雷达动目标短时稀疏分数阶傅里叶变换域检测方法

Radar Detection for Moving Target in Short-Time Sparse Fractional Fourier Transform Domain

复杂背景下的动目标检测技术是雷达目标探测的关键技术和难点之一,亟需发展和研究高时频分辨率、大数据量高效以及适用于多分量信号分析的方法和手段.该文结合经典时频分析技术和高分辨稀疏域信号处理的优势,提出短时稀疏分数阶傅里叶变换(ST-SFRFT)并用于雷达动目标检测和参数估计,实现时变信号高分辨时频表示的同时,改善SCR,提高复杂环境下雷达动目标检测的性能.实测对海雷达数据验证表明,所提方法在抗杂波以及参数估计精度等方面较经典时频动目标检测方法有明显优势.

Moving target detection in complex environment is one of the key points and difficulties in radar target detection.It is necessary to develop theory and method of high time-frequency resolution,high efficiency for big data, and suitable for multi-signals analysis. In this paper, the concept of short-time sparse fractional Fourier transform（ ST-SFRFT） is proposed in association with the advantages of classical time-frequency analysis and high-resolution signal processing in sparse domain. The ST-SFRFT is then used for radar moving target detection and parameter estimation,which can achieve high-resolution representation of time-varying signal and improve signal-to-clutter ratio as well. The detection performance of moving target in complex environment is improved. Real experiment using a marine radar was carried out and the results indicate that the proposed method shows distinct advantages in anti-clutter and parameter estimation over classical time-frequencybased moving target detection methods.