基于固定点平滑的CNS/INS一体化偏差标校方法

Calibration Method of CNS/INS Integrated Navigation System Based on Fixed Point Smoother Algorithm

CNS/INS一体化偏差是制约组合导航系统精度的重要因素,本文提出一种基于Kalman固定点平滑的惯性/天文组合导航系统一体化偏差估计方法。在常规Kalman滤波估计流程的基础上,充分利用量测期间的全部观测值对滤波状态参数进一步平滑处理,实现状态参数的最优化估计。仿真结果表明,相比常规Kalman滤波算法,该方法可有效提升滤波器状态参数估计的稳定性和精度水平,方法的有效性得到验证。

The integrated deviation of CNS/INS is an important factor that restricting the accuracy of integrated navigation system.A calibration method of CNS/INS integrated navigation system based on fixed point smoother algorithm is presented in this paper.The deviations parameters can be estimated optimally by fully utilize the measurement information using the smoother algorithm that based on convention Kalman filtering process.Simulation results show that the smoother algorithm can realize more stability and more accuracy estimated result and the validity of this method are verified.