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 highly‐squinted 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.