基于改进卡尔曼滤波的北斗GPS联合定位算法
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引用本文:彭 勇1,陈俞强2.基于改进卡尔曼滤波的北斗GPS联合定位算法[J].计算技术与自动化,2018,(2):59-62
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彭 勇1,陈俞强2 (1.东莞职业技术学院广东 东莞 5238082.广东工业大学广东 广州 510006) 
中文摘要:在观测条件较差的情况下,单系统卫星可见性不佳,导航定位精度降低甚至无法定位,组合卫星导航系统增加了可见卫星数,可以改善定位结果。本文对BD2/GPS组合定位算法进行了研究,建立了联合差分定位系统在初始化阶段和解算阶段的数学模型,并将平方根平淡卡尔曼滤波算法应用于建立的联合差分定位系统,实验结果表明,该算法有效提高了卫星定位精度和稳定性。
中文关键词:北斗导航  联合定位  卡尔曼滤波
 
BD2/GPS Combined Positioning Algorithm Based on Improved Kalman Filtering
Abstract:Under poor observation conditions, single navigation system usually has lower visibility and declined positioning accuracy,combined navigation system can improve the satellite visibility and improve positioning accuracy. BD2/GPS combined positioning algorithm was studied,the mathematical models of the initialization phase and solver phase in the GPS/BD2 combined differential positioning system were established. The traditional Kalman filter has more much iteration number and high sensitivity to the initial position and the divergence problem,aiming at these defects,the square-root unscented Kalman filter was applied to the GPS/BD2 combined differential positioning system. The experimental results showed that the new algorithm could improve the BD2/GPS combined positioning precision and stability effectively.
keywords:beidou navigation  combined positioning  Kalman filtering
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