测绘通报 ›› 2017, Vol. 0 ›› Issue (4): 17-20.doi: 10.13474/j.cnki.11-2246.2017.0111

• 学术研究 • 上一篇    下一篇

后向平滑与抗差估计融合的SRCKF滤波

孙鹏, 赵长胜, 谭兴龙, 张立凯   

  1. 江苏师范大学地理测绘与城乡规划学院, 江苏 徐州 221116
  • 收稿日期:2016-07-22 修回日期:2016-12-31 出版日期:2017-04-25 发布日期:2017-05-05
  • 作者简介:孙鹏(1991—),男,硕士生,研究方向为GNSS数据处理.E-mail:spcxs@sohu.com
  • 基金资助:
    江苏省自然科学青年基金(BK20150236);江苏师范大学研究生科研创新计划重点项目(2016YZD021)

Square-root Cubature Kalman Filter with Backward-smoothing and Robust Estimation

SUN Peng, ZHAO Changsheng, TAN Xinglong, ZHANG Likai   

  1. School of Geodesy and Geomatics, Jiangsu Normal University, Xuzhou 221116, China
  • Received:2016-07-22 Revised:2016-12-31 Online:2017-04-25 Published:2017-05-05

摘要: 将后向平滑平方根容积卡尔曼滤波用于GPS动态单点定位数据处理,并探讨了粗差对后向平滑滤波的影响。借鉴经典卡尔曼滤波抗差估计思想,给出平方根容积卡尔曼滤波的抗差算法以抵抗量测粗差,而当判断不含粗差时使用后向平滑算法,在有效提高滤波精度的同时避免了抗差滤波对每个历元都需进行迭代运算。实测GPS动态数据验证了算法的有效性。

关键词: 非线性滤波, 平方根容积卡尔曼滤波, 抗差滤波, 后向平滑

Abstract: Backward-smoothing square-root cubature Kalman filter(BS-SRCKF) is used to caculate observation data of GPS dynamic single point positioning,and the gross errors' bad influence on backward-smoothing filter is analyzed in this article. In order to reduce gross errors' impacts, robust SRCKF is put forward referring to robust Kalman filter. And when coarse errors don't exist,backward-smoothing filter can be used to improve the precision of the results and avoid iterative computation if using robust filter each epoch.Measured data is adopted to prove that the algorithm is effective.

Key words: nonlinear filtering, SRCKF, robust filter, backward smoothing

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