Multichannel Autofocus Algorithm for Synthetic Aperture Radar

The autofocus problem in synthetic aperture radar (SAR) is considered, where phase errors in the acquired signal data result in imagery that is improperly focused. We present a new non-iterative approach to SAR autofocus, termed the multichannel autofocus (MCA) algorithm, that allows the image focusing operator to be determined directly using a linear algebraic formulation. Specifically, we exploit the multichannel redundancy of the defocusing operation to create a linear subspace framework, where the unknown perfectly-focused image can be expressed in terms of a known basis expansion. By invoking an additional assumption on the underlying image support, the framework becomes sufficiently constrained so that a unique focusing filter can be solved for. The MCA approach is found to be computationally efficient and robust, and does not require prior assumptions about the characteristics of the SAR scene; the performance of previous SAR autofocus techniques relies upon the accuracy of priors such as sharpness metrics or dominant point scatterers. We present experimental results characterizing the performance of MCA in comparison with conventional autofocus methods, and discuss the practical implementation of the technique.