Fast non-iterative imaging algorithm for CLSAR

Though curvilinear synthetic aperture radar (CLSAR) has the three-dimensional (3-D) imaging capability, the images obtained by non-parametric methods are of little practical use because the data collected by CLSAR is not full volume but sparse data in 3-D frequency space. In this paper, a fast non-iterative imaging (FNII) method is proposed for extracting the scatterer´s 3-D features in CLSAR. Based on the loose coupling between the range and cross-range parameters, the new algorithm first obtains the range estimates via subspace techniques, then estimates the cross-range parameters from the reformed data with the above range estimates, and finally calculates all the amplitudes from the original data. Without iterative produce, FNII algorithm is computational efficiency. Simulation results indicate that the target image obtained via FNII is similar to the original image and comparison with another efficient algorithm LODIPS, FNII has less computational cost and lower SNR threshold.