摘要
为了解决传统野点识别方法中由于缺乏先验知识,难以建立准确的参考模型时出现的病态、收敛速度快速降低、难以在嵌入式系统上设计模块化程序包等问题,文中以最大三阶相关峭度为代价函数,设计三阶相关峭度反卷积逆滤波器,对磁导航信号进行盲提取,以识别并剔除野点。该实验验证以双向四驱轻量级轮式移动机器人为实验平台,实验结果表明,该算法能有效地识别野点,收敛速度快,也无需准确的参考模型。
In order to solve the problems in traditional outlier recognition methods,such as morbidity,fast reduction of con⁃vergence speed,and difficulty in designing modular package on embedded system due to lack of prior knowledge,a third⁃order correlation kurtosis deconvolution inverse filter was designed with the maximum third⁃order correlation kurtosis as the cost function to extract the magnetic navigation signal blindly,identify and remove outliers.The experiment verified that the two⁃way four⁃wheel drive lightweight wheeled mobile robot was used as the experimental platform.The experimental results show that the proposed algorithm can effectively identify outliers,converge quickly and need no accurate reference model.
作者
胥明瑞
杨光永
徐天奇
陈跃斌
XU Ming⁃rui;YANG Guang⁃yong;XU Tian⁃qi;CHEN Yue⁃bin(Electronics and Information College,Yunnan University of Nationalities,Kunming 650504,China)
出处
《仪表技术与传感器》
CSCD
北大核心
2020年第5期99-101,118,共4页
Instrument Technique and Sensor
基金
国家自然科学基金项目(61761049,61261022)
国家民委科研基金项目(14YNZ015)
云南民族大学研究生项目(2018YJCX167)。
关键词
轮式移动机器人
野点识别与消除
最大三阶相关峭度反卷积算法
信号盲提取
wheeled mobile robot
wild point identification and elimination
maximum third⁃order correlation kurtosis deconvolution algorithm
blind signal extraction