Inverse synthetic aperture lidar imaging and compensation in slant weak compressible turbulence

To systematically study the effect of oblique compressible turbulence on inverse synthetic aperture lidar (ISAL) imaging, the atmospheric random phase screen with modified compressible turbulence spectrum is numerically simulated by using FFT spectral inversion method. Using Kirchhoff approximation and convolutional inverse projection algorithm, ISAL imaging of rough surfaces (rough square plates and rough circular plates), rough shapes and rough bodies with different roughness under various compressible turbulence intensities is realized. The analysis shows that the stronger the turbulence, the worse the image quality. The phase gradient self-focusing (PGA) algorithm is used to compensate for the ISAL image resolution caused by compressible turbulence. In the case of weak compressible turbulence, the focusing effect of the image is effectively improved, and the shape of the rough target can be basically distinguishable, thus improving the image quality. However, the image interference and damage caused by medium-strong compressible turbulence are relatively large. The useful information about the target is very small, so the only PGA compensation algorithm can't recover the image of the target.