CBP-based multichannel autofocus for near-field SAR imaging

Multichannel Autofocus (MCA) assumes that there exits a region of low return in the focused image and solves for the correction filter that minimizes the energy in the presumed low-return region. Provided that the lowreturn region is precisely known, the algorithm yields a superior restoration compared to other autofocus methods. Fourier-domain MCA (FMCA) is a generalization of this algorithm that works for practical ranges of look angles. However, both MCA and FMCA assume a planar wavefront, which makes them inapplicable to near-field imaging scenarios where there is a significant amount of wavefront curvature. We propose an autofocus algorithm that builds upon MCA, with a modification that takes into account wavefront curvature. In this setting, the demodulated data can no longer be interpreted as 2-D Fourier samples of the underlying image. Therefore, we make use of the linear relationship between the correction filter and the reconstructed image via Convolution Backprojection (CBP) along curves. Under the far-field assumption, our algorithm is equivalent to FMCA with a Jacobian-weighted 2-D periodic sinc-kernel interpolator when the presumed low-return regions are the same. However, our algorithm has the distinct advantage of being able to select the presumed low-return region within a continuous set of coordinates. We present simulation results showing that our algorithm outperforms other algorithms for the case with wavefront curvature.