Adaptive Spatially Variant Apodization for 2-D Sidelobe Suppression in Near-Field SAR Images

In synthetic aperture radar (SAR), sidelobes inevitably exist in the matched filtering-based imaging results, which severely affect image interpretation. Unfortunately, under the near-field condition, the wavenumber spectrum is spatially variant, which means that there is no window function that can effectively weight the wavenumber spectra of all targets at the same time, making sidelobe suppression particularly challenging. To address this issue, an adaptive spatially variant apodization (SVA) method is proposed in this article. In the proposed method, wavenumber domain weighting is equivalently implemented by a nine-point convolver in the image domain. By adjusting this image domain convolver with pixel position, the method achieves an adaptive change of the weighted region, thereby effectively weighting the wavenumber spectra of different targets. To avoid the mainlobe broadening caused by weighting, multiapodization technique is applied to the results after convolution. By transforming multiapodization into solving a constrained minimization problem, the method achieves the goal of effectively suppressing the sidelobes without reducing the imaging resolution. Experiments on both numerical simulation and measured data verify that the proposed method can suppress the sidelobes by about 10 dB without sacrificing the image resolution.