| 改进的粒子滤波及其在GPS动态定位中的应用 |
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| 引用本文： | 秦臻.改进的粒子滤波及其在GPS动态定位中的应用[J].全球定位系统,2010,35(5):25-28. |
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| 作者姓名： | 秦臻 |
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| 作者单位： | [1]中国矿业大学国土环境与灾害监测国家测绘局重点实验室,江苏徐州221116 [2]中国矿业大学江苏省资源环境信息工程重点实验室,江苏徐州221116〉 |
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| 基金项目： | 教育部博士点基金，江苏省自然科学基金 |
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| 摘 要： | 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。
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| 关 键 词： | 动态定位 粒子滤波 卡尔曼滤波 定位精度 |
The Improved Method of Particle Filtering and Application for Kinematic GPS Positioning |
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| QIN Zhen.The Improved Method of Particle Filtering and Application for Kinematic GPS Positioning[J].Gnss World of China,2010,35(5):25-28. |
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| Authors: | QIN Zhen |
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| Institution: | QIN Zhen (1. China University of Mining and Technology ,Key Laboratory for Land Environment and Disaster Monitoring of SBSM, Xuzhou J iangsu 221116, China 2. China University of Mining and Technology, Jiangsu Key Laboratory of Resources and Environmental Information Engineering, Xuzhou Jiangsu 221116, China) |
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| Abstract: | 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. |
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| Keywords: | Dynamic positioning~ particle filtering Klman filtering positioning accuracy |
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