[1]邵震洪,杨琼,吴怡,等.一种基于协作和多普勒频移的车辆定位算法[J].东南大学学报(自然科学版),2013,43(6):1135-1140.[doi:10.3969/j.issn.1001-0505.2013.06.001]
 Shao Zhenhong,Yang Qiong,Wu Yi,et al.An algorithm based on cooperation and Doppler carrier frequency offset for vehicle positioning[J].Journal of Southeast University (Natural Science Edition),2013,43(6):1135-1140.[doi:10.3969/j.issn.1001-0505.2013.06.001]
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一种基于协作和多普勒频移的车辆定位算法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
43
期数:
2013年第6期
页码:
1135-1140
栏目:
信息与通信工程
出版日期:
2013-11-20

文章信息/Info

Title:
An algorithm based on cooperation and Doppler carrier frequency offset for vehicle positioning
作者:
邵震洪12杨琼1吴怡3Mohamed Mohsen1沈连丰1
1东南大学移动通信国家重点实验室, 南京 210096; 2南京电讯技术研究所, 南京 210007; 3福建师范大学光电与信息工程学院, 福州 350001
Author(s):
Shao Zhenhong12 Yang Qiong1 Wu Yi3 Mohamed Mohsen1 Shen Lianfeng1
1National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
2Nanjing Telecommunication Technology Institute, Nanjing 210007, China
3College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350001, China
关键词:
车辆间协作 多普勒频移 扩展卡尔曼滤波 无迹卡尔曼滤波器 车辆定位
Keywords:
inter-vehicle cooperation Doppler carrier frequency offset extended Kalman filter unscented Kalman filter vehicle positioning
分类号:
TN92
DOI:
10.3969/j.issn.1001-0505.2013.06.001
摘要:
为提高车辆间自组织网(VANET)中车辆定位的精度,提出了一种基于车辆间协作和多普勒频移的算法(CDCFO),并采用无迹卡尔曼滤波器(UKF)来进行车辆定位.多车辆间相互关联的状态和测量信息,如位置、速度以及专用近程车间通信(DSRC)信号的多普勒频移等,通过协作共享可以被有效融合和处理,来提高对车辆运动状态估计和预测的准确度;UKF直接使用非线性测量方程,因此可以避免扩展卡尔曼滤波器(EKF)在对非线性测量方程进行线性化时忽略高阶项带来的误差.计算机分析和仿真结果表明,相对于常规GPS和CDCFO-EKF算法,提出的CDCFO-UKF算法对车辆目标的位置估计平均误差和均方根误差等定位性能都有较大提高.
Abstract:
To improve the vehicle positioning accuracy in the vehicular ad hoc network(VANET), a new positioning algorithm based on inter-vehicle cooperation and Doppler carrier frequency offset(CDCFO)is put forward. Meanwhile, an unscented Kalman filter(UKF)is applied to the algorithm. The relative state and measure information of multi-vehicles, such as location, velocity, Doppler carrier frequency offset of the dedicated short range communication(DSRC)signal and so on, are effectively fused and processed by cooperation and sharing, in order to improve the estimating and predicting accuracy of the vehicle state. Since the UKF directly uses the nonlinear measurement equation, it can avoid the error which is caused by omitting the high-level items during the linearization of the nonlinear measurement equation in the extended Kalman filter(EKF). The analytic and simulated results show that, compared with the common global positioning system(GPS)and the CDCFO-EKF algorithm, the performance of the proposed CDCFO-UKF algorithm such as the mean error and the root mean square error of the vehicle is improved greatly.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介: 邵震洪(1970—),男,博士生;沈连丰(联系人),男,教授,博士生导师,lfshen@seu.edu.cn.
基金项目: 国家高技术研究发展计划(863计划)资助项目(2008AA01Z205)、国家自然科学基金资助项目(61171081)、江苏省技术创新基金资助项目(BC2012006)、教育部新世纪优秀人才支持计划资助项目(NCET-10-0018).
引文格式: 邵震洪,杨琼,吴怡,等.一种基于协作和多普勒频移的车辆定位算法[J].东南大学学报:自然科学版,2013,43(6):1135-1140. [doi:10.3969/j.issn.1001-0505.2013.06.001]
更新日期/Last Update: 2013-11-20