As a high resolution imaging sensor, synthetic aperture ladar data contain phase-error whose source include
uncompensated platform motion and atmospheric turbulence distortion errors. Two previously devised methods, rank
one phase-error estimation algorithm and iterative blind deconvolution are reexamined, of which a hybrid method that
can recover both the images and PSF's without any a priori information on the PSF is built to speed up the convergence
rate by the consideration in the choice of initialization. To be integrated into spotlight mode SAL imaging model
respectively, three methods all can effectively reduce the phase-error distortion. For each approach, signal to noise ratio,
root mean square error and CPU time are computed, from which we can see the convergence rate of the hybrid method
can be improved because a more efficient initialization set of blind deconvolution. Moreover, by making a further
discussion of the hybrid method, the weight distribution of ROPE and IBD is found to be an important factor that affects
the final result of the whole compensation process.
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