摘要
为准确获取水下目标的位置和速度信息,需要对长基线定位中的野值点进行剔除和修正。提出了改进残差检测法用于对野值点的剔除和修正,以卡尔曼滤波的残差绝对值作为判别标准,对野值点进行判别和剔除,以调整后的卡尔曼滤波估计值作为野值点的修正值,针对滤波模型与实际运动不匹配导致滤波前后数据偏差较大的问题,选择对正常点的数据不做处理。湖上实验结果表明,对存在野值点的定位轨迹,未剔除野值点的定位均方根误差为55.68 m,使用残差检测法处理后的定位均方根误差为8.11 m,使用改进残差检测法处理后的定位均方根误差为2.04 m。改进残差检测法可以对长基线定位轨迹中的野值点进行判定、剔除和修正,减小定位误差,提升长基线系统定位精度。
In order to accurately obtain the underwater target position and velocity information,it is necessary to eliminate and correct the outliers in the long base line positioning.An improved residual detection method for the elimination and correction outliers is proposed.In this method,the absolute value of Kalman filtering residual error is taken as the judgment standard to identifying and eliminating outliers,and then the outliers are modified with adjusted Kalman filter estimation.Aiming at the problem that the filtering model does not match the actual motion to cause large deviation of data before and after filtering,the normal data will not be processed.The experimental results on the lake show that for the positioning trajectory where outliers exist,the root-mean-square error without removing outliers is 55.68 m,the root-mean-square error after processing by the residual detection method is 8.11 m,and the root-mean-square error after processing by the improved residual detection method is 2.04 m.Thus,the improved residual detection method can determine,eliminate and correct outliers in positioning trajectory,reduce positioning error,and improve the positioning accuracy of the long base line system.
作者
李钉云
冯海泓
LI Dingyun;FENG Haihong(Shanghai Acoustics Laboratory,Chinese Academy of Sciences,Shanghai 201815,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《声学技术》
CSCD
北大核心
2020年第1期117-120,共4页
Technical Acoustics
基金
国家自然科学基金资助项目(61531018)。
关键词
长基线
野值点
卡尔曼滤波
残差检测
long base line
outliers
Kalman filter
residual error detection
