CPF算法在GNSS-INS列车组合定位系统中的应用

摘要

为了提高GNSS-INS列车组合定位系统的定位精确性,拟将一种性能优良的非线性CKF算法引入到传统粒子滤波(PF)框架中,形成改进的CPF算法.结合某列车控制系统提供的样本数据进行仿真,与传统的PF算法相比,CPF算法滤波效果好,定位误差小,更能满足列车运行的非线性环境要求.结果表明:CPF算法在GNSS-INS列车组合定位系统中具有良好的工程实用价值.%In order to improve positioning accuracy of GNSS-INS train combination positioning system, a fine performance CKF nonlinear filtering algorithm is intended to be introduced to traditional framework of particle filter (PF)to form improved CPF algorithm. Combined with the sample datas provide by a train control system,to carry out simulation,compared with the traditional PF algorithm,the CPF algorithm has good filtering effect,small error, and can meet the requirements of the train operation nonlinear environment. The results show that CPF algorithm has good engineering application value in GNSS-INS train combination positioning system.