改进的粒子滤波及其在GPS动态定位中的应用

The Improved Method of Particle Filtering and Application for Kinematic GPS Positioning

针对城市环境中GPS动态定位系统的特点,提出了一种基于粒子滤波的GPS动态定位算法。与传统卡尔曼滤波算法相比,该算法利用观测伪距误差分布建立重要的密度函数,能够处理噪声符合非高斯分布的情况,且无需对观测方程线性化,提高了GPS动态定位的精度。通过实际算例分析,验证了该算法的有效性。

According to the characteristic of kinematic GPS positioning in urban environment, an algorithm of kinematic GPS positioning based on particle filtering is proposed. Compared with algorithm of traditional Kalman filtering, the new algorithm uses the pseudo- range error distribution establish importance density, and can deal with error appearing non- Gaussian distribution without linearizing observation equation. It is showed from the actual example that the new algorithm improves accuracy of kinematic GPS positioning.