Following publication of the original article[1],the statement of Competing interests has been added.Competing interests Ying Liu is an Associate Editor for Autonomous Intelligent Systems and was not involved in the e...Following publication of the original article[1],the statement of Competing interests has been added.Competing interests Ying Liu is an Associate Editor for Autonomous Intelligent Systems and was not involved in the editorial review or the decision to publish this article.All authors declare that there are no other competing interests.展开更多
An integrated navlgation based on the kinematic or dynamic state model and the raw measurements has the advantages of high redundancy, high reliability, as well as high ability of fault tolerance and simplicity in cal...An integrated navlgation based on the kinematic or dynamic state model and the raw measurements has the advantages of high redundancy, high reliability, as well as high ability of fault tolerance and simplicity in calculation. In order to control the influences of measurements outliers and the kinematic model errors on the integrated navigation results, a robust estimation method and an adaptive data fusion method are applied. An integrated navigation example using simulated data is performed and analyzed.展开更多
文摘Following publication of the original article[1],the statement of Competing interests has been added.Competing interests Ying Liu is an Associate Editor for Autonomous Intelligent Systems and was not involved in the editorial review or the decision to publish this article.All authors declare that there are no other competing interests.
基金Project supported by the National Outstanding Youth Science Foundation ( No.49825107) and the Natural Science Foundation ( No.40244002 No.40174009) .
文摘An integrated navlgation based on the kinematic or dynamic state model and the raw measurements has the advantages of high redundancy, high reliability, as well as high ability of fault tolerance and simplicity in calculation. In order to control the influences of measurements outliers and the kinematic model errors on the integrated navigation results, a robust estimation method and an adaptive data fusion method are applied. An integrated navigation example using simulated data is performed and analyzed.
