High-precision vehicle positioning based on improved interacting multiple model algorithm
DAI Yu-feng
SU Sheng-chao
CUI Wen-xia
WANG Yi-wang
Abstract：In response to the problem of untimely model matching and low positioning accuracy of the traditional interacting multiple model algorithm during vehicle maneuvering,this paper proposes an algorithm that combines the improved interacting multiple model with cubature Kalman filter to improve the performance of vehicle positioning.Firstly,the observations from inertial measurement unit and road side units are fused into the measurement information.Secondly,an adaptive turn model is designed to cope with the situation that a single constant turn model cannot effectively locate the vehicle when the angular velocity is not fixed.Then,the vehicle state is estimated by cubature Kalman filter,due to the nonlinearity of the model and the high dimensionality of the state vector.Finally,an improved interacting multi model algorithm is proposed to optimize the model probability through twice interactions.The simulation experiments show that the algorithm proposed in this paper can effectively improve the model switching speed,as well as the accuracy and stability of vehicle positioning,and its positioning error is reduced by 8.6％compared with the traditional interacting multiple model algorithm.
Keywords：vehicle positioninginteracting multiple modelKalman filtersstate estimation
Publication Date：2025-03-31
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：11( 590-600 )