Robust Adaptive Cubature Kalman Filter and Its Application to Ultra-Tightly Coupled SINS/GPS Navigation System.
Robust Adaptive Cubature Kalman Filter and Its Application to Ultra-Tightly Coupled SINS/GPS Navigation System.
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鲁棒自适应容积卡尔曼滤波器及其在超紧耦合SINS/GPS导航系统中的应用
DOI：
10.3390/s18072352
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发表时间：
2018-07-20
期刊：
影响因子：
--
通讯作者：
Ji S
中科院分区：
文献类型：
--
作者：
Zhao X;Li J;Yan X;Ji S
在本文中，我们提出了一种鲁棒自适应稳态卡尔曼滤波器（CKF）来处理系统模型和噪声统计不准确的问题。为了克服运动模型误差，引入自适应因子对状态预测的协方差矩阵进行调整，并对动态扰动误差带来的影响进行处理。为了克服异常误差，提出了鲁棒估计理论对CKF算法进行在线调整。提出的自适应CKF可以检测粗误差的程度并对其进行处理，从而解决了异常误差带来的影响。本文还对该方法的典型应用系统——高超声速飞行器超紧耦合导航系统进行了研究。高动态场景实验结果表明，该方法能有效处理异常数据和模型不准确引起的误差，具有比UKF和CKF跟踪方法更好的跟踪性能。同时，该方法在跟踪性能上优于基于单调制环的跟踪方法。从而较好地实现了GPS卫星信号的稳定高精度跟踪，提高了系统在高动态、弱信号环境下的适用性。高动态场景实验验证了该方法的有效性。
In this paper, we propose a robust adaptive cubature Kalman filter (CKF) to deal with the problem of an inaccurately known system model and noise statistics. In order to overcome the kinematic model error, we introduce an adaptive factor to adjust the covariance matrix of state prediction, and process the influence introduced by dynamic disturbance error. Aiming at overcoming the abnormality error, we propose the robust estimation theory to adjust the CKF algorithm online. The proposed adaptive CKF can detect the degree of gross error and subsequently process it, so the influence produced by the abnormality error can be solved. The paper also studies a typical application system for the proposed method, which is the ultra-tightly coupled navigation system of a hypersonic vehicle. Highly dynamical scene experimental results show that the proposed method can effectively process errors aroused by the abnormality data and inaccurate model, and has better tracking performance than UKF and CKF tracking methods. Simultaneously, the proposed method is superior to the tracing method based on a single-modulating loop in the tracking performance. Thus, the stable and high-precision tracking for GPS satellite signals are preferably achieved and the applicability of the system is promoted under the circumstance of high dynamics and weak signals. The effectiveness of the proposed method is verified by a highly dynamical scene experiment.
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DOI：
10.1049/ip-rsn:20030741
发表时间：
2003-10-01
期刊：
IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION
影响因子：
--
作者：
Boers, Y;Driessen, JN
通讯作者：
Driessen, JN
影响因子：
20.6
作者：
Julier, SJ;Uhlmann, JK
通讯作者：
Uhlmann, JK
影响因子：
6.4
作者：
Schimmack, Manuel;Haus, Benedikt;Mercorelli, Paolo
通讯作者：
Mercorelli, Paolo
影响因子：
2.9
作者：
Martino, Luca;Read, Jesse;Louzada, Francisco
通讯作者：
Louzada, Francisco
改进迭代体积卡尔曼滤波器性能分析及其在GNSS/INS中的应用
影响因子：
7.3
作者：
Cui, Bingbo;Chen, Xiyuan;Liu, Xiao
通讯作者：
Liu, Xiao