针对SINS/DVL组合导航传统误差模型中卡尔曼滤波在复杂水域误差较大的问题，引入李群右误差模型并提出一种自适应抗差算法。该算法在传统滤波的基础上，采用引入量测新息构建统计量，利用统计量所处区间来构建权值矩阵，进而修改量测噪声协方差矩阵来解决滤波发散的问题。通过船载实验数据，所提的鲁棒滤波相较于传统滤波在位置和速度估计精度方面分别提高了56.3%和69.1%，相较于普通抗差滤波分别提高了7.9%和12.5%。研究结果表明，在李群右误差模型基础上利用自适应抗差算法可以有效提高滤波的抗干扰能力。
To address the issue of large errors in traditional Kalman filtering for SINS/DVL integrated navigation in complex water environments, a Lie group right error model is introduced and an adaptive robust algorithm is proposed. This algorithm, based on traditional filtering, modifies the measurement noise covariance matrix by constructing a weight matrix using the introduced measurement residue to solve the problem of filtering divergence, thus improving the algorithm's anti-interference ability. Through onboard experiments, the proposed robust filtering method improved position and velocity estimation errors by 56.3% and 69.1%, respectively, compared to traditional filtering, and by 7.9% and 12.5%, respectively, compared to conventional robust filtering. Research results show that utilizing adaptive robust algorithms on the basis of Lie group error model can effectively enhance the filtering's anti-interference capability.
2025,47(3): 123-128 收稿日期：2024-4-29
DOI：10.3404/j.issn.1672-7649.2025.03.020
分类号：U666.12
基金项目：国家自然科学基金资助项目（42074010，42174051）
作者简介：郜鹏华(2001-),男,硕士研究生,研究方向为组合导航
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