基于最小二乘法的光纤陀螺动态寻北算法研究

摘要

相比于静态条件下的寻北方案,动态寻北能够有效抑制光纤陀螺的各种随机误差,大幅提高寻北快速性和定位精度.常见的动态寻北算法有最小二乘拟合法、数学函数调制解调法和单位函数调制解调法等.在最小二乘拟合算法原理的基础上,利用Matlab/Simulink仿真工具建立了两种寻北模型,并对模型适用性进行了检验.通过建立模型研究了转台转速、采样频率、随机噪声、采样点数及常值漂移对光纤陀螺动态寻北结果的影响.仿真实验结果表明随机漂移噪声是影响寻北精度的关键因素.采样点对寻北结果的影响袁明,采样点数足够多时,寻北误差趋于稳定,可以实现残周期采样的寻北从而缩短寻北时间.%Compared with the north seeking schemes under the static condition,the dynamic north seeking schemes can effectively restrain the random errors of the Fiber Optic Gyroscope (FOG),and greatly improve the accuracy and rapidity.Least square fitting method,mathematical function modulation/demodulation method and unit function modulation/demodulation method are common dynamic north seeking algorithms.In the paper,the principle of least square fitting algorithm is introduced and related formulas are deduced.Two north seeking models are established by Matlab/ Simulink simulation tool and the applicability of the model is tested.The effects of rotation speed,sampling frequency,random errors,sampling points and constant drift on the dynamic north seeking result of FOG are studied by the established models.The simulation results show that the random drift noise is the key factor that affects the accuracy of the north seeking,and other factors also restrict the accuracy of the north seeking.The effect of sampling points on the results of the north seeking shows that the north seeking errors tend to be stable when sampling points are enough,and north seeking can be realized with the residual period sampling and north seeking time can be shortened.