| Independent of external supports,the autonomous navigation system only determines its position,velocity and attitude relative to a coordinate system in real time by using the measurement equipment carried by itself to guide navigation.The strapdown inertial navigation system（SINS）navigation errors inevitably diverge,traditional methods provide position,velocity and attitude information through external equipment to compensate error divergence,but the autonomy and reliability of navigation system are sacrificed.The vision-based approach is limited by the environment,which lead to the lack of traceable features and make errors.Low-cost and robust positioning technology that can prolong the effective navigation time in GNSS-denied environment is one of the keys to determining the reliability of vehicle navigation system.In this paper,a low-cost autonomous navigation method for land vehicles is proposed.During the interruption of the Global Navigation Satellite System（GNSS）,the integration of odometer assisted inertial navigation（INS/OD）system and map matching（MM）system can achieve higher positioning accuracy than traditional autonomous positioning technology when the system is constrained by navigation scenarios.In this paper,the essential causes of position and speed error drift of INS/OD system are pointed out through observability analysis.It is pointed out that the main cause of navigation divergence of INS/OD system is the poor observability of direction Angle.In the simulation experiment,the main cause is that the zero deviation of Z-axis gyroscope of INS/OD system cannot be observed.Aiming at map matching module,this paper uses undirected graph to model urban road network,and only relies on location to complete fast topology construction.The preprocessing module is designed to divide the map and simplify the preservation elements to improve the positioning efficiency of candidate sections.The emission probability and transfer probability models are designed,and the hidden Markov matching algorithm achieves high matching success rate in the experiment.For the system fusion module,this paper uses extended Kalman filter to correct navigation errors.The matching trigger model is designed to realize automatic division of treatment matched sections,and the coordinate of matching points and heading observation are determined quickly by the pre-processing system.The observation model was designed and the error relations of attitude Angle error,attitude Angle and misalignment Angle were provided based on Rodrigues formula.The fusion system significantly increased the observable state of the system and solved the problem of fast divergence of heading.The fusion method proposed in this paper enhance the positioning performance of the micro-electro-mechanical systems（MEMS）INS/odometer integrated system during GNSS outages,without additional equipment.The main contribution of this study is to point out the essential cause of the position and velocity error drift of INS/OD system through observability analysis,and to suggest a novel hybrid strategy to integrate the MEMS INS,odometer based on both Kalman filtering and Map-Matching,which inhibits divergence through position and azimuth observation provided by map.The proposed navigation strategy is verified via road tests with artificial GNSS outages,showing that the root mean square of azimuth angle error,horizontal velocity error and horizontal position error of the proposed navigation strategy decrease by 93.2%,92.6% and 95.5%when the 200 s GNSS interruption time is set. |
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