针对舰艇强导航干扰背景下，导航能力偏弱的单舰难以保证自身导航精度的问题，本文提出基于和积算法的舰艇编队主从式惯性基协同导航方法。利用编队各舰搭载的不同精度惯性导航基准，开展协同导航技术研究。构建了2艘舰艇组成的一主一从式惯性基协同导航数学模型，并将惯性导航信息参量与因子图融合，设计了基于因子图的和积协同导航算法；通过分析因子图中节点消息传递过程，获取了各节点之间的导航消息传递概率密度函数；以时间更新和测量更新为基础，建立2次消息传递过程，最终获得更新校正的从舰导航信息。试验结果表明，相较于传统的基于扩展卡尔曼滤波的惯性基协同导航算法，基于因子图的和积算法位置解算精度提高16.69%，北向速度精度提高34.94%，东向速度精度提高48.90%，可有效提高卫导拒止环境下的从舰惯性基导航精度。
In order to solve the problem that single ship with weak navigation capability cannot guarantee their own navigation accuracy under strong navigation interference, a cooperative navigation technology based on sum-product algorithm is studied by utilizing the different precision inertial navigation reference systems installed on each ship in the ship formation. A mathematical model of inertial-based cooperative navigation for two ships in a master-slave configuration was established. The information parameters of inertial navigation were fused with factor graph, and a sum-product cooperative navigation algorithm based on factor graph was designed. By analyzing the message passing process of nodes in the factor graph, the probability density function of navigation message passing between nodes was obtained. Based on the time update and measurement update, two message passing processes were established, and finally, the updated and corrected navigation information of the follower ship was obtained. The experimental results show that, compared with the traditional inertial-based cooperative navigation algorithm based on Extended Kalman filter, the positioning solution accuracy of sum-product algorithm based on the factor graph is improved by 16.69%, the northward velocity accuracy is improved by 34.94%, and the eastward velocity accuracy is improved by 48.90%, which can effectively improve the inertial-based navigation accuracy in the GNSS denied environment of slave ship.
2025,47(12): 134-140 收稿日期：2025-1-2
DOI：10.3404/j.issn.1672-7649.2025.12.024
分类号：U666
基金项目：黑龙江省自然科学基金项目（YQ2021E011）
作者简介：王苏(1978-),男,博士,讲师,研究方向为导航、制导与控制
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