Theory And Simulation Study On Low-Cost Integrated Positioning System Of GPS And SINS

A low-cost integrated positioning system, consisting of GPS and SINS, was studied for autonomous agricultural vehicle applications. This study aimed to improve the reliability and accuracy of the positioning system, at the same time, reduce the cost. Consequently it will give an impetus to the development of digital agriculture.In this paper, a centralized Kalman filter based on position-velocity model was designed to integrate data from all sensors to provide accurate and robust vehicle positioning data. The subsystems were analyzed respectively and the error pattern of them was established.The optimal filter technology (Kalman Filter) was used to estimate the error and the SINS was corrected by the optimal error. In order to prove the availability of the integrated method and data fusion algorithm, the GPS/SINS integrated positioning system was simulated on the computer. From the result of the simulation, we can draw a conclusion that GPS/SINS position-velocity integration can greatly enhance the precision of the positioning system, especially raise the precision of location and speed obviously.