An improved SINS/NHC integrated navigation algorithm based on Ackermann turning geometry

The non-holonomic constraint (NHC) is a common auxiliary information based on the motion characteristics of land vehicles to improve navigation accuracy. Affected by Ackermann turning geometry, the accuracy of the velocity of the vehicle frame will decline in the maneuvering process. In this paper, the error above is modeled and compensated based on Ackermann turning geometry to improve the navigation accuracy, so as to enhance the system reliability: (1) Analysis shows that there is a velocity measurement error when the vehicle has angular motion without considering the lever arm effect; (2) A continuous linear 19dimensional (19D) Strapdown inertial navigation system (SINS)/NHC error model considering the lever arm effect based on Ackermann turning geometry is derived in this paper and (3) Kalman filter is utilized to estimate the error parameters. Field test results show that the proposed method can effectively improve the accuracy of positioning compared with the traditional method.