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

Abstract

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.

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): NmF2 and hmF2

“…These issues are, however, not solely limited to the IRI. Themens et al [2013] demonstrated that the sparsity of data in high-latitude regions contributes to significant errors in the representation of TEC in these regions by global TEC maps, and Themens et al [2015] showed that the strong gradients in TEC at high latitudes significantly degrade the performance of standard Global Positioning System (GPS)-based TEC calibration techniques. Also, Athieno et al [2015] and Athieno and Jayachandran [2016] show that standard HF communication models exhibit significant errors at high latitudes, largely due to errors in the URSI and International Radio Consultative Committee critical frequency maps, which are also used in the IRI.…”

Assessment of BeiDou differential code bias variations from multi-GNSS network observations

“…Compared to satellite DCBs, the receiver DCBs are less stable, and their magni- tudes and variations show large differences for different types of receivers. The receiver DCB seems to be related to the temperature around antennas (Coster et al, 2013;Yasyukevich et al, 2015;Themens et al, 2015). Besides its intrinsic variations, the estimated DCB series includes the signal associated with ionospheric anomalous variations and other errors, such as the multipath effect and the high-order effect of ionospheric delay, that are ignored in traditional TEC and DCB estimation, since non-modeling errors will affect the DCB estimation (Petrie et al, 2011).…”

Enhanced Polar Outflow Probe Ionospheric Radio Occultation Measurements at High Latitudes: Receiver Bias Estimation and Comparison With Ground‐Based Observations

“…The shell height is taken as the center of mass of the ionosphere above CASSIOPE (Komjathy & Langley, ; Themens et al, ): where N e ( h ) is the electron density at height h . Electron densities below auroral latitudes are taken from the International Reference Ionosphere (IRI) 2012 empirical model, which provides electron densities up to 2,000 km altitude.…”

“…The shell height is taken as the center of mass of the ionosphere above CASSIOPE (Komjathy & Langley, 1996;Themens et al, 2015):…”

“…Large differences of 1.5-2.5 TECU coincide with large bias sensitivities in Figure 7a. As shown in Themens et al (2015), errors in the MSD method due to the use of a fixed shell height can introduce artificial seasonal and solar cycle variabilities in the bias estimates. Although an increase in bias difference is observed each spring in Figure 7b, there is no clear seasonal dependence.…”