基于ARM7飞控系统多传感器数据融合方法及实现  

Multi-sensor Data Fusion Method and Implementation of Unmanned Helicopter Control System Based on ARM7

作　　者：孙豫川[1] 裴海龙[1] 吴毅彬[1] 

机构地区：[1]自主系统与网络控制教育部重点实验室(华南理工大学),广州510640

出　　处：《计算机测量与控制》2013年第1期103-105,141,共4页Computer Measurement &Control

基　　金：国家自然科学基金重点项目(60736024)

摘　　要：无人直升机控制系统是一个典型的多传感器系统,为了实现各传感器的优势互补,需要进行多传感器数据融合;可以采用十一阶扩展卡尔曼滤波器——EKF来实现数据融合滤波;这里介绍了十一阶扩展卡尔曼滤波器在基于arm7无人直升机飞控系统中的应用,卡拉曼滤波有效地去除了角度约的漂移量;为了降低十一阶kalman在ARM 7中的运算时间,可以将一个大系统拆分成若干小系统,然后分别对小系统进行滤波,同时对卡尔曼滤波里面的一些运算做优化处理;最终在主频是48MHZ的ARM 7中的运算时间由70ms减少到25ms,成功实现了十一阶卡尔曼滤波在本系统中的高效运行。Unmanned helicopter control system is a typical multi--sensor system, which needs multi--sensor data fusion in order to real- ize the complementary advantages of the sensors. We adopt 11 order Extended Kalman Filter （EKF） to realize data fusion filter. This paper introduces the application of the 11 order EKF in unmanned helicopter flight control system based on ARM7. Kalman filter effectivly re- moved the drift about angle value. In order to reduce the computation time of 11 order kalman in the ARM7, the paper will divide a large system down into several small systems, and then respectively filter the small systems, and at the same time optimize some operations in kal- man filter. Finally, the time of computation in ARM7 reduced from 70ms to 25ms, successfully achieve the efficient operation of 11 order EKF in our flight control system.

关 键 词：十一阶扩展卡尔曼滤波 ARM7 飞控系统 多传感器 降阶 优化 

分 类 号：TP303[自动化与计算机技术—计算机系统结构]