提出一种不敏粒子滤波的相位展开方法.该方法是不敏粒子滤波器与路径跟踪策略以及全方位的局部相位梯度估计相结合的结果,不受模型噪声统计特性和线性条件约束,同时完成噪声消除和相位展开;利用不敏卡尔曼滤波器来进行粒子更新,使重要密度函数能够融入最新观测信息和更加符合真实状态的后验概率分布,从而提高了相位展开精度与效率.仿真和实测数据处理结果验证了本文方法的有效性.%This paper presents a phase unwrapping algorithm based on the unscented particle filter ( UPF) for synthetic-aperture radar (SAR) interferometry. This method provides independence from noise statistics and is not constrained by the nonlinearity of the problem. This technique performs simultaneously noise filtering and phase unwrapping by the optimal data fusion approach. In addition,the importance density funcfion is integrated with the latest observation information and is more in line with the postefior probility distribution of true phase by using an unscented Kaiman filter (UKF) to carry out particle update, which also enhances the accuracy and the efficiency of the proposed method. Simulation and real data processing results validate the effectiveness of proposed method, and show a significant improvement with respect to the EKFPU algorithm and other conventional unwrapping algorithms in some situations.
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