测绘学报

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一种基于智能搜索策略的UKF相位展开方法

谢先明1,皮亦鸣2   

  1. 1. 电子科技大学
    2. 电子科技大学电子工程学院
  • 收稿日期:2009-11-27 修回日期:2010-03-12 出版日期:2011-12-28 发布日期:2019-01-01
  • 通讯作者: 谢先明

An UKF Phase estimate method based on the artificial-intelligence search strategy

  1. 1. University of Electronic and Science and Technology of China
    2.
  • Received:2009-11-27 Revised:2010-03-12 Online:2011-12-28 Published:2019-01-01

摘要: 提出一种基于智能搜索策略的UKF干涉相位展开方法。该方法把不敏卡尔曼滤波与人工智能的搜索策略以及全方位的局部相位梯度估计结合起来,实现最佳的信息融合; 该方法同时完成噪声消除及相位展开,避免了传统的方法在相位展开之前首先进行噪声滤波的不足;利用局部频率估计器直接从复干涉图的功率谱中提取相位梯度,解决了相位展开中的“坡度欠估计”问题。仿真和实测数据处理结果验证了本文方法的有效性,且与基于扩展卡尔曼滤波的相位展开算法(EKFPU)以及一些传统方法相比具有较高的精度和较强的稳健性。

Abstract: Combining an unscented kalman filter (UKF) with artificial-intelligence search strategy and an omnidirectional local phase slope estimator,this paper presents a new phase unwrapping algorithm based on the unscented kalman filtering (UKF). This technique performs simultaneously noise filtering and phase unwrapping by the optimal data fusion approach. Phase slope will be estimated directly from the sample frequency spectrum of the complex interferogram by a local frequency estimator and the underestimation of phase slope is overcome. Simulation and real data processing results validate the effectiveness of proposed method, and show a significant improvement with respect to the extended-kalman-filter phase unwrapping (EKFPU) algorithm and some conventional phase unwrapping algorithms in some situations.