its own advantages and disadvantages, and this paper provides in-depth analysis of both algorithms and presents experimental simulations. Keywords: parameter estimation, maximum likelihood estimation, cyclic spectrum, wavelet transform.