UKF和UPF在惯导初始对准中的应用研究对比

捷联惯性导航系统是新型航位推算系统，在惯导系统执行工作任务之前需要进行初始对准，以保证系统的正常运行。对捷联式惯导系统，初始对准就是确定初始时刻的姿态阵，利用惯性元件的输出信息，选用合适的滤波方法，将计算的导航坐标系与真实导航坐标系的失准角估计出来，来修正姿态矩阵，使计算坐标系与真实坐标系尽可能重合。在实际的导航系统中，状态方程和量测方程通常都是非线性的，对于非线性特性，传统的解决方法是利用EKF滤波算法，但它只适用于弱非线性模型的估计，系统的非线性越强，引起的估计误差就越大，甚至会引起滤波发散。为此提出两种滤波算法UKF与UPF，并将两者进行了仿真对比，结果表明UPF算法比UKF算法收敛速度更快，估计精度更高。

Comparison of application of UKF and UPF in initial alignment of INS

SINS is a new type of dead reckoning system in inertial navigation system initial alignment is needed before implementing the task, to ensure the normal operation of the system. SINS, the initial alignment is to determine the initial attitude matrix, the output information of inertial components, selecting appropriate filtering method, the quasi angle estimation calculated navigation coordinates and the real navigation coordinates, to correct the attitude matrix, the calculation of coordinates and real coordinates coincide as much as possible. In the navigation systems, the state equation and measurement equation are usually nonlinear, the nonlinear characteristics, the traditional solution is to use EKF filtering algorithm to estimate but it is only suitable for the weak nonlinear model, the nonlinear system is stronger, the estimation error caused by the greater, even lead to filter divergence. For this reason, this paper proposes two filtering algorithms UKF and UPF, and compares them with simulation results. The results show that the UPF algorithm converges faster than the UKF algorithm and has higher estimation accuracy.