Adaptive Tuning Missing-data Amplitude and Phase Estimation Method in Wide Angle SAR
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摘要: 宽角合成孔径雷达(WASAR)由于数据获取时间长，强电磁体、无线频段及方位扰动等因素会造成接收数据出现缺失，采用常规FFT处理方法会造成图像混叠，模糊及高旁瓣等问题。该文首先将自适应幅相估计(ATAPES)方法扩展至2维，其次，将tuning因子引入缺失数据外推过程，提出一种2维缺失数据自适应幅相估计(ATMAPES)方法，算法将最优外推估计结果填补回原始数据得到完整2维频域数据，通过循环迭代得到目标位置及幅度的准确估计结果。仿真实验验证了算法的有效性。Abstract: Wide Angle Synthetic Aperture Radar (WASAR) undergoes a long data collection time and strong electromagnetic, radio frequency interference and azimuth disturbance could lead to missing-data problems. It suffers from aliasing errors, ambiguity and high sidelobes if using FFT method for imaging. This paper first expands the Adaptive Tuning Amplitude and Phase EStimation (ATAPES) method into two-dimension, then, the tuning factor is introduced to data extrapolating process and an Adaptive Tuning Missing-data Amplitude and Phase EStimation (ATMAPES) is proposed. The optimized extrapolated result is filled back into the missing data and the accurate estimating results of target location and amplitude is obtained through circular iteration. The feasibility and effectiveness of the proposed method are validated by simulation results.
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