Extracting Micro-Doppler Radar Signatures From Rotating Targets Using Fourier-Bessel Transform and Time-Frequency Analysis
Extracting Micro-Doppler Radar Signatures From Rotating Targets Using Fourier-Bessel Transform and Time-Frequency Analysis
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DOI：
10.1109/tgrs.2013.2271706
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发表时间：
2014-06-01
影响因子：
8.2
通讯作者：
Venkataramaniah, K.
中科院分区：
文献类型：
--
作者：
Suresh, P.;Thayaparan, T.;Venkataramaniah, K.
本文将傅立叶-贝塞尔变换(FBT)和时频变换(TF)与分数傅立叶变换(FrFT)相结合，对旋转目标的微多普勒(m-D)雷达特征提取进行了研究。该方法主要包括两个过程，第一个过程是对雷达回波信号进行分解，以提取m-D特征，第二个过程是目标函数分析，以估计目标的运动参数。为了从雷达信号回波中提取m-D特征，结合FBT和FrFT将雷达信号分解为平稳和非平稳分量。然后，通过应用反傅立叶-贝塞尔变换(IFBT)来重建分量。在从目标原始雷达回波中提取m-D特征后，使用TF分析来估计目标的运动参数。该方法也是在强海杂波环境下检测机动空中目标的有效工具，并适用于仿真数据和真实实验数据。
In this paper, we report the efficiency of the Fourier-Bessel transform (FBT) and time-frequency (TF)-based method in conjunction with the fractional Fourier transform (FrFT), for extracting micro-Doppler (m-D) radar signatures from the rotating targets. This approach comprises mainly of two processes, with the first being the decomposition of the radar return, in order to extract m-D features, and the second being the TF analysis to estimate motion parameters of the target. In order to extract m-D features from the radar signal returns, the time domain radar signal is decomposed into stationary and nonstationary components using the FBT in conjunction with the FrFT. The components are then reconstructed by applying the inverse Fourier-Bessel transform (IFBT). After the extraction of the m-D features from the target's original radar return, TF analysis is used to estimate the target's motion parameters. This proposed method is also an effective tool for detecting maneuvering air targets in strong sea clutter and is also applied to both simulated data and real-world experimental data.