Kezhao LI / Henan Polytechnic University;Beidou Navigation Application Technology Collaborative creation Center
Huabin CHAI / Henan Polytechnic University
In response to the current and future situation of the surface car in urgent need of accurate real-timing positioning in open-pit mines, as well as the low accuracy of existing GNSS-based vehicle navigation and positioning algorithms, we propose a new multi-model adaptive GNSS navigation and positioning algorithm based on camera assistance and non-integrity constraints in the context of the intersection and integration of navigation and positioning and mining disciplines. Firstly, the camera is used to capture the environmental information around the mining vehicle and judge the driving state of the vehicle, so as to adaptively select different state models to solve the problem of poor navigation and positioning accuracy caused by the existing Kalman-based GNSS mining positioning algorithm which commonly uses the uniform speed model. Secondly, the corresponding non-integrity constraint models are designed based on different driving states of the vehicle, such as parking, straight-line motion, turning, climbing, etc. Finally, filtering is performed based on the adaptive state and vehicle constraint models to obtain real-time high-precision mining vehicle position information. Through actual vehicle navigation experiments, the effectiveness and rationality of the proposed algorithm is proved, and the problem of low positioning accuracy of existing mining vehicle GNSS navigation in complex open pit mining environments has been well solved.