An Improved Autonomous Inertial-Based Integrated Navigation Scheme Based on Vehicle Motion Recognition

The autonomous navigation technology of INS has always attracted the attention of many scholars. In satellite-denied environment, making full use of the auxiliary sensors with autonomous characteristics can suppress the dynamic error generated by INS in autonomous navigation effectively. However, auxiliary sensors like an odometer (OD) and laser doppler velocimeter (LDV) will cause instability to the navigation system. To solve the above problems, we propose an improved autonomous inerital-based integrated navigation scheme utilizing vehicle motion recognition. The main research work can be summarized as: (1) Non-holonomic constrained velocity model and tri-axis zero velocity model has been established for inertial-based integrated navigation model. (2) Vehicle motion state recognition method has been proposed utilizing the IMU data. As shown in the experimental results, the proposed method can estimate the IMU biases and increase the positioning accuracy effectively as compared with the traditional methods.