多传感器组合导航系统的联邦 UKF 算法研究
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TN966; V249. 3

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国家自然科学基金(60874112,61673208)、山东省自然科学基金(2016ZRA06068)项目资助


Research on federal UKF algorithm for multi-sensor integrated navigation system
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    摘要:

    多传感器组合导航系统是一种典型的非线性系统,为了提高其滤波精度,本文提出了多传感器组合导航系统联邦 UKF 算法。 首先,在建立多传感器组合导航系统的非线性状态方程及线性量测方程的基础上,对标准 UKF 进行了简化;然后,以简 化 UKF 为基础提出了多传感器组合导航系统的联邦 UKF 算法,并设计了姿态融合算法及其故障检测函数以验证该算法的容 错性能;最后,以 GNSS / CNS / SINS 多传感器组合导航系统为例进行了仿真验证。 仿真结果表明,相对于联邦线性卡尔曼滤波 器,联邦 UKF 算法可提高位置及姿态精度约 25. 8%、22. 2%,同时继承了联邦线性卡尔曼滤波器的容错性能。

    Abstract:

    Multi-sensor integrated navigation system is a typical nonlinear system, a federated UKF algorithm is proposed to improve its filtering accuracy in this paper. Firstly, the standard UKF is simplified on the basis of establishing nonlinear state equation and linear measurement equation of multi-sensor integrated navigation system. Then, based on this simplified UKF, the federated UKF algorithm of multi-sensor integrated navigation system is proposed, the attitude fusion algorithm is designed, and the fault detection function is designed simply in order to verify the fault-tolerant performance of the algorithm. Finally, the GNSS / CNS / SINS multi-sensor integrated navigation system is taken as an example for simulation verification. The simulation results show that the federated UKF algorithm can improve the position and attitude accuracy by 25. 8% and 22. 2% when compared with the federated linear Kalman filter, and inherit the fault-tolerant performance of the federated linear Kalman filter.

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朱璐瑛,孙炜玮,刘成铭,孙兆玮.多传感器组合导航系统的联邦 UKF 算法研究[J].电子测量与仪器学报,2022,36(7):91-98

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  • 在线发布日期: 2023-03-06
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