引用本文: 何平, 许才军, 温扬茂, 丁开华, 王琪. 时序InSAR的误差模型建立及模拟研究[J]. 武汉大学学报 ( 信息科学版), 2016, 41(6): 752-758.
HE Ping, XU Caijun, WEN Yangmao, DING Kaihua, WANG Qi. Analysis and Simulation for Time Series InSAR Error Model[J]. Geomatics and Information Science of Wuhan University, 2016, 41(6): 752-758.
 Citation: HE Ping, XU Caijun, WEN Yangmao, DING Kaihua, WANG Qi. Analysis and Simulation for Time Series InSAR Error Model[J]. Geomatics and Information Science of Wuhan University, 2016, 41(6): 752-758.

## Analysis and Simulation for Time Series InSAR Error Model

• 摘要: 基于时序InSAR函数模型,分别建立了单主影像和多主影像时序InSAR误差模型,在理论上完善了时序InSAR数学模型。利用构建的随机误差模型,模拟试验研究了随机误差模型对时序InSAR待估参数精度的影响。结果表明,与等权模型相比较,加权模型(随机误差模型)估计的参数精度有一定提高;但由于加权条件下的参数估计模型复杂、计算效率低,目前利用等权方法进行时序InSAR的参数估计更简便易行。

Abstract: Based on the function model of TS-InSAR (time series interferometric synthetic aperture radar) technique, this paper establishes stochastic function models (weighted/equal-weight) for single-master and multi-master image TS-InSAR method respectively to enrich the mathematical model of TS-InSAR. A simulation test is used to estimate the precision of model parameters for our equal-weighted function model (stochastic model). Compared to the equal-weight model, the precision of deformation parameters shows little improvement over the weighted model. However, complications in the weighted model means that much disk-space is consumed with low computational efficiency. Most computers therefore cannot undertake TS-InSAR analysis tasks with reasonable hardware configuration. At present, the equal-weight model is feasible for TS-InSAR.

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