摘要
提出了一种基于联合卡尔曼滤波理论和地图匹配技术的高精度车载导航系统定位方法。该方法一方面对联合卡尔曼滤波器的结构进行简化,简化后的联合滤波器能够较好地将全球定位系统(GPS)与航位推算系统(DR)获取的空间信息进行融合,不仅较大程度地减小滤波计算量,而且避免了子滤波器间误差的互相干扰,提高了空间定位精度。另一方面提出了根据行车方向与位置匹配行车道路的技术,该技术不仅具有较好的行车道路匹配效果,而且能够对各种行车异常情况进行处理。实验证明,本文提出的方法能够较好地满足车载导航系统对空间定位方法实时性及高精度的要求。
An integration solution for location accurately in vehicle navigation system is approached, which includes the united Kalman filter and the map matching algorithms. On the one hand, the fher with a simple separate structure is constructed to fuse the spacial data of Global Positioning System （GPS） and Dead Reckoning （DR）, which not only decreases the algorithmic complexity more greatly relative to the standard Kalmn filter, but also improves the location precision and algorithmic stability by avoiding the divergence among children fihers. On the other hand, an weighted average algorithm based on the topological analysis of the road network, utilizing vehicle heading and position information, is developed for map matching, which can produce the accurate position on the electronic map efficiently, particularly in difficult operational environments such as junctions and intersections. Furthermore, series of methods are added to map matching under the diversified position conditions and the different traffic environments. The results of simulation confirm the solution is usable and effective for location in vehicle navigation system.
出处
《地理信息世界》
2010年第1期48-55,共8页
Geomatics World
