关键词: 合成孔径雷达, 盲同态解卷积, 相位解缠绕, 平滑滤波, 模糊核

Abstract:

Synthetic aperture radar (SAR) image suffers from the deterioration due to the unknown phase error caused by unstable platform and atmosphere perturbation. A novel autofocus algorithm is presented in this paper to obtain phase error. The proposed algorithm is put forward based on the differences of smoothness properties for log-spectrum of motion error and image reflectivity. The differences could be employed to discriminate the motion error and reflectivity function. The log-spectrum of motion error is a slow-varying function, while the log-spectrum of image reflectivity owns some statistical properties which is similar to jagged function distribution. Then, motion error can be separated by applying a proper smoothing filter to the log-spectrum of blurred image. We set up a model that the log-amplitude spectrum and phase of spectrum for blurred image are processed through different smoothing filter functions. The log-spectrum of amplitude is recovered by current de-noising algorithms and phase is restored through phase-unwrapping and smoothing filter. It is demonstrated that the amplitude and phase of motion error can be reliably restored from the blurred SAR image and refiectivity function of image can be accurately reconstructed. In this paper, Riesz basis is constructed by scaling function of Daubechies wavelet function. An orthogonal subspace is built. Finally, a smoothing filter is applied to the derivative of compressed data. Then, motion error can be obtained. In order to demonstrate the performance of the proposed method, simulation data and real data are processed to verify the proposed algorithm. The analysis illustrates that this algorithm could obtain accurate motion error and possesses higher implementation efficiency.

Key words: synthetic aperture radar, blind homomorphic deconvolution, phase unwrapping, smoothing filter, blurring kernel