基于IEKF的空间探测车月面定位与建图

Lunar Surface Positioning and Mapping of Space Rover Based on IEKF

摘要: 月球表面巡视探测具有环境复杂严苛、先验知识缺乏并且计算资源受限等特点和限制。自主环境感知与避障是决定月球探测车自主探测能力的关键。而月面定位和建图是月球探测的基础技术，对于提高月球探测器的导航精度、实现月球表面的自主导航、支持月球科学研究和资源勘探等具有重要意义。卡尔曼滤波理论作为最重要的最优估计理论，被广泛应用于航空航天领域。文章采用改进后的迭代扩展卡尔曼滤波(IEKF)在月球探测车月面定位和建图方面进行研究：首先对探测车进行建模，然后建立空间探测坐标系并进行坐标转换，分析探测车运动学模型，进而构建IEKF定位和建图方法。最后，在相同的仿真实验条件下，分别采用EKF和改进后的IEKF对白噪声和有色噪声情况下的定位和建图效果进行实验。实验结果表明改进后的IEKF在处理非线性系统中有着很大的优势，在有色噪声和白噪声下都表现良好，尤其在有色噪声下。因此，将改进后的IEKF应用于月球探测车上有利于提升月面定位和建图的精度。

Abstract: Lunar surface exploration is characterized and limited by a complex and harsh environment, lack of a priori knowledge and limited computational resources. Autonomous environment sensing and obstacle avoidance are the key to determine the autonomous exploration capability of the lunar exploration vehicle. Lunar surface localization and mapping is the basic technology of lunar exploration, which is of great significance for improving the navigation accuracy of lunar rovers, realizing autonomous navigation on the lunar surface, and supporting lunar scientific research and resource exploration. Kalman filter theory, as the most important optimal estimation theory, is widely used in aerospace field. The article adopts the improved Iterative Extended Kalman Filter (IEKF) in the study of lunar exploration rover lunar surface localization and mapping: firstly, the rover is modeled, then the spatial exploration coordinate system is established and the coordinate transformation is performed, and the rover kinematic model is analyzed, and then the IEKF localization and mapping method is constructed. Finally, under the same simulation experimental conditions, EKF and the improved IEKF are used to experiment the localization and mapping effects under white noise and colored noise, respectively. The experimental results show that the improved IEKF has a great advantage in dealing with nonlinear systems and performs well in both colored noise and white noise, especially in colored noise. Therefore, applying the improved IEKF to the lunar exploration vehicle is conducive to improving the accuracy of lunar surface localization and map construction.