一种抗差自适应UKF算法及其在GNSS/SINS组合导航系统的应用

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。

Robust adaptive UKF algorithm and its application inGNSS / SINS integrated navigation system

The standard UKF algorithm of GNSS / SINS integrated navigation system lacks the ability to adjust the measurement noisevariance and system status anomaly adaptively, which affects the filtering accuracy of the integrated navigation system. A robust adaptiveUKF algorithm is proposed in order to solve the above problem. Firstly, this algorithm introduces the variational Bayesian estimationprinciple to estimate the measurement noise variance in real time. Then, an adaptive factor is constructed to reduce the influence ofabnormal system state on the navigation solution, based on the predicted residual of the filter. Finally, this algorithm is applied toGNSS / SINS integrated navigation system. The simulation results show that, compared with the standard UKF algorithm and the robustUKF algorithm, the proposed algorithm can improve the position accuracy by 51. 2% and 9. 3% respectively in the whole simulationperiod when the statistical characteristics of the measurement noise change, and can reduce the influence of abnormal system modeldisturbance and filter initial value deviation on the navigation solution. The experimental results show that the proposed algorithm hasstrong adaptability and robustness, and can improve the accuracy of integrated navigation system in complex environment.