Observation Quality Assessment and Performance of GNSS Standalone Positioning with Code Pseudoranges of Dual-Frequency Android Smartphones

The new generation of Android smartphones is equipped with GNSS chips capable of tracking multi-frequency and multi-constellation data. In this work, we evaluate the positioning performance and analyze the quality of observations collected by three recent smartphones, namely Xiaomi Mi 8, Xiaomi Mi 9, and Huawei P30 pro that take advantage of such chips. The analysis of the GNSS observation quality implies that the commonly employed elevation-dependent function is not optimal for smartphone GNSS observation weighting and suggests an application of the C/N0-dependent one. Regarding smartphone code signals on L5 and E5a frequency bands, we found that they are characterized with noticeably lower noise as compared to E1 and L1 ones. The single point positioning results confirm an improvement in the performance when the weights are a function of the C/N0-rather than those dependent on the satellite elevation and that a smartphone positioning with E5a code observations significantly outperforms that with E1 signals. The latter is expressed by a drop of the horizontal RMS from 8.44 m to 3.17 m for Galileo E1 and E5a solutions of Xiaomi Mi 9 P30, respectively. The best positioning accuracy of multi-GNSS single-frequency (L1/E1/B1/G1) solution was obtained by Huawei P30 with a horizontal RMS of 3.24 m. Xiaomi Mi 8 and Xiaomi Mi 9 show a horizontal RMS error of 4.14 m and 4.90 m, respectively

GNSS-SDR pseudorange quality and single point positioning performance assessment

In recent years, we have witnessed a growing demand for GNSS receiver customization in terms of modification of signal acquisition, tracking, and processing strategies. Such demands may be addressed by software-defined receivers (SDRs) which refers to an ensemble of hardware and software technologies and allows re-configurable radio communication architectures. The crux of the SDRs is the replacement of the hardware components through software modules. In this paper, we assess the quality of GNSS observables acquired by SDR against the selected u-blox low-cost receiver. In the following, we investigate the performance level of single point positioning that may be reached with an ultra-low-cost SDR and compare it to that of the low-cost GNSS receiver. The signal quality assessment revealed a comparable performance in terms of carrier-to-noise density ratio and a significant out-performance of the u-blox over SDR in terms of code pseudorange noise. The experimentation in the positioning domain proved that software-defined receivers may offer a position solution with three-dimensional standard deviation error at the level of 5.2 m in a single point positioning mode that is noticeably poorer accuracy as compared to the low-cost receiver. Such results demonstrate that there is still room for SDR positioning accuracy improvement

GNSS-based analysis of high latitude ionospheric response on a sequence of geomagnetic storms performed with ROTI and a new relative STEC indicator

This contribution presents a combined analysis of the occurrence of polar patches and development of auroral oval triggered by a sequence of geomagnetic storms in March 2012. The detection of the patches was realized with relative slant TEC (STEC) values extracted from geometry-free combination using novel, iterative algorithm of 4-degree polynomial fitting. The proposed approach allows sensing of large structures with high temporal resolution, since it provides epoch-wise information on STEC enhancement in respect to the specified background level. The comparative analysis of the novel indicator with well-known Rate of TEC Index (ROTI) has shown that the new one ensures the more detailed view on patch propagation. The applicability of relative STEC values was also preliminary confirmed by their validation with plasma density data obtained from SWARM mission. The evolution of auroral oval, involving its expansion as well as the intensity of TEC fluctuation, was performed with ROTI parameter. The results of patch occurrence and oval expansion for different geomagnetic conditions are consistent with previous works what proves the feasibility of comprehensive global navigation satellite system (GNSS)-based analyses with the proposed methodology

An analysis of multi-GNSS observations tracked by recent Android smartphones and smartphone-only relative positioning results

In this study we assess the quality of multi-GNSS observations of recent Android smartphones. The results reveal a significant drop of smartphone carrier-to-noise density ratio (C/N0) with respect to geodetic receivers, and discernible differences among constellations and frequency bands. We show that the higher the elevation of the satellite, the larger discrepancy in C/N0 between the geodetic receivers and smartphones. Thus we show that a C/N0 weighting scheme may be superior to the elevation dependent one usually adopted for GNSS observations. We also discover that smartphone code pseudoranges are noisier by about one order of magnitude as compared to geodetic receivers, and that the code signals on L5 and E5a outperform those on L1 and E1, respectively. It is shown that smartphone phase observations are contaminated by the effects that can destroy the integer property and time-constancy of the ambiguities. There are long term drifts detected for GPS L5, Galileo E1, E5a and BDS B1 phase observations of Huawei P30. We highlight competitive phase noise characteristics for the Xiaomi Mi 8 when compared to the geodetic receivers. We also reveal a poor quality of other than GPS L1 phase signals for the Huawei P30 smartphones related to the unexpected drifts of the observations. Finally, the positioning experiment proves that it is feasible to obtain a precise cm-level solution of a smartphone to smartphone relative positioning with fixed integer ambiguities

The implications of ionospheric disturbances for precise GNSS positioning in Greenland

Ionospheric irregularities impair Global Navigation Satellite System (GNSS) signals and, in turn, affect the performance of GNSS positioning. Such effects are especially evident at low and high latitudes, which are currently gaining the attention of research and industry sectors. This study evaluates the impact of ionospheric irregularities on GNSS positioning in Greenland. We assess the performance of positioning methods that meet the demands of a wide range of users. In particular, we address the needs of the users of mass-market single-frequency receivers and those who require a solution of high precision provided by geodetic dual-frequency receivers. We take advantage of the datasets collected during three ionospheric storms: the St. Patrick’s Day storm of March 17, 2015, the storm on June 22, 2015, and another on August 25–26, 2018. We discover a significant impact of the ionospheric disturbances on the ambiguity resolution performance and the accuracy of the float solution in Real Time Kinematics (RTK) positioning. Next, assessing the single-frequency ionosphere-free Precise Point Positioning (PPP), we demonstrate that the model is generally unaffected by ionospheric disturbances. Hence, the model is predestined for the application by the users of single-frequency receivers in the areas of frequent ionospheric disturbances. Finally, based on the observation analyses, we reveal that phase signals on the L2 frequency band are more prone to cycle slips induced by ionospheric irregularities than those transmitted on the L1. Such signal properties explain a noticeable decline in the dual-frequency RTK performance during the ionospherically disturbed period and merely no effect for the single-frequency ionosphere-free PPP model.Peer ReviewedPostprint (published version

Method for forecasting ionospheric electron content fluctuations based on the optical flow algorithm

We present the optical flow algorithm for forecasting the rate of total electron content index (OFROTI). It consists of a method for predicting maps of rapid fluctuations of ionospheric electron content in terms of global navigation satellite system (GNSS) dual-frequency phase measurements of the rate of change of total electron content index (ROTI). The forecast is made in space and time, at horizons up to more than 6 h. These forecast maps will consist of the ROTI spatial distribution in the northern hemisphere above 45° latitude. The prediction method models the ROTI spatial distribution as a pseudoconservative flux, i.e., exploiting the inertia of the flux of ROTI to determine the future position. This idea is implemented as a modification of the optical flow image processing technique. The algorithm has been modified to deal with the nonconservation of the ROTI quantity in time. We show that the method can predict both, the local value of ROTI and also the regions with ROTI above a given level, better than the prediction using the current map as forecast, i.e., predicting by a current map from horizons of 15 min up to 6 h. The method was tested on 11 representative active and calm days during 2015 and 2018 from the multi-GNSS (GPS, GLONASS, Galileo, and Beidou) multifrequency measurements of more than 250 multi-GNSS receivers above 45°N latitude, including the high rate (1 Hz) measurements of Greenland geodetic network (GNET) network among the International GNSS Service network.This work is funded by ESA ITT “Forecasting Space Weather Impacts on Navigation Systems in the Arctic (Green-land Area)” Expro+, Activity No. 1000026374. The GNET GNSS observations from Greenland was kindly provided by The Danish Agency for Data Supply and Efficiency, in the Danish Ministry of Energy, Utilities and Climate, Copenhagen, DenmarkPeer ReviewedPostprint (author's final draft

Improved MSTID modelling and impact on precise GNSS processing

Peer ReviewedPreprin

Direct MSTID mitigation in precise GPS processing

This is the peer reviewed version of the following article: Hernandez, M., Wielgosz, P., Paziewski, J., Krypiak-Gregorczyk, A., Krukowska, M., Stepniak, K., Kaplon, J., Hadas, T., Sosnica, K., Bosy, J., Orús, R., Monte, E., Yang, H., Garcia-Rigo, A., Olivares-Pulido, G. Direct MSTID mitigation in precise GPS processing. "Radio science", Març 2017, vol. 52, núm. 3, p. 321-337, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/2016RS006159/abstract. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-ArchivingIn this paper, the authors summarize a simple and efficient approach developed to mitigate the problem in precise GNSS positioning originated by the most frequent ionospheric wave signatures: the Medium Scale Travelling Ionospheric Disturbances (MSTIDs). The direct GNSS Ionospheric Interferometry technique (hereinafter dGII), presented in this paper, is applied for correcting MSTID effects on precise Real Time Kinematic (RTK) and tropospheric determination. It consists of the evolution of the former climatic Differential Delay Mitigation Model for MSTIDs (DMTID), for real-time conditions, using ionospheric data from a single permanent receiver only. The performance is demonstrated with networks of GNSS receivers in Poland, treated as users under real-time conditions, during two representative days in winter and summer seasons (days 353 and 168 of year 2013). In range domain, dGII typically reduces the ionospheric delay error up to 10-90% of the value when the MSTID mitigation model is not applied. The main dGII impact on precise positioning is that we can obtain reliable RTK position faster. In particular the ASR (ambiguity success rate) parameter increases, from 74% to 83%, with respect to the original uncorrected observations. The average of time to first fix is shortened from 30s to 13s. The improvement in troposphere estimaton, due to any potential impact of the MSTID mitigation model, was most difficult to demonstrate.Peer ReviewedPostprint (author's final draft

Roadmap on signal processing for next generation measurement systems

Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.AerodynamicsMicrowave Sensing, Signals & System