A Novel ISAR Imaging Algorithm for a Maneuvering Target Based on Generalized Second-Order Time-Scaled Transform

It is well-known that for a maneuvering target, its inverse synthetic aperture radar (ISAR) imaging quality may significantly deteriorate using the classical range-Doppler (RD) algorithm. To address this issue, this article proposes a novel ISAR imaging algorithm based on the generalized second-order time-scaled transform (GSOTST). In the proposed method, the multicomponent cubic phase signal (CPS) modeling is adopted for the radar echo signal after translational motion compensation (TMC) to portray the phase change characteristics more accurately. First, the target signal is transformed into the slow-time-delay-time domain using a correlation kernel function (CKF). Subsequently, the nonstationary phase is eliminated in the slow-time-generalized delay-time-frequency (GDTF) domain, and the GSOTST is used to decouple the temporal variables. Finally, the generalized Fourier transform is performed to transform the signal into the 2-D frequency domain, where the energy of the target signal is integrated into a well-focused 2-D peak, enabling the high-precision target parameter estimation and finely focused ISAR imaging. The experimental results from both simulation and real-measured data validate the effectiveness of the proposed algorithm.