摘要
在铁路场景下,基于通信的无线网络定位技术中的定位误差主要来自系统测量误差,且参与定位的基站数目有限。文中结合TDOA算法和AOA算法中系统测量误差在定位误差中影响的互异特性,并利用铁轨路径方程,采用TDOA/AOA数据融合算法,有效地减小了系统测量误差带来的定位影响,提高了定位精度。在仿真实验中,用定位均方根误差作为评价指标,对TDOA算法、AOA算法和TDOA/AOA数据融合算法分别在不同条件下进行仿真分析。结果表明,在铁路场景下,本算法的定位均方根误差要小于TDOA算法和AOA算法,即该数据融合算法具有更好的定位性能。
In the railway scenario, based on wireless network location technology, the systematic measurement error leads to the location error, and the number of base stations which can locate is limited. In this paper ,a TDOA/AOA data fusion algorithm is proposed, which can effectively reduce the location error and improve the accuracy. In this aigorithm, TDOA algorithm, AOA algorithm, and the path equation are combined. In the simulation experiment, compared with TDOA algorithm and AOA algorithm, TDOA/AOA data fusion algorithm has the smaller location root-mean-square error under different simulation conditions. Result shows this algorithm has better location performance.
出处
《计算机技术与发展》
2013年第4期75-78,共4页
Computer Technology and Development
基金
国家自然科学基金资助项目(60830001)
轨道交通控制与安全国家实验室项目(RCS2008ZZ007)
中央高校基本科研业务费(2010JBZ008)
长江学者和创新团队发展计划资助项目(IRT0949)
关键词
铁路场景
TDOA
AOA
数据融合
定位
railway scenario
time difference of arrival
angle of arrival
data fusion
location
