Robust adaptive unscented Kalman filter for attitude estimation of pico satellites
Robust adaptive unscented Kalman filter for attitude estimation of pico satellites
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DOI：
10.1002/acs.2393
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发表时间：
2014-02-01
影响因子：
3.1
通讯作者：
Soken, Halil Ersin
中科院分区：
文献类型：
--
作者：
Hajiyev, Chingiz;Soken, Halil Ersin
Unscented卡尔曼滤波（UKF）是一种对于非线性系统的估计问题，即使是在高度非线性的情况下，也能给出足够好的估计结果的滤波算法。然而，在系统不确定或测量故障的情况下，UKF会变得不准确并随时间而偏离。介绍了一种微型卫星容错姿态估计算法。该算法使用鲁棒自适应UKF，根据故障类型对过程噪声协方差（q -自适应）或测量噪声协方差（r -自适应）进行校正。针对传统的UKF算法，提出了一种新的自适应方案，对故障进行检测和隔离，并根据故障类型进行必要的自适应处理。该算法作为微型卫星姿态估计算法的一部分进行了测试。版权所有：John Wiley & Sons， Ltd。
Unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for the estimation problems of nonlinear systems even when high nonlinearity is in question. However, in case of system uncertainty or measurement malfunctions, the UKF becomes inaccurate and diverges by time. This study introduces a fault-tolerant attitude estimation algorithm for pico satellites. The algorithm uses a robust adaptive UKF, which performs correction for the process noise covariance (Q-adaptation) or measurement noise covariance (R-adaptation) depending on the type of the fault. By the use of a newly proposed adaptation scheme for the conventional UKF algorithm, the fault is detected and isolated, and the essential adaptation procedure is followed in accordance with the fault type. The proposed algorithm is tested as a part of the attitude estimation algorithm of a pico satellite. Copyright (c) 2013 John Wiley & Sons, Ltd.