车辆动力学模型辅助的惯性导航系统

为提高车辆导航系统的精确度和可靠性,提出一种车辆动力学模型辅助惯性导航系统的方法。建立车辆非线性动力学模型,利用四阶龙格库塔法实时解算速度信息。以惯导误差方程为状态方程,动力学模型与惯性导航解算的速度差为观测量,设计了容积卡尔曼滤波器,并用估计的状态误差对惯导进行校正。仿真结果表明,所提出的利用车辆动力学模型辅助惯导的方法能有效抑制惯导误差的发散,位置精度和速度精度比纯惯导系统提高了一个数量级,航向角精度提高了73%。

Vehicle dynamic model aided inertial navigation system

To improve the accuracy and reliability of the vehicle navigation system,an inertial navigation system aided by vehicle dynamic model is proposed.A nonlinear dynamic model of the vehicle is established and a fourth-order RungeKutta algorithm is used to calculate the velocity in real time.The error equation of the inertial navigation system is the state equation,and the calculated velocity difference between the vehicle dynamic model and inertial navigation is the observation vector.Then a cubature Kalman filter is designed,and the estimated state error is used to compensate the inertial navigation system.Simulation results show that the proposed method can effectively suppress the divergence of the inertial navigation error.The accuracies of the estimated position and velocity are both one order higher than those of the pure inertial navigation system,and the accuracy of the estimated yaw angle is improved by about 73％.