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顾及地形坡度的非线性最小二乘相位解缠
引用本文:刘伟科,刘国林,付政庆.顾及地形坡度的非线性最小二乘相位解缠[J].地球信息科学,2013,15(1):137-143.
作者姓名:刘伟科  刘国林  付政庆
作者单位:1. 山东科技大学测绘科学与工程学院, 青岛 266510;
2. 山东科技大学现代教育中心, 青岛 266510
基金项目:国家自然科学基金项目(41274007,40874001);山东省自然科学基金项目(ZR2012DM001);山东科技大学科研创新团队支持计划项目(2011KYTD103)。
摘    要:InSAR相位解缠是利用干涉合成孔径雷达(InSAR)数据,提取数字高程模型,进行精确差分干涉测量的关键技术之一。然而缠绕的差分相位信息在地形陡峭或者坡度变化较大区域的解缠结果会有较大的误差传递的问题,针对此问题将干涉图中的地形坡度表示为距离向和方位向的局部相位频率,利用局部相位频率估计地形坡度和推导缠绕相位梯度概率密度函数(PG-PDF)参数模型,并将参数模型作为非线性最小二乘相位解缠模型约束条件,平滑不满足要求的缠绕相位梯度,经过迭代求解得到的解缠结果可以在消除噪声的同时减少地形因素的欠采样对相位解缠结果的影响,提高相位解缠的精度。最后,利用欧空局ENVISAT ASAR卫星获取的干涉数据进行实验,验证了算法在解缠精度和对地形的适应性方面优于直接加权的相位解缠算法,在频域下顾及地形的方法能有效克服LS对于相位坡度欠估计的缺点,具有较高的精度和稳定性,能够有效地考虑地形坡度的影响,抑制误差传递。

关 键 词:非线性最小二乘  相位解缠  梯度概率密度  最小二乘模型  地形坡度
收稿时间:2012-08-13;

Nonlinear Least Squares Phase Unwrapping Based on Topographic Slopes
LIU Weike,LIU Goulin,FU Zhengqing.Nonlinear Least Squares Phase Unwrapping Based on Topographic Slopes[J].Geo-information Science,2013,15(1):137-143.
Authors:LIU Weike  LIU Goulin  FU Zhengqing
Institution:1. Geomatics College, Shandong University of Science and Technology, Qingdao 266510, China;
2. Modern Educational Center, Shandong University of Science and Technology, Qingdao 266510, China
Abstract:Interferometric synthetic aperture radar (InSAR) phase unwrapping is one of the key technologies, which, uses the InSAR interference phase, to extract digital elevation model or accurate differential interferometry. However, affected by the porblem that the terrain is streep or the slope is larger, the unwrapping result is bad and causes error transmission in the differential wrapped phase information. In view of this problem, this paper considered to express the terrain slope in the interferogram as the partial phase frequency in range and azimuth direction. Using partial phase frequency to estimate the terrain slope and derivate the wrapped phase gradient probability density function (PG-PDF), the parameter model was used as the constraints of the nonlinear least squares phase unwrapping algorithm, in order to smooth the un-requirements unwrapped phase gradient. After unwrapping, the iterative solution which obtained from the results could eliminate the noise while reducing topographical factors under the condition of less sampling, at the same time the phase unwrapping results improved the accuracy of phase unwrapping. Finally, in the experiments that used the interferometric data obtained from ESA ENVISAT ASAR, it is verified that taking into account the terrain in the frequency domain method could effectively overcome the shortcomings of LS estimates for the phase gradient owed, and the algorithm in unwrapping could effectively give consideration to terrain factors, suppress error propagation, and have precision and adaptability to the terrain slope better than a direct weighted phase unwrapping algorithm.
Keywords:nonlinear least squares  phase unwrapping  gradient probability density  least squares model  topographic slopes
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