基于LM法的光束法平差巡视器导航定位

光束法平差是一种通过高斯牛顿法进行最优估计的方法，在利用相机图像进行巡视器导航定位时起着重要的作用.为获得在缺少足够控制信息的月面环境下的高精度定位信息，提出一种利用列文伯格-马夸尔特算法(LM算法)代替高斯牛顿算法，进行图像光束法平差的巡视器导航定位方法.根据LM算法的核心思想和巡视器图像的构网特征，构建光束法平差模型，并给出了合适的阻尼策略和验后权估计方法.实验结果表明，基于LM算法的光束法平差巡视器导航定位，可以克服高斯牛顿算法适用性弱的缺点，具有较高的定位精度和理想的收敛速率.

Bundle Adjustment Based on LM Algorithm for Rover Navigation and Localization

An exact rover localization algorithm in bundle adjustment (BA) was proposed， which used Levenberg Marquardt algorithm instead of Gauss Newton algorithm to obtain high precision localization information. It could be used especially in the cases of lacking adequate control information in the lunar surface environment. According to the core ideas of the Levenberg Marquardt algorithm and lunar image structure network， the error estimation based on bundle adjustment was formulated， and then the appropriate damping strategy and posterior weights estimation were given. Simulation results showed that the disadvantages of weak applicability of Gauss Newton algorithm could be overcome by using the proposed algorithm， and it has a high localization accuracy and iterative convergence rate.