Focusing highly squinted data with motion errors based on modified non-linear chirp scaling

The motion compensation (MOCO) plays a significant role to accommodate the motion errors caused by atmosphere turbulence and/or aircraft maneuvers in airborne synthetic aperture radar configurations. In broadside or small squint cases, the well-focused image can be obtained by the typical two-step MOCO to have the quadratic motion errors compensated. However, with the increasing of squint angle, not only the high-order motion errors, but also the azimuth-variant errors must be taken into account. In this study, a modified non-linear chirp scaling (MNLCS) algorithm is proposed to handle this problem in highlysquinted case. The key is to use the method of series reversion to cover the high-order motion errors, the MNLCS to precondition the data to process the azimuth-variant components and a series expansion to obtain an accurate form of the signal spectrum. The skewed spectrum in highly-squinted case is reduced through the use of a linear range cell migration correction. The simulated results have shown the MNLCS algorithm can handle data with more complicated geometries than the previous algorithm.