The application discloses a space target large-angle high-resolution
radar imaging space-varying
phase compensation method and
system, a storage medium and an electronic device, and comprises the following steps: acquiring an ISAR original echo, completing a translation compensation and a distance beyond a
cell correction; and converting residual two-dimensional space-varying
phase error compensation into a high-dimensional parameter
estimation problem based on image entropy minimization. A mean value, a step length and a
covariance matrix of a CMA-ES
algorithm are initialized, a candidate solution
population is iteratively generated, and image entropy is calculated after compensation is performed on each group of space-varying phase coefficients to serve as fitness. An optimal individual is screened, a cumulative evolution path and a conjugate path are fused, and
population parameters are adaptively updated. After a convergence condition is met, optimal coefficients are output, and a high-focusing ISAR image is reconstructed. The application overcomes the defects of a traditional gradient
algorithm, such as being prone to local optimization and relying on initial values, utilizes global step length dynamic adjustment and a
covariance adaptive mechanism of CMA-ES, has strong
global optimization capability and
noise robustness, and can still converge stably in a low
signal-to-
noise ratio environment.