基于联合卡尔曼滤波的汽车防碰撞多传感器信息融合方法

Multi-sensor Information Fusion Algorithm in Automotive Anti-collision System Based on Federated Kalman Filter

车辆行驶信息感知是汽车防碰撞系统的关键技术之一,只用单一传感器对目标车辆进行测量容易产生虚警.在对联合卡尔曼滤波分析的基础上,给出了基于联合卡尔曼滤波的汽车防碰撞多传感器信息融合方法.计算机仿真结果表明,该算法可以得到较精确的融合数据,对于增强汽车防碰撞系统的安全性具有重要意义.

The perception of vehicle running information was one of the key technologies in automotive anti-collision system. And it was easy to cause false alter when using the single sensor measured the aim vehicle. The multi-sensor information fusion algorithm based on federated Kahnan filter was introduced and applied to solve the muhi-sensor information fusion problem in automotive anti-collision system. The simulation results showed that the federated Kalman filter can receive accurate fusion data and enhance the safety of automotive anti-collision system.