The influence of geomagnetic storms on the estimation of GPS instrumental biases

Zhang, W.; Zhang, D. H.; Xiao, Zuo

doi:10.5194/angeo-27-1613-2009

Cited by 47 publications

(31 citation statements)

References 24 publications

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“…While several techniques exist for determining these biases, one must take care in their application in regions outside their initial design [Lanyi and Roth, 1988;Ma and Maruyama, 2003;Ma et al, 2005;Rideout and Coster, 2006;Arikan et al, 2008]. Recent studies have attempted to characterize variabilities in these biases estimated through single-station approaches using real data and simulations [Ciraolo et al, 2007;Mazzella, 2009;Zhang et al, 2009;Brunini and Azpilicueta, 2010;Zhang et al, 2010;Conte et al, 2011;Coster et al, 2013]. These studies highlight the need to understand not only the nature of true bias variability but also the impact of the fundamental assumptions made in standard bias estimation techniques on bias estimation.…”

Section: Introductionmentioning

confidence: 99%

The nature of GPS differential receiver bias variability: An examination in the polar cap region

2015

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While modern GPS receiver differential code bias estimation techniques have become highly refined, they still demonstrate unphysical behavior, namely, notable solar cycle variability. This study investigates the nature of these seasonal and solar cycle bias variabilities in the polar cap region using single‐station bias estimation methods. It is shown that the minimization of standard deviation bias estimation technique is linearly dependent on the user's choice of shell height, where the sensitivity of this dependence varies significantly from 1 total electron content unit (1 TECU = 1016 el m−2) per 4000 km in solar minimum winter to in excess of 1 TECU per 90 km during solar maximum summer. Using an ionosonde, we find appreciable shell height variability resulting in bias variabilities of up to 2 TECU. Comparing northward face Resolute Incoherent Scatter Radar (RISR‐N) measurements to a collocated GPS station, we find that RISR‐derived GPS receiver biases vary seasonally but not with solar cycle. RMS differences between bias estimation methods and observation between 2009 and 2013 were found to range from 2.7 TECU to 3.4 TECU, depending on method. To account for the erroneous solar cycle variability of standard bias estimation approaches, we linearly fit these biases to sunspot number, removing the trend. RMS errors after sunspot detrending these biases are reduced to 1.91 TECU. Also, these ISR‐derived and sunspot‐detrended biases are fit to ambient temperature, where a significant correlation is found. By using these temperature‐fitted biases we further reduce RMS errors to 1.66 TECU. These results can be taken as further evidence of temperature‐dependent dispersion in the GPS cabling and antenna hardware.

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Section: Introductionmentioning

confidence: 99%

The nature of GPS differential receiver bias variability: An examination in the polar cap region

2015

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“…The accuracy of instrumental bias estimated using GPS observations in different solar cycle period was studied initially. It is found that the RMS of the instrumental bias estimated using GPS data observed during solar minimum period is much less than that estimated during solar maximum years (Zhang, 2009b). On the other hand, because the error analysis about the instrumential bias in this study is just based on the results obtained from one estimation methods described in Sect.…”

Section: Results and Analysismentioning

confidence: 98%

“…During storm period, the ionosphere exhibits severe deviation from background ionosphere that lasts from several hours to several days and covers regionally or globally. Based on the GPS data observed in mid-latitude region from 2004 to 2006, the instrumental bias were obtained using a estimation method of instrumental bias, and the differences of the instrumental bias between the active geomagnetic days and the quiet geomagnetic days were studied (Zhang et al, 2009a). It is found that the standard deviation of instrumental biases during active geomagnetic days is obviously larger than that during the quiet days, and this deviation can degrade the accuracy of ionospheric TEC derived from GPS observations.…”

Section: Introductionmentioning

confidence: 99%

Accuracy analysis of the GPS instrumental bias estimated from observations in middle and low latitudes

Zhang

et al. 2010

Ann. Geophys.

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Abstract. With one bias estimation method, the latituderelated error distribution of instrumental biases estimated from the GPS observations in Chinese middle and low latitude region in 2004 is analyzed statistically. It is found that the error of GPS instrumental biases estimated under the assumption of a quiet ionosphere has an increasing tendency with the latitude decreasing. Besides the asymmetrical distribution of the plasmaspheric electron content, the obvious spatial gradient of the ionospheric total electron content (TEC) along the meridional line that related to the Equatorial Ionospheric Anomaly (EIA) is also considered to be responsible for this error increasing. The RMS of satellite instrumental biases estimated from mid-latitude GPS observations in 2004 is around 1 TECU (1 TECU = 10 16 /m 2 ), and the RMS of the receiver's is around 2 TECU. Nevertheless, the RMS of satellite instrumental biases estimated from GPS observations near the EIA region is around 2 TECU, and the RMS of the receiver's is around 3-4 TECU. The results demonstrate that the accuracy of the instrumental bias estimated using ionospheric condition is related to the receiver's latitude with which ionosphere behaves a little differently. For the study of ionospheric morphology using the TEC derived from GPS data, in particular for the study of the weak ionospheric disturbance during some special geo-related natural hazards, such as the earthquake and severe meteorological disasters, the difference in the TEC accuracy over different latitude regions should be paid much attention.

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“…Researchers in the first group have focused their attentions on analyzing the receiver DCB estimates that are by-products of vTEC determination [28][29][30]. Actually, these estimates with daily time resolution may be subject to severe modeling errors, originating mainly from the imperfection of vTEC mathematical representations.…”

Section: Introductionmentioning

confidence: 99%

Characterization of multi-GNSS between-receiver differential code biases using zero and short baselines

Zhang

Teunissen

2015

Science Bulletin

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Care should be taken to minimize adverse impact of receiver differential code biases (DCBs) on global navigation satellite system (GNSS)-derived ionospheric parameters. It is therefore of importance to ascertain the intrinsic characteristics of receiver DCBs, preferably in the context of new-generation GNSS. In this contribution, we present a method that enables time-wise retrieval of between-receiver DCBs (BR-DCBs) from dualfrequency, code-only measurements collected by a pair of co-located receivers. This method is applicable to the US GPS as well as to a new set of GNSS constellations including the Chinese BeiDou, the European Galileo and the Japanese QZSS. With the use of this method, we determine the multi-GNSS BR-DCB time-wise estimates covering a time period of up to 2 years (January 2013-March 2015) with a 30-s time resolution for five receiverpairs (four zero and one short baselines). For the BR-DCB time-wise estimates pertaining to an arbitrary receiver-pair and constellation, we demonstrate their promising intraday stability by means of statistical hypothesis testing. We also find that the BeiDou BR-DCB daily weighted average (DWA) estimates show a dependence on satellite type, in particular for receiver-pairs of mixed types. Finally, we demonstrate that long-term variability in BR-DCB DWA estimates can be closely associated with hardware temperature variations inside the receivers.

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The influence of geomagnetic storms on the estimation of GPS instrumental biases

Cited by 47 publications

References 24 publications

The nature of GPS differential receiver bias variability: An examination in the polar cap region

The nature of GPS differential receiver bias variability: An examination in the polar cap region

Accuracy analysis of the GPS instrumental bias estimated from observations in middle and low latitudes

Characterization of multi-GNSS between-receiver differential code biases using zero and short baselines

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