An Improved Nonlinear Chirp Scaling Algorithm for a Squinted SAR of Curvilinear Trajectory

For a maneuverable platform synthetic aperture radar (SAR), the track can be curvilinear. Thus, the conventional imaging algorithms that use linear trajectory models become questionable. In this paper, the true range history (curvilinear trajectory) is accurately expressed using higher-order approximation. Then, an accurate Two-Dimension (2-D) spectrum is derived based on the method of series reversion (MSR). Furthermore, an improved nonlinear chirp scaling algorithm (NLCSA) is presented to correct space-variant range cell migration (RCM) and range variance on secondary range compression (SRC). Finally, the simulation results show that the presented algorithm can effectively focus large scene and high squint angle in SAR of curvilinear trajectory.