| Summary: | A situation in which an image is combined with multiple images to form interferometric pairs is often observed in small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) deformation inversion, and this situation leads to a near linear correlation between the column vectors of the model design matrix. The Liu-type estimator introduces the parameters k and d into the normal equation to reduce the condition number of the design matrix and to improve the fitting properties. As the parameter k is mainly used to reduce ill-posed problems of the design matrix, the value of k is not limited. However, the value of k, as determined by existing methods, is usually too large or too small. Since the calculation of the mean square error involves true values, the parameter d is often affected by errors in the estimation results, which leads to the decreased accuracy of Liu-type estimation results. To determine the optimal value of d, an iterative Liu-type estimator is proposed to eliminate errors. Then, the L-curve optimization method and iterative Liu-type estimator are combined to achieve the optimal k. The reliability and accuracy of the methods are analyzed through SBAS-InSAR deformation experiments. The experimental results show that after using the L-curve method and an iterative operation to optimize k and d, the accuracy of the Liu-type estimator based on parameter optimization is clearly improved compared with that of the ridge estimator and the Liu-type estimator.
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