Research On Vehicle Navigation And Motion State Monitoring Method Based On MIMU

In recent years,the development of intelligent driving,vehicle insurance and other fields put higher requirements for vehicle navigation and motion state monitoring.Based on the demand of vehicle navigation and monitoring under the complex environment,an online calibration method of MIMU's error,a method of MIMU based vehicle navigation and motion state monitoring,and a design scheme of embedded platform are proposed in this paper.The accuracy and feasibility of the research results are verified by experiments.The work and achievements of the paper are listed as follows:(1)Aiming at the problem of low-precision and difficult-installation of the consumer-level MIMU,an online calibration method of MIMU's error is proposed in this paper.The method combines the coarse calibration based on vehicle specific motion with the fine calibration based on velocity and attitude matching.Compared to the general method,our method can complete the installation of navigation module in any angle,so as to improve the efficiency and versatility of calibration method.(2)Without the auxiliary information of vision and odometer,the vehicle velocity model and static model are analyzed in this paper.Based on these models,a constraint method of velocity,an estimate method of forward velocity,a method of zero velocity update and zero angular rate update are proposed in this paper.Combining the proposed model with SINS and GNSS through the federal Kalman filter,our method can effectively improve the accuracy and reliability of MIMU based vehicle navigation system under complex environment.(3)Considering the requirements of vehicle motion state monitoring in the field of intelligent vehicle insurance,some method of monitoring base on MIMU are proposed in this paper.The monitored dangerous states include the vehicle abnormal shift,abnormal turn,tilt and collisions.Our method utilizes the corresponding sensor information and navigation result and has high accuracy.(4)Taking the cost,volume,quality,power consumption,reliability of device and the portability,real-time performance of our algorithm into consideration,an embedded hardware platform based on ARM/MIMU and a software platform based on uC/OS-III are designed in this paper.The validity and practicability of the proposed method are verified by experiments.