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An estimation method for InSAR interferometric phase using correlation weight joint subspace projection

机译:相关加权联合子空间投影的InSAR干涉相位估计方法

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In this article, we propose a method to estimate the synthetic aperture radar interferometry (InSAR) interferometric phase based on the model of correlation weight joint pixel by using the joint subspace projection technique. In the method, the correlation weight joint data vector is constructed and the data vector can make the noise subspace dimension of the corresponding weight covariance matrix which is not affected by the coregistration error, thus avoiding the trouble of calculating the noise subspace dimension before estimating the InSAR interferometric phase. The method takes advantage of the coherence information of neighboring pixel pairs to auto-coregister the SAR images and employs the projection of the joint signal subspace onto the corresponding joint noise subspace to estimate the terrain interferometric phase. The method can auto-coregister the SAR images and reduce the interferometric phase noise simultaneously. Theoretical analysis and computer simulation results show that the method can provide accurate estimate of the interferometric phase (interferogram) even when the coregistration error reaches one pixel. The effectiveness of the method is verified via simulated data and real data.
机译:在本文中,我们提出了一种基于联合子空间投影技术的基于相关权重联合像素模型的合成孔径雷达干涉测量(InSAR)干涉相位估计方法。该方法构造了相关权重联合数据向量,该数据向量可以使相应权重协方差矩阵的噪声子空间维数不受共心误差的影响,从而避免了在估计噪声维数之前计算噪声子空间维数的麻烦。 InSAR干涉相。该方法利用相邻像素对的相干信息来自动共对准SAR图像,并采用联合信号子空间到相应联合噪声子空间上的投影来估计地形干涉相位。该方法可以自动共配准SAR图像并同时减少干涉相位噪声。理论分析和计算机仿真结果表明,该方法即使在主偏误差达到一个像素时也能提供干涉相位(干涉图)的准确估计。通过仿真数据和实测数据验证了该方法的有效性。

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