Improved SVA method for SAR sidelobe suppression

The existing improved spatially variant apodization(SVA)algorithms cost large computation,cannot depress the sidelobes of synthetic aperture radar (SAR)image effectively,or reduce the energy of the mainlobes.To overcome these problems,an improved SVA algorithm is presented in this paper.Firstly,the impact of the non-integer Nyquist sampling rates on the impulse response function corresponding to the ideal frequency-domain window function is analyzed.Subsequently, to meet the demand of the sidelobe suppression,a new impulse response function is built to get a corresponding frequency-domain window function,and introduce some constraints.Finally,the maximum weights and the minimum weights of SAR data are compared to achieve sidelobe suppression.This algorithm can depress the sidelobes fast and effectively with no loss of the mainlobe energy.The simulation and experimental results confirm the validity of the algorithm.