基于贝叶斯估计的水下机器人罗盘故障检测

Compass Fault Detection of Autonomous Underwater Vehicles Based on Bayesian Estimation

以电子磁通门罗盘为例对自主水下机器人(Autonomous Underwater Vehicles,AUVs)传感器故障检测方法展开研究。针对电子罗盘极易受到周围磁场的影响而产生时对时错的数据这一问题,首先联立AUV的运动学和动力学方程得到AUV的全状态非线性模型;然后分析了电子罗盘的误差来源,建立了误差的模型;在此基础上,提出了基于贝叶斯估计的故障检测方法并给出了该方法离散形式的递推迭代公式;最后参照实际使用的电子罗盘的参数和AUV的机动能力,设计了仿真实验和外场试验,通过实验验证了该方法的正确性和有效性。

As the electronic magnetic compass is extremely easy to be influenced by the surrounding magnetic field and hence generates data with large deviation, the method of compass fault detection for AUV is studied in this paper. Firstly, the full state nonlinear model of AUV is obtained by correlating kinematic and dynamic equations. Secondly, the measurement deviation of the compass is analyzed and the model of the deviation is established. Based on this, a fault detection method based on Bayesian estimation is proposed and the iterative formula of the method in the discrete form is presented. Finally, simulations and field experiments are designed and carried out according to the parameters of the compass and the maneuver capability of the AUV and the results verify the correctness and effectiveness of this method.