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A Novel Correlation Method of Microwave Staring Correlated Imaging Based on Multigrid and LSQR

机译:基于多重网格和LSQR的微波凝视相关成像的新相关方法

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Based on the temporal-spatial stochastic radiation field, microwave staring correlated imaging (MSCI) can achieve high resolution reconstruction of the target. When MCSI is applied in remote sensing, the imaging area will be very large. With the increasing of imaging equation scale, the ill-conditioned problem will seriously influence the resolution of imaging. This paper focuses on the algorithm to realize high-resolution MSCI in condition of large imaging area. Inspired by multigrid (MG) method, we use multigrid (MG) method to decrease the low-frequency error and high-frequency error of the solution by dealing with the imaging equation in different scales. Furthermore, we apply Least Square QR-factorization (LSQR) algorithm to solve the large scale ill-conditioned equation. We name the new algorithm as MG-LSQR. Simulation results show that the proposed algorithm could increase the resolution efficiently in condition of large imaging area.
机译:基于时空随机辐射场,微波凝视相关成像(MSCI)可以实现目标的高分辨率重建。当将MCSI应用于遥感时,成像面积将非常大。随着成像方程规模的增大,病态问题将严重影响成像分辨率。本文重点研究在成像面积较大的情况下实现高分辨率MSCI的算法。受多重网格(MG)方法的启发,我们使用多重网格(MG)方法通过处理不同比例的成像方程来减小解的低频误差和高频误差。此外,我们应用最小二乘QR分解(LSQR)算法来求解大型病态方程。我们将新算法命名为MG-LSQR。仿真结果表明,该算法在成像面积较大的情况下可以有效提高分辨率。

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