A Camera/IMU Tightly-Coupled Navigation Algorithm and Verification by Hybrid Simulation  

作　　者：Li Wang Xiao-Ji Niu Quan Zhang Qi-Jin Chen Wei-Ping Jiang 

机构地区：[1]GNSS Research Center,Wuhan University

出　　处：《Journal of Harbin Institute of Technology(New Series)》2013年第6期84-90,共7页哈尔滨工业大学学报（英文版）

基　　金：Sponsored by the National High Technology Research and Development Program(Grant No.2012AA12A209);the National Natural Science Foundation of China(Grant No.41174028,41374033);the Key Laboratory Development Fund from the Ministry of Education of China(Grant No.618-277176);the LIESMARS Special Research Fund,the Research Start-up Fund from Wuhan Univesity(Grant No.618-273438);the Fundamental Research Funds for the Central Universities(Grant No.201161802020002)

摘　　要：GNSS( global navigation satellite systems) are unavailable in challenging environments such as urban canyon and indoor locations due to signal blocking and jamming. Camera / IMU( inertial measurement units) integrated navigation systems can be alternatives to GNSS. In this paper,a tightly coupled Camera / IMU algorithm modeled by IEKF( iterated extended kalman filter) is presented. This tight integration approach uses image generated pixel coordinates to update the Kalman Filter directly. The developed algorithm is verified by a hybrid simulation,i.e. using inertial data from field test to fuse with simulated image feature measurements. The results show that the tight approach is superior to the loose integration when the image measurements are insufficient( i.e. less than three ground control points).GNSS （global navigation satellite systems） are unavailable in challenging environments such as urban canyon and indoor locations due to signal blocking and jamming.Camera/IMU （inertial measurement units） integrated navigation systems can be alternatives to GNSS.In this paper,a tightly coupled Camera/IMU algorithm modeled by IEKF （iterated extended kalman filter） is presented.This tight integration approach uses image generated pixel coordinates to update the Kalman Filter directly.The developed algorithm is verified by a hybrid simulation,i.e.using inertial data from field test to fuse with simulated image feature measurements.The results show that the tight approach is superior to the loose integration when the image measurements are insufficient （i.e.less than three ground control points）.

关 键 词：inertial navigation image-aided navigation PHOTOGRAMMETRY Kalman filterCLC number：V249.32 Document code：AArticle ID：1005-9113（2013）06-0084-07 

分 类 号：V249.32[航空宇航科学与技术—飞行器设计]