摘要
为了解决电离层扰动和低高度角下非差数据的实时周跳探测与修复问题,提出了一种基于TurboEdit历元差模型的优化算法。首先在无几何距离组合历元差中加入滑动多项式拟合法提取电离层延迟与多路径效应误差的趋势项,通过选择合适的阈值,增强对小周跳的探测能力;然后针对历元差模型无法区别周跳与粗差的问题,引入统计诊断中的Score检验量并构建了基于Score检验的周跳与粗差分离模型,避免了粗差引起的周跳误探现象;最后在成功探测出周跳后,使用探测量最小1范数准则来选取正确的周跳修复值。采用国际GNSS服务站GPS非差数据对所提算法进行验证,实验结果表明,该优化算法能够有效抑制低高度角时的多路径效应和电离层延迟误差,实时剔除粗差并准确修复周跳,对小周跳具有较高的探测灵敏度与较低的误判率。
Objectives:Carrier phase is the key to achieve high precision positioning,and its quality determines the reliability of positioning results.Due to the development and needs of society,the data acquisition environment is becoming more and more complex,and the real-time requirements are also constantly improving,which greatly increases the probability of cycle slip and increases the difficulty of cycle slip detection.However,some cycle slip detection algorithms commonly used at present have poor detection effect in such environments as active ionosphere,low elevation angle,occlusion,etc.,which lead to false detection and missed detection.Methods:In order to solve these problems,firstly,an improved algorithm based on TurboEdit epoch difference model is proposed.The trend terms of ionospheric delay and multipath effect errors are extracted by adding sliding polynomial fitting method to the epoch difference of GF(Geometry-Free),and by choosing appropriate threshold,the detection ability of small cycle slips is enhanced.Then,to solve the problem that epoch difference model can not distinguish cycle slip and gross errors,Score test in statistical diagnosis is introduced and constructed.A cycle slip and gross errors separation model based on Score test is built to avoid the phenomenon of cycle slip detection caused by gross errors.Finally,the improved GF epoch difference model is combined with Melbourne Wubbena(MW)combination to repair cycle slip,and the minimum one norm criterion of detection is used to select the correct repair value of cycle slip.The algorithm is verified by using the GPS un-differenced data of IGS(International GNSS Service) stations.Results:The cycle slips obtained by the improved GF epoch difference still have high detection sensitivity for small cycle slips.The simulated small cycle slip,continuous cycle slip and special cycle slip are detected,such as(1,1),(-1,-1),(5,4),etc.Two successive abnormal epochs detected by GF epoch difference optimization algorithm have successfully separated the simulated(1,1),(0,0.5) small gross errors after a Score test and deviation test.When GF and MW probes are used to calculate cycle slip directly,there are errors in cycle slip calculation due to the excessive noise of MW probe,and the calculation error reaches 3 weeks.By using the improved minimum one norm of GF epoch differential survey and MW survey,the correct cycle slip solution is found successfully.Conclusions:In the aspect of cycle slip detection,the improved GF epoch difference method can weaken the influence of ionospheric delay variation and multipath effect,and improve the accuracy of cycle slip detection.At the same time,through the appropriate threshold selection,even in the case of high ionospheric scintillation,small cycle slip and continuous cycle slip can be detected accurately.In the separation of cycle slip and gross errors,the fitting residual is replaced by the prediction residual to improve the Score test,which makes it suitable for anomaly test in real-time situation.Based on this,the separation model of cycle slip and gross errors can separate the gross errors from cycle slip accurately,avoid the misjudgment of cycle slip,and improve the reliability of real-time TurboEdit cycle slip detection method.In the aspect of cycle slip repair,the criterion of cycle slip repair success is to minimize the one norm of the probe change caused by correct cycle slip repair.Compared with solving cycle slip solution directly and rounding,this proposed algorithm can not only verify the correctness of cycle slip solution,but also correct the wrong cycle slip solution in real-time,get the accurate cycle slip value,and repair the subsequent observation value of epoch.
作者
夏磊
赖祖龙
梅长松
焦晨晨
蒋可
潘雄
XIA Lei;LAI Zulong;MEI Changsong;JIAO Chenchen;JIANG Ke;PAN Xiong(School of Geography and Information Engineering(Wuhan),China University of Geosciences,Wuhan 430078,China)
出处
《武汉大学学报（信息科学版）》
EI
CAS
CSCD
北大核心
2021年第6期920-927,共8页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金(41874009)。
