摘要
针对智能全站仪在诸如FAST等尖端科学实验中的广泛运用，对全站仪动态测量数据序列特征进行分析的基础上，提出综合运用回归分析去除运动趋势项、小波降噪减弱偶然误差项和频谱分析提取系统误差项等方法对动态测量数据进行处理，从而可以获得仪器进动跟踪带来的系统误差频率，在合作目标运动角速度为128pps时系统进动误差频率为0．2～0．4Hz，并与理论分析结果相比较，比较结果说明该方法实用有效，有一定应用价值。
Aiming that ,the intellective total stations are widely applied in the top science experiments such as FAST, this paper firstly analyzes the character of the total station＇s dynamic surveying series data, then uses regression analysis to remove the moving trend item, wavelet denoising to weaken the random error, and frequency analysis to get system error information integrated to deal with the TCA2003 experimental data. In the end, the paper gives that the system error frequency is about 0.2-0.4 Hz when the cooperation object＇s moving angle rate is 128 pps, which is the same as the result of the theory analysis. The analysis method is raluable.
出处
《测绘工程》
CSCD
2008年第4期28-30,共3页
Engineering of Surveying and Mapping
关键词
动态测量
回归分析
小波降噪
频谱分析
ATR
dynamic surveying
regression analysis
wavelet denoising
frequency analysis
ATR
