PWFT-RD: A High-Quality and Low-Complexity ISAR Imaging Approach for Maneuvering Target - Jiayin Xue; Qinyu Zhang; Ye Wang; Shushi Gu; Tingting Zhang (IEEE Access, 2018)
For inverse synthetic aperture radar imaging, high-quality and real-time performances are two essential indicators in many real applications. Due to the complex motion of the maneuvering target, the Doppler frequency is generally time varying. Consequently, it is difficult for most imaging algorithms to satisfy these two indicators simultaneously. The approaches based on the traditional range-Doppler (RD) algorithm can generally achieve rapid imaging but often encounter image blurring problems while the range-instantaneous-Doppler (RID) algorithms can generate high-quality images but at the cost of tremendous computational complexity. Aiming at this issue, we propose a new approach, termed power-weighting Fourier transform-based range-Doppler (PWFT-RD), to achieve a better comprehensive performance of the image quality and computational cost simultaneously. Specifically, we first build up the generalized signal model to describe the target motion with high-order dynamics. Second, we propose the PWFT which has the property of modulating expanded the signal spectrum into a keen-edged envelope. After that, we implement high-accuracy motion compensation (MOCOMP) by formulating the high-order parameter estimation as the least-squares problem and finally develop the PWFT-RD approach. Analysis and comparison experiments are designed to validate the effectiveness of our approach on employing PWFT for improving MOCOMP accuracy and enhancing the azimuth focus quality. In particular, the PWFT-RD approach shows much better real-time performance than RID algorithms thanks to its linear and blind processing attributes with quite low computational complexity.