Performance Evaluation of Frequency-Domain Algorithms for Chirped Low Frequency UWB SAR Data Processing

This paper studies the performance of the frequency-domain algorithms (FDAs) for low-frequency ultra-wideband synthetic aperture radar (UWB SAR) data processing. First, a generalized theoretical derivation of the FDAs is presented from the viewpoint of SAR signal processing. The derivation not only provides a deeper understanding to the imaging principle of the extended Omega-K algorithm (EOKA), but also makes it compatible and comparable with the other FDAs. Second, the performance comparison on different FDAs is made based on theoretical analysis, simulation and experimental data. The comparison results show that the Omega-K algorithm (ωKA) has the highest imaging precision in the ideal case (i.e, no motion error), but its application is limited by the poor ability of compensating motion errors. In contrast, the EOKA and nonlinear chirp scaling algorithm (NCSA) have excellent performance on dealing with the motion error, but they can only be applied under specific preconditions. Besides, as cetner frequency gets lower, the fractional bandwidth and integration angle get larger, the imaging precision of NCSA greatly decreases, while the ωKA and EOKA still keep high precision.