基于汽车发动机多传感器信息融合的研究  

Study on Automotive Engine Multi-sensor-based Information Fusion

作　　者：凌滨[1] 刘立臣[1] 姜岚[1] 

机构地区：[1]东北林业大学,黑龙江哈尔滨150040

出　　处：《林业机械与木工设备》2009年第6期20-21,共2页Forestry Machinery & Woodworking Equipment

基　　金：省教育厅科学技术研究项目"汽车智能测控系统"(11533008)

摘　　要：介绍了基于多传感器信息融合技术的联邦卡尔曼滤波器的结构,并将其应用于汽车发动机多压力传感器系统中。理论分析与仿真结果表明,该滤波器设计合理,算法具有全局最优性,可提高系统的性能和容错能力。The structure of the federated Kalman filter based on multi-sensor information fusion technology is introduced and the filter is applied in the multi-pressure sensor system of automotive engines. Theoretical analysis and simulation results show that the federated Kalman filter features reasonable design and global optimality, capable of improving the performance and fault-tolerant ability of the system.

关 键 词：多传感器 数据融合 联邦卡尔曼滤波 容错 

分 类 号：TP212.11[自动化与计算机技术—检测技术与自动化装置]