A new method for GLONASS inter-frequency bias estimation based on long baselines
- 251 Downloads
Frequency division multiplexing of GLONASS signals causes inter-frequency bias (IFB) in receiving equipment. IFB significantly increases the difficulties of fixing GLONASS ambiguities and limits the accuracy and reliability of GLONASS positioning and orbit determination. Accurately estimating and calibrating IFB can effectively solve such a problem. However, at present, most methods of IFB estimation are based on zero and short baselines, in which case it is not only difficult to realize fast and efficient IFB estimation but also one cannot fully utilize publicly available IGS and CORS data. Therefore, we present a new method for GLONASS IFB estimation based on long baselines. First, to weaken the influence of inter-frequency code bias, the wide-lane ambiguities are calculated directly based on the wide-lane combinations of observations. Then, according to the range of inter-frequency phase bias (IFPB) rates, a IFPB defined as the difference in IFPBs between adjacent frequencies, a step-by-step search schedule is designed to remove the impacts of IFPB on wide-lane and narrow-lane ambiguity resolution. Finally, after fixing integer wide-lane and narrow-lane ambiguities, the IFPB rate can be estimated. An experimental network is set up to verify the validity of this method; the experiment includes the data observed for 31 days at 542 stations in Europe and North America. The IFPB rates of 38 receiver types from nine manufacturers are successfully determined. Experimental results show that the estimated IFPB rates for the same receiver type stabilize within a month with a standard deviation of less than 1.4 mm/∆f (millimeters per frequency number increment, ∆f denotes the frequency difference of adjacent GLONASS frequencies with frequency number increment of 1). Generally, the difference in IFPB rates of receiver types from the same manufacturer does not exceed 2.5 mm/∆f. However, the estimated IFPB rates of Septentrio’s newly produced receivers, as compared with that of the old receiver types, show a rate difference of up to 50 mm/∆f. This significant difference should be considered for practical applications.
KeywordsGLONASS Long baselines Ionospheric-free ambiguity resolution Inter-frequency bias
Thanks to IGS and ESA/ESOC for providing GLONASS data and precise products. The GLONASS data collected from EPN, American CORS and CACS were used in this study, which is acknowledged. This study was supported by The National Science Fund for Distinguished Young Scholars (No. 41525014), Changjiang Scholars Program and together with the Surveying and Mapping Basic Research Program of National Administration of Surveying, Mapping and Geoinformation (No. 15-02-01). We thank all anonymous reviewers for their valuable, constructive and prompt comments.
- Banville S, Collins P, Lahaye F (2013) Concepts for undifferenced GLONASS ambiguity resolution. In: Proceedings of ION GNSS 2013, Institute of Navigation, Nashville, Tennessee, USA, Sep 16–20, pp 1186–1197Google Scholar
- Bassiri S, Hajj G (1993) Higher-order ionospheric effects on the global positioning system observables and means of modeling them. Manuscr Geod 18(5):280Google Scholar
- ICD (2008) GLONASS Interface Control Document, 5.1 edn. Russian Institute of Space Device Engineering, Moscow Google Scholar
- Liu J, Ge M (2003) PANDA software and its preliminary result of positioning and orbit determination. Wuhan Univ J Nat Sci 8(2B):603–609Google Scholar
- Mervart L (1995) Ambiguity resolution techniques in geodetic and geodynamic applications of the global positioning system. Ph.D. thesis, University of BerneGoogle Scholar
- Pratt M, Burke B, Misra P (1998) Single-epoch integer ambiguity resolution with GPS-GLONASS L1-L2 Data. In: Proceedings of ION GPS 1998, Institute of Navigation, pp 389–398Google Scholar
- Reussner N, Wanninger L (2011) GLONASS inter-frequency biases and their effects on RTK and PPP carrier-phase ambiguity resolution. In: Proceedings of ION GNSS 2011, Institute of Navigation, Portland, Oregon, USA, September 19-23, pp 712–716Google Scholar
- Revnivykh S (2010) GLONASS status and progress. In: Proceedings of ION GNSS 2010, Institute of Navigation, Portland, Oregon, USA, Sep 21–24, pp 609–633Google Scholar
- Shi C, Zhao Q, Geng J, Lou Y, Ge M, Liu J (2008) Recent development of PANDA software in GNSS data processing. In: Proceedings of SPIE 2008, international conference on earth observation data processing and analysis (ICEODPA), Dec 29, vol 7285, pp 231–249Google Scholar
- Sleewagen J, Simsky A, De Wilde W, Boon F, Willems T (2012) Demystifying GLONASS inter-frequency carrier phase biases. Inside GNSS 7(3):57–61Google Scholar
- Wanninger L, Wallstab-Freitag S (2007) Combined processing of GPS, GLONASS, and SBAS code phase and carrier phase measurements. In: Proceedings of ION GNSS 2007, Institute of Navigation, Fort Worth, Texas, USA, Sep 25–28, pp 866–875Google Scholar