The Analyzation of SAR Image Adaptive Sidelobe Reduction Algorithms and Experiments

Abstract

Synthetic aperture radar is an active coherent high resolution imaging system. The classical imaging algorithms process the SAR received data by matched filter in two-dimensional frequency domain, and get reconstructed SAR images. In classical imaging algorithms, Fast Fourier Transform is used broadly. Because of the limited frequency domain support of the SAR systems, the system impulse responses in the range and azimuth directions are sinc functions. And the SAR images have great dynamic domain. The ratio of the returned power between the bright and the weak targets reached 50 dB, even higher. The sidelobe of a bright point target can easily obscure and violate the mainlobe of weaker points. So SAR images often demands sidelobe reduction. The conventional sidelobe reduction applies the fixed weighting functions on the whole aperture data, and the conventional weighting approach have to compromise between the degree of sidelobe reduction and imaging resolution. In this paper discusses two adaptively sidelobe reduction algorithms, and compared their processing results with conventional sidelobe reduction methods by the simulated data and the IECAS L\|SAR system raw data.