GPS World, March 2013

Signal Processing INNOVATION to the IGS GIM were computed The results plotted by elevation angle are displayed in FIGURE 5 for all seven stations processed all satellite arcs from the same station are plotted using the same color The overall agreement between the global model and the station derived VTECs is fairly good with a bias of about 1 TECU Still the top panel demonstrates that at high elevation angles discrepancies between VTEC values derived from standard leveled observations and the ones obtained from the model have a spread of nearly 6 TECU With integer leveled observations see bottom panel this spread is reduced to approximately 2 TECU It is important to realize that the dispersion can be explained by several factors such as remaining leveling errors the inexact receiver and satellite bias estimates and inaccuracies of the global model It is nonetheless expected WKDW OHYHOLQJ HUURUV DFFRXQW IRU WKH PRVW VLJQL FDQW SDUW RI this error for standard leveled observations For satellites observed at a lower elevation angle the spread between arcs is similar for both methods except for station UCLU in panel a for which the estimated VWDWLRQ SDUDPHWHU ORRNV VLJQL FDQWO ELDVHG V VWDWHG previously the reason is that leveling errors are reduced when divided by the mapping function The latter also introduces further errors in the comparisons which explains why a wider spread should typically be associated with low elevation angle satellites Nevertheless it should be clear from Figure 5 that integer leveled observations offer a better consistency than standard leveled observations Conclusion The technique of integer leveling consists of introducing preferably integer ambiguity parameters obtained from PPP into the geometry free combination of observations This process removes the arc dependency of the signals and allows integer leveled observations to be used with any existing TEC estimation software While leveling errors of a few TECU exist with current procedures this type of error can be eliminated through use of our procedure SURYLGHG WKDW FDUULHU SKDVH DPELJXLWLHV DUH HG WR WKH SURSHU LQWHJHU YDOXHV V D FRQVHTXHQFH 67 YDOXHV derived from nearby stations are typically more consistent with each other Unfortunately subsequent steps involved in generating VTEC maps such as transforming STEC to VTEC and interpolating VTEC values between stations DWWHQXDWH WKH EHQH WV RI XVLQJ LQWHJHU OHYHOHG REVHUYDWLRQV There are still ongoing challenges associated with the GIM generation process particularly in terms of latency and three dimensional modeling Since ambiguity resolution in PPP can be achieved in real time we believe WKDW LQWHJHU OHYHOHG REVHUYDWLRQV FRXOG EHQH W QHDU UHDO time ionosphere monitoring Since ambiguity parameters are constant for a satellite pass provided that there are no cycle slips integer ambiguity values that is the leveling information can be carried over from one map generation process to the next Therefore this methodology could reduce leveling errors associated with short arcs for instance QRWKHU SURVSHFWLYH EHQHILW RI LQWHJHU OHYHOHG observations is the reduction of leveling errors contaminating data from low Earth orbit LEO satellites which is of particular importance for three dimensional TEC modeling Due to their low orbits LEO satellites W SLFDOO WUDFN D 36 VDWHOOLWH IRU D VKRUW SHULRG RI WLPH V a consequence those short arcs do not allow code noise and multipath to average out potentially leading to important leveling errors On the other hand undifferenced ambiguity LQJ IRU 2 VDWHOOLWHV DOUHDG KDV EHHQ GHPRQVWUDWHG and could be a viable solution to this problem Evidently more research needs to be conducted to fully DVVHVV WKH EHQH WV RI LQWHJHU OHYHOHG REVHUYDWLRQV 6WLOO we think that the results shown herein are encouraging and offer potential solutions to current challenges associated with ionosphere monitoring Acknowledgments We would like to acknowledge the help of Paul Collins IURP 15 DQ LQ SURGXFLQJ LJXUH DQG WKH QDQFLDO contribution of the Natural Sciences and Engineering Research Council of Canada in supporting the second and third authors This article is based on two conference SDSHUV H QLQJ WKH DVLV RI DQ μ QWHJHU HYHOOLQJ Procedure for Estimating Slant Total Electron Content presented at ION GNSS 2011 and Ionospheric Monitoring 8VLQJ μ QWHJHU HYHOOHG 2EVHUYDWLRQV SUHVHQWHG DW 21 GNSS 2012 ION GNSS 2011 and 2012 were the 24th and 25th International Technical Meetings of the Satellite Division of The Institute of Navigation respectively ION GNSS 2011 was held in Portland Oregon September 19 23 2011 while ION GNSS 2012 was held in Nashville Tennessee September 17 21 2012 SIMON BANVILLE is a Ph D candidate in the Department of Geodesy and Geomatics Engineering at the University of New Brunswick UNB under the supervision of Dr Richard B Langley His research topic is the detection and correction of cycle slips in GNSS observations He also works for Natural Resources Canada on real time precise point positioning and ambiguity resolution WEI ZHANG received his M Sc degree 2009 in space science from the School of Earth and Space Science of Peking University China He is currently an M Sc E student in the Department of Geodesy and Geomatics Engineering at UNB under the supervision of Dr Langley His research topic is the assessment of three dimensional regional ionosphere tomographic models using GNSS measurements MORE ONLINE Further Reading For references related to this article go to gpsworld com and click on Innovation in the navigation bar www gpsworld com March 2013 GPS World 49