基于低成本组合导航定位系统的新融合滤波算法

A New Filtering Algorithm for Information Fusion Based on Low Cost Integrated Navigation System

设计了一种可用于地面交通工具或机器人的低成本组合导航定位系统,提出了基于该系统的新信息融合方法,将模糊卡尔曼滤波算法和地图匹配技术联合起来。仿真结果表明:模糊卡尔曼滤波算法相当于一数据平滑处理窗口,具有比常规卡尔曼滤波算法更高的精度。

This paper deals with a new information fusion algorithm based on a low cost integrated navigation system used by cars and ground robotics vehicle. The proposed algorithm combines fuzzy Kalman filter algorithm with map matching techniques. The simulation results indicate that fuzzy Kalman filter can be viewed as a data-smothering window, and is better than regular extended Kalman filter algorithm.