A Beam-Segmenting Polar Format Algorithm Based on Double PCS for Video
  SAR Persistent Imaging
Jiawei Jiang Yinwei Li Shaowen Luo Ping Li Yiming Zhu
Video synthetic aperture radar (SAR) is attracting more attention in recent
years due to its abilities of high resolution, high frame rate and advantages
in continuous observation. Generally, the polar format algorithm (PFA) is an
efficient algorithm for spotlight mode video SAR. However, in the process of
PFA, the wavefront curvature error (WCE) limits the imaging scene size and the
2-D interpolation affects the efficiency. To solve the aforementioned problems,
a beam-segmenting PFA based on principle of chirp scaling (PCS), called
BS-PCS-PFA, is proposed for video SAR imaging, which has the capability of
persistent imaging for different carrier frequencies video SAR. Firstly, an
improved PCS applicable to video SAR PFA is proposed to replace the 2-D
interpolation and the coarse image in the ground output coordinate system
(GOCS) is obtained. As for the distortion or defocus existing in the coarse
image, a novel sub-block imaging method based on beam-segmenting fast filtering
is proposed to segment the image into multiple sub-beam data, whose distortion
and defocus can be ignored when the equivalent size of sub-block is smaller
than the distortion negligible region. Through processing the sub-beam data and
mosaicking the refocused subimages, the full image in GOCS without distortion
and defocus is obtained. Moreover, a three-step MoCo method is applied to the
algorithm for the adaptability to the actual irregular trajectories. The
proposed method can significantly expand the effective scene size of PFA, and
the better operational efficiency makes it more suitable for video SAR imaging.
The feasibility of the algorithm is verified by the experimental data.