计算机技术与发展Issue(8)：80-83,89,5.DOI:10.3969/j.issn.1673-629X.2015.08.017
基于非线性卡尔曼滤波的车辆定位优化算法
An Optimization Algorithm of Vehicle Positioning Based on Nonlinear Kalman Filter
摘要
Abstract
Intelligent Transportation Systems ( ITS) is an important trend in the development of future transport systems. In order to pro-vide the various functions,the system should acquire the exact position of the vehicle. How to achieve accurate and rapid vehicle position is an important issue which modern intelligent transportation systems must go to research. The actual systems are generally nonlinear sys-tem,so a nonlinear unscented Kalman filter algorithm is used. When the vehicle is in motion is mutated,the accuracy of unscented Kal-man filter algorithm is declined. Due to improving the accuracy of vehicle position while the vehicle is motor-driven,the interacting mul-tiple model algorithm is combined with the unscented Kalman filtering. At the same time,the improved algorithm can adapt to a variety of motion state of the vehicle. Simulation results show that the positioning accuracy of interacting multiple model unscented Kalman filtering algorithm is obviously better than unscented Kalman filtering algorithm.关键词
车辆定位/卡尔曼滤波/交互多模算法/非线性模型Key words
vehicle location/unscented Kalman filter/interacting multiple model algorithm/non-linear model分类
信息技术与安全科学引用本文复制引用
卞月根,张伟..基于非线性卡尔曼滤波的车辆定位优化算法[J].计算机技术与发展,2015,(8):80-83,89,5.基金项目
江苏省普通高校研究生科研创新计划项目(CXLX13456) （CXLX13456）
