卡尔曼滤波相位解缠及其与其他方法的对比分析

Kalman Filter Phase Unwrapping Algorithm and Comparison and Analysis with Other Methods

  • 摘要: 一般相位解缠算法通常在相位解缠前首先需要借助滤波算法进行噪声消除,随后才能相位解缠,以保证解缠的质量和顺利实施。卡尔曼滤波将相位解缠问题转化为状态估计问题,实现相位解缠与噪声消除一并处理,简化了数据处理过程。利用真实干涉SAR数据进行实验,采用卡尔曼滤波相位解缠算法进行处理,并与其他几种较常用相位解缠算法的结果从目视和定量两方面进行比较和分析。验证了卡尔曼滤波相位解缠方法在滤波和解缠效果方面的有效性和可行性,可以获得较为可靠的解缠结果。

     

    Abstract: The general phase unwrapping algorithm usually need use some filtering algorithms to eliminate noise firstly,and then to phase unwrapping,so as to ensure the quality of unwrapping and successful implementation.The Kalman Filter overcomes this drawback and transforms the phase unwrapping problem into state estimate issue to deal with phase unwrapping and noise eliminating at the same time,simplifying data processing.Using Kalman Filter phase unwrapping method to deal with real InSAR data,it is to compare and analyze its result with these of other commonly used algorithms from both aspect of vision and quantitation.It is verified that Kalman Filter phase unwrapping algorithm has effectiveness and feasibility in the respect of noise restraining and unwrapping effect and it can gain more reliable unwrapping result.

     

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