考虑伪距残差相关性的北斗系统卫星数据质量异常监测算法

An Abnomal Monitoring Algorithm for Satellite Data Quality of the Beidou System Considering the Correlation of Pseudo-distance Residuals

针对北斗卫星系统中由欺骗干扰引起数据异常的问题,考虑伪距残差相关性,设计北斗系统卫星数据质量异常监测系统。对北斗导航卫星系统(Beidou navigation satellite system,BDS)的时延具有变化特征的欺骗干扰数据质量进行监测,进一步提升动态导航定位准确度。首先,构建具有迭代特征的多模全球导航卫星系统(global navigationsatellitesystem,GNSS)伪距相关组合定位算法模型。利用GNSS接收机和惯性导航系统(inertial navigation system,INS)的伪距、伪距率差值进行卡尔曼滤波,并获得伪距、伪距率残差。利用欺骗干扰时延特征构建残差滑动方差模型。然后,利用当前和历史残差数据构造残差滑动方差(residual sliding variance,RSV)检测量,最后不断迭代更新伪距率和伪距,与阈值相对实现进行欺骗检测。试验研究表明,该系统检测存在欺骗节点时的误差率在3%左右,准确度提升约60%。

Aiming at the problem of data abnormality caused by spoofing interference in the Beidou satellite system,a satellite data quality abnomal monitoring system for the Beidou satellite system is designed considering the pseudo-distance residual correlation.The quality of deception interference data of Beidou navigation satellite system(BDS)with varying delay characteristics is monitored to further improve the accuracy of dynamic navigation and positioning.Firstly,a multi-mode GNSS pseudo distance correlation combined positioning algorithm model with iterative characteristics is constructed.Kalman filtering is performed by using the pseudo range and pseudo range rate difference of global navigation satellite system(GNSS)receiver and inertial navigation system(INS).The pseudodistance and pseudo-distance rate residuals are obtained.The residual sliding variance model is constructed by using the deception interference delay feature.Then,the residual sliding variance(RSV)detection quantity is constructed using the current and historical residual data.Finally,the pseudo-range rate and pseudo-range are iteratively updated to realize the deception detection relative to the threshold value.The experimental results show that the error rate of the system is about 3%,and the accuracy is improved by about 60%.