南京信息工程大学学报2024，Vol.16Issue(1)：114-119,6.DOI:10.13878/j.cnki.jnuist.20230214001
GNSS/SINS/视觉导航鲁棒算法
GNSS/SINS/visual navigation robust algorithm
摘要
Abstract
Global Navigation Satellite System(GNSS),Strapdown Inertial Navigation System(SINS)and visual sen-sors can complement each other,and their information fusion can obtain high-precision,drift-free navigation and posi-tioning information.Aiming at the problem that GNSS/SINS/vision fusion navigation is vulnerable to the impact of mo-tion speed,light change,occlusion,etc.,which leads to the decline of navigation positioning accuracy and robustness,this paper adds the SoftLone robust kernel function to the cost function of the graph optimization framework,and sets the gross error test procedure of the measured value to reduce the negative impact of outliers.Further,the chi-square test is performed on the calculated residuals of the measured value,and the weight of the over-limit residual is reduced to improve the accuracy and robustness of the system.The experimental results show that the proposed algorithm has higher accuracy and better robustness than traditional algorithm without robust kernel function,outlier elimination strategy and chi-square test,and algorithm with other robust kernel functions.It can greatly improve the positioning ac-curacy and robustness of GNSS/SINS/visual navigation.In large scale scenario,there is no large drift errors,and root mean square error and standard deviation of absolute pose are 0.735 m and 0.336 m,respectively.关键词
全球导航卫星系统/捷联惯性导航系统/视觉/鲁棒算法/卡方检验Key words
global navigation satellite system(GNSS)/strapdown inertial navigation system(SINS)/vision/robust algorithm/chi-square test分类
航空航天引用本文复制引用
李明,柴洪洲,郑乃铨..GNSS/SINS/视觉导航鲁棒算法[J].南京信息工程大学学报,2024,16(1):114-119,6.基金项目
国家自然科学基金(42074014) （42074014）
