雷达学报Issue(1)：25-34,10.DOI:10.12000/JR15055
结合MD自聚焦算法与回波模拟算子的快速稀疏微波成像误差补偿算法
Accelerated Sparse Microwave Imaging Phase Error Compensation Algorithm Based on Combination of SAR Raw Data Simulator and Map-drift Autofocus Algorithm
摘要
Abstract
Sparse microwave imaging is new concept, theory and methodology of microwave imaging, which introduces the sparse signal processing theory to microwave imaging and combines them together to overcome the paradox of increasing system complexity and imaging performance of current Synthetic Aperture Radar (SAR) systems. Traditional airborne SAR systems are facing a phase error problem in the echo which is caused by the non-ideal motion of the aircraft. This phase error could be compensated by autofocus algorithms. But in the sparse microwave imaging, such autofocus algorithm are no longer valid because traditional signal processing based on matched filtering has been replaced with sparse reconstruction. Current autofocus algorithms under sparse constraints are usually based on a two-step iteration, which convergences slowly and costs plenty of computation. In this paper, we introduce the Map-Drift (MD) autofocus algorithm to the accelerated sparse microwave imaging algorithm based on SAR raw data simulator, and propose the novel “MD-SAR raw data simulator autofocus algorithm”. This algorithm keeps the advantages of both accelerated imaging algorithm and MD algorithm, including the fast convergence and accurate compensation of two-order phase error in echo. Compared with current algorithms based on two-step iteration, the propose method convergences fast and effectively.关键词
稀疏微波成像/合成孔径雷达(SAR)/相位误差/自聚焦/子孔径相关/回波模拟算子Key words
Sparse microwave imaging/Synthetic Aperture Radar (SAR)/Phase error/Autofocus/Map-Drift (MD)/SAR raw data simulator分类
信息技术与安全科学引用本文复制引用
张柘,张冰尘,洪文,吴一戎..结合MD自聚焦算法与回波模拟算子的快速稀疏微波成像误差补偿算法[J].雷达学报,2016,(1):25-34,10.基金项目
国家973项目(2010CB731905)“稀疏微波成像的理论、体制和方法研究”Foundation Item：The National Basic Research Program (973 Program) of China under grant 2010CB731905Studies on theory, system, and methodology of Sparse Microwave Imaging （2010CB731905）
