一种基于交叉证认技术的自适应小波变换及其在削减GPS多路径误差中的应用

Abstract

多路径效应影响是目前限制GPS定位精度进一步提高的瓶颈。提出用交叉证认技术自动识别小波分解的信号层,再通过小波重构实现降噪和信号提取,并将该方法应用于GPS多路径误差的削减中。对模拟数据和实际GPS观测资料的分析表明,该方法能合理分离不同噪声水平下资料序列中的信号和噪声;当噪声水平小于信号振幅的一半时,能成功分离资料序列中的高频信号。同时,运用该方法得到的多路径改正模型和GPS多路径效应的重复性,可有效地削弱多路径效应的影响,提高GPS定位精度。 GPS multipath disturbance is a bottleneck problem that limits accuracy of Global Positioning System(GPS) positioning.A method based on the technique of cross-validation to automatically identify wavelet signal layers is developed for separating noise from signals in data series,and applied to mitigate GPS multipath effects.Experiments with both simulated data series and real GPS observations show that the method is a powerful signal decomposer,which can successfully separate noise from signals as long as the noise level is lower than about half of the magnitude of the signals.A multipath correction model can be derived with the proposed method and the sidereal day-to-day repeating property of GPS multipath signals can be used to remove multipath effects in subsequent days of GPS observations,and therefore improve the quality of the GPS results.