A Novel Channel Inconsistency Calibration Algorithm for Azimuth Multichannel SAR Based on Fourth-Order Cumulant

In a high-resolution and wide-swath synthetic aperture radar (SAR) platform, the along-track position error reduces the accuracy of the phase error estimation, which will lead to the failure of aliased signal reconstruction. However, classical subspace-based methods require at least one redundant subaperture to construct signal or noise subspace. To overcome this condition, a robust channel error estimation method is presented, which introduces the higher order cumulants to separate these two subspaces by increasing the spatial degree of freedom. First, the $M$ physically existing subapertures are expanded into $2M-1$ virtual channels to construct the noise subspace more accurately. Then, according to the expanded array configuration, the channel error model and the actual steering vector are modified. Finally, based on the orthogonality of signal and noise subspaces, two sets of constrained minimization formulations are constructed. Due to the coupling between these errors, the phase and along-track position errors can be obtained, respectively, by exploiting the idea of alternate iterations. Besides, compared with classical subspace-based methods, the proposed algorithm can avoid the subspace swap phenomenon under condition of low signal-to-noise ratios because the fourth-order cumulant can efficiently suppress additive Gaussian white noise. Finally, the well-focused SAR images, acquired by the four-channel airborne, GF3-01, and GF3-02 SAR systems, demonstrate the feasibility of the proposed error estimation method.