| 基于UKF的GPS非线性动态滤波算法 |
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| 引用本文： | 彭竞,李献球,王飞雪.基于UKF的GPS非线性动态滤波算法[J].全球定位系统,2005,30(6):30-34. |
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| 作者姓名： | 彭竞 李献球 王飞雪 |
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| 作者单位： | 1. 国防科技大学电子科学与工程学院卫星导航定位研发中心,湖南,长沙,410073
2. 北京市5136信箱,北京,100094 |
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| 基金项目： | 新世纪优秀人才支持计划资助 |
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| 摘 要： | 介绍了一种Unscented卡尔曼滤波算法，它通过确定性采样获得一组采样点，可获得更多的观测假设，对系统状态统计特性的估计更加准确，同时该算法无需对系统方程进行线性化，避免了传统的EKF算法由于线性化引入的误差。本文将UKF算法用于GPS非线性动态滤波技术中，建立了仿真模型并定义了仿真条件，与EKF算法的仿真结果相比，在系统状态统计特性未知的情况下，UKF算法对系统状态的估计更准确，定位精度更高。
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| 关 键 词： | GPS EKF UKF 非线性系统 |
| 文章编号： | 1008-9268(2005)06-0030-04 |
| 修稿时间： | 2005年9月6日 |
GPS Nonlinear Dynamic Filter Algorithm Based on Unscented Kalman Filter |
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| PENG Jing,LI Xian-qiu,WANG Fei-xue.GPS Nonlinear Dynamic Filter Algorithm Based on Unscented Kalman Filter[J].Gnss World of China,2005,30(6):30-34. |
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| Authors: | PENG Jing LI Xian-qiu WANG Fei-xue |
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| Institution: | PENG Jing~1,LI Xian-qiu~2,WANG Fei-xue |
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| Abstract: | This paper introduces an algorithm of Unscented Kalman Filter.This approach gets a set of sigma points by deterministic sampling,and it could get more observed hypotheses and estimate the statistical characteristic of the system states more exactly.At the same time,it is not necessary to linearize the system equations,and it avoids the error caused by the linearization in the traditonal Extended Kalman Filter.In this paper,the UKF is used for GPS nonlinear dynamic filter.It puts forward a simulation model and defines the simulation condition.With the unknown statistical characteristic of the system states,the performances of EKF and UKF are compared by simulation,it is shown that the performance of the UKF algorithm is more precise and has higher accuracy in positioning. |
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| Keywords: | GPS Extended Kalman Filtering Unscented Kalman Filter nonlinear system |
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