Extracting Micro-Doppler Radar Signatures From Rotating Targets Using Fourier-Bessel Transform and Time-Frequency Analysis

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.