一种小型无人旋翼机高度信息融合方法  

An Altitude Information Fusion Method for Small Unmanned Aerial Rotorcrafts

作　　者：雷旭升[1] 李晶晶[1] 郭克信[1] 杜玉虎[1] 

机构地区：[1]北京航空航天大学惯性技术国家级重点实验室新型惯性仪表与导航系统技术国防重点学科实验室,北京100191

出　　处：《机器人》2012年第4期432-439,共8页Robot

基　　金：国家杰出青年科学基金资助项目(60825305);国家自然科学基金资助项目(60905056);国家973计划资助项目(2009CB72400102)

摘　　要：针对小型无人旋翼机在起降过程中由于地效、外扰作用造成的高度传感器量测信息不精确的问题,提出一种基于单目视觉信号的高度获取方法,利用改进的大津法及仿射不变矩的方法提高目标识别的准确性;并针对视觉图像受噪声干扰、气压传感器存在误差积累、GPS测量精度不精确以及超声量程有局限性的问题,提出一种基于残差信息的自适应卡尔曼滤波,将视觉信息、气压高度计、GPS和超声高度信息进行融合,以提高全量程的高度估计的精度.最后通过静态测试实验、自主悬停以及自主降落实验验证本方法的有效性.Focusing on the low precision of the altitude sensors for the small unmanned aerial rotorcraft （SUAR） due to the ground-effect and external disturbances in the process of taking off and landing, a method based on monocular vision is proposed to get altitude information. With the improved Ostu method and the affine invariant moments, the system can realize the high precision target recognition. Furthermore, to deal with the problems of the image noise, the measurement error for the barometric sensor and GPS （global positioning system）, and the limited measurement range of ultrasonic sensor, an adaptive Kalman method based on residual error is proposed to fuse the data of altitude information from vision system, barometric altimeter, GPS and ultrasonic sensors. Thus, the SUAR can get altitude information of high precision in whole measuring range. Finally, the effectiveness of the proposed method is tested by the static test, hovering flight test and automatic landing test.

关 键 词：小型无人旋翼机(SUAR) 单目视觉 高度信息融合 自适应卡尔曼滤波 

分 类 号：TP249[自动化与计算机技术—检测技术与自动化装置]