LFMCW信号的周期FRFT域自适应检测与参数估计

针对现有雷达信号检测方法中检测门限较难确定的问题，本文基于周期分数阶Fourier变换(PFRFT)提出了一种LFMCW信号自适应检测与参数估计方法。首先介绍了周期FRFT，分析了周期FRFT的匹配特性和处理增益；然后推导计算了高斯白噪声背景下的LFMCW信号周期FRFT域的概率统计特性，结合Neyman-Pearson准则自适应地确定检测门限，实现了低信噪比下LFMCW信号的快速检测和参数估计。理论分析和实验仿真表明了该方法的有效性。 

Adaptive Detection and Parameter Estimation of LFMCW Signal in Periodic FRFT Domain

In view of the problem that the existing radar signal detection method in the detection threshold is difficult to determine, this paper puts forward a method of adaptive detection and parameter estimation of LFMCW signal based on the periodic fractional Fourier transform(PFRFT). First, with the introduction of PFRFT, the matching characteristics and processing gain of PFRFT was analyzed; Then, the probability statistical properties of LFMCW signal in PFRFT domain was derived in the background of the Gaussian white noise, the detection threshold was determined adaptively by Neyman-Pearson criterion, and it implements the rapid detection and parameter estimation of LFMCW signal in low SNR. The analytical theory and simulation results show its effectivity.