摘要
在基于时间到达差(Time Difference Of Arrival,TDOA)的定位估计算法中,CHAN算法计算量小,能够在视距(Line Of Sight,LOS)传播环境下获得较高的定位精度,因而被广泛应用。但是在非视距传播环境(Non-Line Of Sight,NLOS)下,该算法的定位性能会明显下降。因为在非视距情况,尤其是密集城区,由于建筑物等障碍物的存在使得无线电信号无法直线传播,这就引入了NLOS误差;而CHAN算法中的加权矩阵只考虑了系统误差,无法消除NLOS误差。文中在基于视距环境下CHAN算法的研究基础上,对非视距引入的NLOS误差的统计特性进行分析,给出一种在NLOS情况下,通过优化非视距TDOA测量值误差的方法来改善非视距下的CHAN算法性能,并通过仿真分析了CHAN算法在不同环境模型下的定位性能。仿真结果表明,改善的CHAN算法在NLOS环境下能取得较好的定位性能。
Among the positioning algorithms based on TDOA,CHAN algorithm is widely used for its small calculation and high positio-ning accuracy in LOS propagation environment. However,CHAN positioning performance decreases significantly when the propagation condition is NLOS. In the case of NLOS,especially in dense urban areas,the radio signals can’ t travel in straight lines with the existence of the obstacles such as tall buildings,thus introducing the NLOS error. While the weighted matrix in CHAN algorithm is unable to elimi-nate the NLOS error for it only considers system error. Based on the study of CHAN algorithm in LOS environment and the analysis of statistical characteristics of NLOS error,a method which improves the CHAN performance in the case of NLOS by optimizing the NLOS TDOA measurement error is proposed in this paper. Analysis of CHAN algorithm is done by computer simulation in different environment models. The simulation results show that improved CHAN algorithm can achieve better positing performance.
出处
《计算机技术与发展》
2015年第9期61-65,共5页
Computer Technology and Development
基金
国家自然科学基金资助项目(61271236)
工业和信息化部通信软科学项目(2014-R-50)
江苏政府留学奖学金资助项目
南京邮电大学校项目(NY210007)
南京邮电大学大学生创新训练计划省级重点项目(SZDG2013012)
