针对卫星拒止环境下，战时或执行紧急任务时采用水声定位，但无法完成信标标定的问题，提出一种基于随机信标的因子图同时定位构图算法。建立DVL和罗经因子节点、信标因子节点数学模型，构建了基于因子图的融合架构，采用最大后验概率估计方法进行导航状态和信标位置的估计。数值仿真结果表明，因子图算法定位精度比传统EKF滤波算法在圆形运动轨迹和蛇形运动轨迹下分别提高37.6%和14.6%，验证了因子图同时定位构图算法是一种可行的导航方法。
For satellite denial environments, aim at the problem that the beacon calibration cannot be completed in wartime or performing emergency tasks, factor graph based on random beacon is proposed to achieve simultaneous positioning and mapping. The mathematical models of DVL and compass factor node and sonar factor node are established. Construct a fusion architecture based on factor graph. Navigation state and beacon position are estimated using maximum posterior probability estimation method. Numerical simulation result shows that the positioning accuracy of the factor graph algorithm is 37.6% and 4.6% higher than that of the traditional EKF filter algorithm under the circular motion trajectory and the serpentine motion trajectory, respectively. It is verified that the simultaneous localization and mapping algorithm of factor graph is a feasible navigation method.
2021,43(10): 132-136 收稿日期：2021-08-25
DOI：10.3404/j.issn.1672-7649.2021.10.027
分类号：TP212.9
基金项目：军科委基础加强项目（2020-JCJQ-ZD-134-00）
作者简介：王凯(1982-),男,高级工程师,从事惯性组合导航研究
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