东南大学学报(自然科学版)
東南大學學報(自然科學版)
동남대학학보(자연과학판)
JOURNAL OF SOUTHEAST UNIVERSITY
2013年
6期
1135-1140
,共6页
邵震洪%杨琼%吴怡%Mohamed Mohsen%沈连丰
邵震洪%楊瓊%吳怡%Mohamed Mohsen%瀋連豐
소진홍%양경%오이%Mohamed Mohsen%침련봉
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
車輛間協作%多普勒頻移%擴展卡爾曼濾波%無跡卡爾曼濾波器%車輛定位
차량간협작%다보륵빈이%확전잡이만려파%무적잡이만려파기%차량정위
inter-vehicle cooperation%Doppler carrier frequency offset%extended Kalman filter%un-scented Kalman filter%vehicle positioning
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。
為提高車輛間自組織網(VANET)中車輛定位的精度,提齣瞭一種基于車輛間協作和多普勒頻移的算法(CDCFO),併採用無跡卡爾曼濾波器(UKF)來進行車輛定位。多車輛間相互關聯的狀態和測量信息,如位置、速度以及專用近程車間通信(DSRC)信號的多普勒頻移等,通過協作共享可以被有效融閤和處理,來提高對車輛運動狀態估計和預測的準確度;UKF 直接使用非線性測量方程,因此可以避免擴展卡爾曼濾波器(EKF)在對非線性測量方程進行線性化時忽略高階項帶來的誤差。計算機分析和倣真結果錶明,相對于常規 GPS 和 CDCFO-EKF 算法,提齣的CDCFO-UKF 算法對車輛目標的位置估計平均誤差和均方根誤差等定位性能都有較大提高。
위제고차량간자조직망(VANET)중차량정위적정도,제출료일충기우차량간협작화다보륵빈이적산법(CDCFO),병채용무적잡이만려파기(UKF)래진행차량정위。다차량간상호관련적상태화측량신식,여위치、속도이급전용근정차간통신(DSRC)신호적다보륵빈이등,통과협작공향가이피유효융합화처리,래제고대차량운동상태고계화예측적준학도;UKF 직접사용비선성측량방정,인차가이피면확전잡이만려파기(EKF)재대비선성측량방정진행선성화시홀략고계항대래적오차。계산궤분석화방진결과표명,상대우상규 GPS 화 CDCFO-EKF 산법,제출적CDCFO-UKF 산법대차량목표적위치고계평균오차화균방근오차등정위성능도유교대제고。
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 algo-rithm.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 estima-ting and predicting accuracy of the vehicle state.Since the UKF directly uses the nonlinear measure-ment equation,it can avoid the error which is caused by omitting the high-level items during the lin-earization 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.