摘要
为解决GNSS-RTK实时测量中存在的数据波动性大,难以满足高精度沉降监测需求的问题,通过引入方差补偿自适应卡尔曼滤波,对原始测量数据进行滤波去噪,实现了绝大部分白噪声的过滤和修正。同时,对原始测量数据与滤波数据进行分析比对,滤波前原始数据标准差在7 mm左右,方差补偿法滤波后数据标准差在3 mm左右,实现了两倍多的精度提升。实践证明,方差补偿自适应卡尔曼滤波在抑制滤波发散和提高监测数据精度上具有显著的效果。
To solve large data volatility in GNSS-RTK real time measurement,which was difficult to meet the needs of high-accuracy deformation monitoring,we introduced variance compensated adaptive Kalman filter to denoise the original data,filtering and correcting most of the white noise.At the same time,we compared the standard deviation of original data with the filtered data,and found that the standard deviation before filtering was about 7 mm,the standard deviation after filtering by variance compensation method was about 3 mm,realizing more than twice the accuracy improvement.Practice has proved that the variance compensated adaptive Kalman filter has a significant effect on restraining filter divergence and improving monitoring data accuracy.
作者
罗保林
金飞
罗亮
LUO Baolin;JIN Fei;LUO Liang(Chengdu Institute of Survey&Investigation,Chengdu 610031,China)
出处
《地理空间信息》
2023年第10期73-75,共3页
Geospatial Information
基金
成都市科技项目(VQ21SS1135Y17004)。
关键词
沉降监测
卡尔曼滤波
自适应卡尔曼滤波
方差补偿
settlement monitoring
Kalman filtering
adaptive Kalman filter
variance compensation
