超宽带定位的降噪方法研究  

Study of noise reduction method for ultra wideband positioning

作　　者：王川阳 王坚 宁一鹏[1] 余航[1] WANG Chuanyang;WANG Jian;NING Yipeng;YU Hang(NASG Key Laboratory of Land Environment and Disaster Monitoring,China University of Mining and Technology,Xuzhou, Jiangsu 221116,China;School of Geomatics and Urban Spatial Informatics,Beijing University of Civil Engineering and Architecture, Beijing 102616, China)

机构地区：[1]中国矿业大学国土环境与灾害监测国家测绘地理信息局重点实验室,江苏徐州221116 [2]北京建筑大学测绘与城市空间信息学院,北京102616

出　　处：《测绘科学》2019年第4期175-181,共7页Science of Surveying and Mapping

基　　金：国家重点研发计划资助项目(2016YFC0803103)

摘　　要：针对超宽带定位中原始观测数据存在的高频噪声影响定位结果的问题,该文利用小波变换、Vondrak滤波、卡尔曼滤波3种方法分别对原始观测数据和定位结果两种方案进行降噪处理,并通过静态实验对比了降噪前后定位结果精度。结果表明,在两种降噪方案中,3种方法都能够有效提高定位结果精度,且卡尔曼滤波方法的效果最优,此外,对于同一点位,两种降噪方案得出的定位结果精度基本一致。Aiming at the problem of positioning result influenced by high frequency noise existing in raw observation data in ultra wideband positioning.In this paper,wavelet transform,Vondrak filter and Kalman filter were used to denoise the raw observation data and the positioning result respectively.The positioning results were compared before and after noise reduction by the static experiment.The results showed that the three methods could effectively improve the positioning accuracy among the two noise reduction schemes,and the Kalman filter method was the best.In addition,the accuracy of the positioning results obtained by the two noise reduction schemes at the same point was basically the same.

关 键 词：超宽带定位 噪声 小波变换 Vondrak 卡尔曼滤波 

分 类 号：P228.4[天文地球—大地测量学与测量工程]