Computer Engineering and Applications ›› 2017, Vol. 53 ›› Issue (3): 266-270.DOI: 10.3778/j.issn.1002-8331.1606-0213

Previous Articles    

Adaptive Square Root Cubature Kalman Filter and its application in GPS dynamic single point positioning

SUN Peng1, ZHAO Changsheng1, WU Wenyu2, ZHANG Likai1, YANG Mengyuan1   

  1. 1.School of Geodesy and Geomatics, Jiangsu Normal University, Xuzhou, Jiangsu 221116, China
    2.Wuhan Space Vision Technology Limited Company, Wuhan 430205, China
  • Online:2017-02-01 Published:2017-05-11

自适应SRCKF在GPS动态单点定位中的应用

孙  鹏1,赵长胜1,吴文宇2,张立凯1,杨梦圆1   

  1. 1.江苏师范大学 地理测绘与城乡规划学院,江苏 徐州 221116
    2.武汉航天远景科技股份有限公司,武汉 430205

Abstract: Square Root Cubature Kalman Filter(SRCKF)exhibits excellent?numerical stability and efficiency. In order to improve the precision of the filtering when the dynamic model is inaccurate, this paper applies two kinds of adaptive factors to decrease the weight of the forecasting information, and the algorithm is used to process the data of GPS dynamic single point positioning. Finally, GPS pseudo-range observations of aerial photography craft are used to verify that the algorithm is useful.

Key words: cubature rule, square root filter, adaptive factor, dynamic single point positioning

摘要: 平方根容积卡尔曼滤波具有良好的数值稳定性与滤波效率,针对滤波中状态函数与实际不符带来的误差对滤波造成的影响,将基于预测残差统计量的自适应因子和最优自适应因子与平方根容积卡尔曼滤波算法相结合以降低预测信息在滤波中的权重,并将平方根容积卡尔曼滤波与带自适应因子的平方根容积卡尔曼滤波用于GPS动态单点定位数据处理,最后用航摄飞机实测GPS动态观测数据验证了算法的有效性。

关键词: 容积准则, 平方根滤波, 自适应因子, 动态单点定位