Abstract: An improved algorithm based on polarized light is put forward concentrating on the problems which are course angle error divergence and not getting high precision as well as high reliability navigation parameters, for automotive auxiliary algorithm of inertial navigation system. Together with the output of the inertial navigation system, the algorithm uses the filter model of multisource information system for navigation parameters of the filter estimation adopting the course angle, the virtual position and the velocity observed quantity, which can be acquired by the polarized light sensor system and the vehicle dynamic mathematical model respectively. Therefore, the inertial navigation system and vehicle dynamic mathematical model can be corrected by the real-time feedback. Simulation analysis is performed by computer. Results show that the inertial navigation system aided algorithm not only can get better accuracy than the pure inertial navigation system and traditional kinematics auxiliary method of inertial navigation but also has certain engineering application value in achieving accurate and reliable autonomous orientation of vehicle navigation system.

Key words: polarized light, vehicle dynamic model, inertial navigation, vehicle navigation, combination filter

摘要： 针对车载惯性导航系统运动学辅助算法中, 航向角误差发散，无法长时间得到高精度、高可靠性导航参数的问题，提出一种基于大气偏振光分布规律高精度定向的运动学辅助惯导精度提高算法。通过车载偏振光传感器系统测量解算获得的航向角信息和车辆动态数学模型提供的虚拟位置与速度观测量，与惯性导航系统的输出一起，利用多源信息融合技术进行导航参数的滤波估计，结果能实时反馈校正惯性导航系统和车辆动态数学模型。通过计算机仿真与分析表明，该改进的惯性导航系统辅助方法能够有效抑制航向角误差发散，定位精度较纯惯导及传统惯导运动学辅助方法显著增强，且对最终实现陆地作战车辆精确可靠的自主导航定位具有一定的工程应用价值。

关键词: 天空偏振光, 车辆动态数学模型, 惯性导航, 车辆导航, 组合滤波器