Research On Combined GPS/SINS Navigation Algorithm Based On Monocular Vision Assistance

Modern society is developing towards intelligence,and high precision navigation and positioning technology is one of the important core technologies of intelligent systems.This thesis addresses the problem that GPS/SINS combined navigation has low positioning accuracy in GPS rejection areas and cannot meet the actual needs,and proposes a visionassisted GPS/SINS combined navigation method.Firstly,this thesis examines in detail various conventional navigation techniques,which mainly include GPS,vision and inertial navigation.Through a detailed analysis of the principles and error sources of the three,it is theoretically shown that they are highly complementary to each other,and thus the feasibility and necessity of combined navigation is demonstrated.A combined vision/GPS/inertial navigation system is then designed,which can significantly improve the positioning accuracy in the absence of GPS signals to meet the needs of practical applications.Due to the large computational effort of visual navigation,the combined GPS/inertial navigation system is able to meet the requirements of high accuracy positional resolution without the need to solve the visual sensor data when the GPS signal is strong,and only when the carrier enters the GPS rejection area,the positional data from the previous combined GPS/SINS navigation is used as the initial visual sensor data to solve and compensate for the shortcomings of pure inertial guidance.Finally,a vision/GPS based navigation system is built.Finally,a combined vision/GPS/SINS-based navigation system is built,which is divided into two main parts: the front-end implements visual feature extraction and matching,GPS signal sensing,sensor time synchronisation and IMU pre-integration;the back-end implements position optimisation and loopback detection.In order to verify the effectiveness of the combined navigation system,a set of outdoor vehicle field tests were designed and the results were analysed in detail.The results proved that the algorithm in this thesis has high accuracy and stable positioning error throughout the whole journey of the trolley(including the GPS rejection area),and the overall eastward position error and northward position error were reduced by 39% and 37.5% respectively.Compared with the traditional GPS/inertial combined navigation system,the system designed in this thesis can overcome the effects of GPS signal loss to a certain extent and achieve high accuracy positioning in indoor environments.As the computer’s ability to process and analyse large amounts of data continues to improve,the processing speed,accuracy and robustness of the combined vision/GPS/inertial navigation system will also be further improved,and it is expected to become one of the core technologies for achieving autonomous navigation and positioning in the future.