胡晓梅,潘新龙,朱璐瑛,韩有杰.一种抗差自适应 UKF 算法及其在 GNSS / SINS
组合导航系统的应用[J].电子测量与仪器学报,2022,36(12):153-160 |
一种抗差自适应 UKF 算法及其在 GNSS / SINS
组合导航系统的应用 |
Robust adaptive UKF algorithm and its application inGNSS / SINS integrated navigation system |
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DOI: |
中文关键词: 变分贝叶斯 自适应因子 抗差自适应 UKF 组合导航系统 |
英文关键词:variational Bayes adaptive factor robust adaptive UKF integrated navigation system |
基金项目:国家自然科学基金(60874112,62076249)、山东省自然科学基金(ZR2020MF154)项目资助 |
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中文摘要: |
GNSS / SINS 组合导航系统标准 UKF 算法缺乏对量测噪声方差及系统状态异常的自适应调节能力,进而影响了组合导
航系统的滤波精度。 为了解决上述问题,提出了一种抗差自适应 UKF 算法。 首先,该算法引入变分贝叶斯估计原理以实时估
计量测噪声方差;然后,基于滤波器预测残差,构建了自适应因子以降低系统状态异常时对导航解的影响;最后,将该算法应用
于 GNSS / SINS 组合导航系统中,仿真结果表明,当量测噪声统计特性发生变化时,相对于标准 UKF 算法及抗差 UKF 算法,在整
个仿真时段内,本文算法可提高位置精度分别为 51. 2%及 9. 3%,同时可以降低系统模型异常扰动和滤波器初值偏差对导航解
的影响。 实验结果表明本文算法具有较强的自适应性及抗差性,可提升复杂环境下组合导航系统的精度。 |
英文摘要: |
The standard UKF algorithm of GNSS / SINS integrated navigation system lacks the ability to adjust the measurement noise
variance and system status anomaly adaptively, which affects the filtering accuracy of the integrated navigation system. A robust adaptive
UKF algorithm is proposed in order to solve the above problem. Firstly, this algorithm introduces the variational Bayesian estimation
principle to estimate the measurement noise variance in real time. Then, an adaptive factor is constructed to reduce the influence of
abnormal system state on the navigation solution, based on the predicted residual of the filter. Finally, this algorithm is applied to
GNSS / SINS integrated navigation system. The simulation results show that, compared with the standard UKF algorithm and the robust
UKF algorithm, the proposed algorithm can improve the position accuracy by 51. 2% and 9. 3% respectively in the whole simulation
period when the statistical characteristics of the measurement noise change, and can reduce the influence of abnormal system model
disturbance and filter initial value deviation on the navigation solution. The experimental results show that the proposed algorithm has
strong adaptability and robustness, and can improve the accuracy of integrated navigation system in complex environment. |
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