The ring laser gyro inertial measurement unit has many systematic error terms and influences each other. These error terms show a complex nonlinear drift that cannot be ignored when the temperature changes, which seriously affects the stability time and output accuracy of the system. In this paper, a system-level temperature modeling and compensation method is proposed based on the relevance vector regression method. First, all temperature-related parameters are modeled; meanwhile, the Harris hawks optimization algorithm is used to optimize each model parameter. Then, the system compensation is modeled to stabilize the system output to the desired temperature. Compared with the least square method, the fitting performance comparison and the system dynamic compensation experiment prove this method’s superiority. The root mean square error, the mean absolute error, the -squared, and the variance of residual increased by an average of 35.27%, 39.29%, 2.29%, and 30.34%, respectively.

中文翻译：

---

基于HHO-RVR的RLG-IMU系统级温度补偿方法

环形激光陀螺惯性测量单元具有许多系统误差项，并且相互影响。这些误差项显示了一个复杂的非线性漂移，当温度变化时，它不能被忽略，这严重影响了系统的稳定时间和输出精度。本文提出了一种基于相关矢量回归方法的系统级温度建模与补偿方法。首先，对所有与温度相关的参数进行建模；同时，使用哈里斯霍克斯（Harris hawks）优化算法来优化每个模型参数。然后，对系统补偿建模，以将系统输出稳定到所需温度。与最小二乘法相比，拟合性能比较和系统动态补偿实验证明了该方法的优越性。均方根误差-平方，残差方差分别平均增加35.27％，39.29％，2.29％和30.34％。