摘要
卡尔曼滤波将相位解缠转化为状态估计问题,同时实现相位解缠与噪声消除。由于原始雷达信号以及后处理过程中产生的诸多误差,造成相位数据不连续产生局部误差传递,使得解缠结果不准确。提出一种基于掩膜的加权卡尔曼滤波相位解缠算法。该算法通过对包缠数据中的低质量区域进行掩膜处理,对掩膜后的高质量区域进行卡尔曼滤波相位解缠,再对掩膜区域实施加权卡尔曼滤波相位解缠,得到了较为可靠的相位解缠结果。采用仿真数据和ALOS卫星的山东兖矿地区干涉SAR数据进行实验,验证了算法的有效性和可靠性。
The Kalman filter transforms the phase unwrapping problem into the state estimate issue to deal with phase unwrapping and noise eliminating at the same time. But the original radar signal and post-processing producing a lot of errors and others can cause phase discontinuity and local error propagation, unwrapped result is not accurate. Therefore, weighted Kalman filter phase unwrapping algorithm based on mask is proposed. Through the low-quality region in wrapped phase is masked, Kalman filter is implemented in the high-quality region after masked. When the high-quality region is unwrapped correctly, weighted Kalman filter is implemented in the masked off low-quality region, then a reliable unwrapping result is obtained. Using simulated data and InSAR data of ALOS satellite in Shandong Yanzhou mining area, it is verified that the proposed algorithm is effective and reliable.
出处
《计算机工程与应用》
CSCD
2013年第10期10-13,117,共5页
Computer Engineering and Applications
基金
国家自然科学基金(No.40874001)
海岛(礁)测绘技术国家测绘局重点实验室资助项目(No.2010A01)
潍坊学院引进人才博士基金(No.2013BS15)
