Tightly combined GPS/Galileo RTK for short and long baselines: Model and performance analysis

To ensure the compatibility and interoperability with modernized GPS, Galileo satellites are capable of broadcasting navigation signals on carrier phase frequencies that overlap with GPS, i.e., GPS/Galileo L1-E1/L5-E5a. Moreover, the GPS/Galileo L2-E5b signals have different frequencies with wavelength differences smaller than 4.2?mm. Such overlapping and narrowly spaced signals between GPS and Galileo bring the opportunity to use the tightly combined double-differenced (DD) model for precise real-time kinematic (RTK) positioning, resulting in improved performance of ambiguity resolution and positioning with respect to the classical standard or loosely combined DD model. In this paper, we focus on the model and performance assessment of tightly combined GPS/Galileo L1-E1/L2-E5b/L5-E5a RTK for short and long baselines. We first investigate the tightly combined GPS/Galileo DD observational model for both short and long baselines with simultaneously considering the GPS/Galileo overlapping and non-overlapping frequencies. Particularly, we introduce a reparameterization approach to solve the rank deficiency that caused by the correlation between the DISB parameters and the DD ionospheric parameters for both overlapping and non-overlapping frequencies. Then we present performance assessment for the tightly combined GPS/Galileo RTK model with real-time estimation of the differential inter-system bias (DISB) parameters for short and long baselines in terms of ratio value, ambiguity dilution of precision (ADOP), ambiguity conditional number, decorrelation number, search count, empirical success rate, time-to-first-fix (TTFF), and positioning accuracy. Results from both static and kinematic experiments demonstrated that compared to the loosely combined model, the tightly combined model can deliver improved performance of ambiguity resolution and precise positioning with different satellite visibility. For the car-driven short baseline experiment with 10° elevation cut-off angle, the tightly combined model can not only significantly increase the ratio value by approximately 27.5% (from 16.0 to 20.4), but also reduce the ambiguity ADOP, the conditional number, and the search count in LAMBDA by approximately 22.2% (from 0.027 to 0.021 cycles), 14.9% (from 199.2 to 169.6), and 25.4% (from 150.1 to 112.0), respectively. Comparable decorrelation number, empirical success rate, and positioning accuracy are also obtained. For the car-driven long baseline experiment, it is also observed that the ambiguity resolution performance in terms of the ratio value, the decorrelation number, the condition number, and the search count are significantly improved by approximately 18.5% (from 2.7 to 3.2), 22.0% (from 0.186 to 0.227), 55.9% (from 937.6 to 413.7), and 10.3% (from 43.8 to 39.3), respectively. Moreover, comparable ADOP, empirical success rate, and positioning accuracy are obtained as well. Additionally, the TTFF can be reduced (from 54.1 to 51.8 epochs with 10° elevation cut-off angle) as well from the results of static experiments.     

Forecasting space weather: Can new econometric methods improve accuracy?

Space weather forecasts are currently used in areas ranging from navigation and communication to electric power system operations. The relevant forecast horizons can range from as little as 24 h to several days. This paper analyzes the predictability of two major space weather measures using new time series methods, many of them derived from econometrics. The data sets are the A_p geomagnetic index and the solar radio flux at 10.7 cm. The methods tested include nonlinear regressions, neural networks, frequency domain algorithms, GARCH models (which utilize the residual variance), state transition models, and models that combine elements of several techniques. While combined models are complex, they can be programmed using modern statistical software. The data frequency is daily, and forecasting experiments are run over horizons ranging from 1 to 7 days. Two major conclusions stand out. First, the frequency domain method forecasts the A_p index more accurately than any time domain model, including both regressions and neural networks. This finding is very robust, and holds for all forecast horizons. Combining the frequency domain method with other techniques yields a further small improvement in accuracy. Second, the neural network forecasts the solar flux more accurately than any other method, although at short horizons (2 days or less) the regression and net yield similar results. The neural net does best when it includes measures of the long-term component in the data.     

A glimpse at the GOCE satellite gravity gradient observations

Since 30 September 2009, following the launch and in-orbit testing of the most sophisticated gravity mission ever built, the European Space Agency (ESA) GOCE satellite is in ‘measurement mode’, providing continuous time series of satellite gravity gradient (SGG) observations and GPS satellite-to-satellite tracking (SST) observations. The availability of GPS SST observations allows the precise reconstruction of the GOCE position and thus the precise geolocation of the SGG observations. The SGG observations are based on the differences between observations taken by pairs of accelerometers, which need to be corrected first by applying a so-called calibration matrix and second by subtracting rotational terms (centrifugal and angular accelerations).     

一种推广的靶效应模型及其对剂量-存活率的拟合探讨

辐射生物物理模型对于准确、有效地评估空间辐射引起的生物损伤及风险具有重要意义。目前较为流行的基于地基模拟的“靶效应模型”和“非靶效应模型”，是进一步探索空间辐射生物物理模型的基础。在考虑了辐射的非靶效应和机体复杂的修复过程的基础上，将传统理论中“击中”即“失活”的线性关系进行了推广，提出了基于否定算子的靶效应模型。通过对辐射钝感和敏感的两类细胞辐射实验中剂量与细胞存活率数据进行拟合发现，对于正常皮肤成纤维细胞的存活率数据，经典的靶学说与基于否定算子的改进靶效应模型都有较好的拟合效果；而对于人类胚胎肝细胞的存活率数据，基于否定算子的改进靶效应模型的拟合结果明显优于传统的靶学说模型。拟合结果中的模型参数值在人成纤维细胞和胚胎肝细胞中明显不同，说明了本模型的参数与传能线密度，细胞的种类、以及修复能力等物理和生物因素有关。     

On the mid-latitude ionospheric storm association with intense geomagnetic storms

The bulk association between ionospheric storms and geomagnetic storms has been studied. Hemispheric features of seasonal variation of ionospheric storms in the mid-latitude were also investigated. 188 intense geomagnetic storms (Dst ≤ 100 nT) that occurred during solar cycles 22 and 23 were considered, of which 143 were observed to be identified with an ionospheric storm. Individual ionospheric storms were identified as maximum deviations of the F2 layer peak electron density from quiet time values. Only ionospheric storms that could clearly be associated with the peak of a geomagnetic storm were considered. Data from two mid-latitude ionosonde stations; one in the northern hemisphere (i.e. Moscow) and the other in the southern hemisphere (Grahamstown) were used to study ionospheric conditions at the time of the individual geomagnetic storms. Results show hemispheric and latitudinal differences in the intensity and nature of ionospheric storms association with different types of geomagnetic storms. These results are significant for our present understanding of the mechanisms which drive the changes in electron density during different types of ionospheric storms.     

Latitudinal features of Total Electron Content over the African and European longitude sector following the St. Patrick’s day storm of 2015

GNSS TEC values have been obtained from 18 stations distributed from the magnetic equator to nearly 80°N magnetic dip in the African and west-European longitude sector corresponding to the March 17–18, 2015 geomagnetic storm. Significantly depleted ionosphere have been observed at stations north of 50°N geographic on March 18, 2015 following the above storm over a longitude swath 11.9°–21°E covering the Eastern Africa and Western European longitude sector. High ROTI values were noted on March 17^th at locations around 80°N magnetic dip. Two prominent peaks in PCN were noted around 09:00 UT and 14:00 UT on March 17, 2015 and around 15:00 UT on March 18, 2015. Daytime thermospheric (O/N₂) ratio was markedly less on March 18th at latitudes above 60°N geographic which is suggested to be the major driver behind depleted high latitude ionosphere during the recovery phase of the storm on March 18, 2015.     

Model based Computerized Ionospheric Tomography in space and time

Reconstruction of the ionospheric electron density distribution in space and time not only provide basis for better understanding the physical nature of the ionosphere, but also provide improvements in various applications including HF communication. Recently developed IONOLAB-CIT technique provides physically admissible 3D model of the ionosphere by using both Slant Total Electron Content (STEC) measurements obtained from a GPS satellite - receiver network and IRI-Plas model. IONOLAB-CIT technique optimizes IRI-Plas model parameters in the region of interest such that the synthetic STEC computations obtained from the IRI-Plas model are in accordance with the actual STEC measurements. In this work, the IONOLAB-CIT technique is extended to provide reconstructions both in space and time. This extension exploits the temporal continuity of the ionosphere to provide more reliable reconstructions with a reduced computational load. The proposed 4D-IONOLAB-CIT technique is validated on real measurement data obtained from TNPGN-Active GPS receiver network in Turkey.     

Modeling spatial density in low earth orbits using wavelets and random search

The events that occurred after 2007 such as Chinese anti-satellite test, explosion of Briz-M upper stage, break up of cosmos-2421 and collision of cosmos-2251 with Iridium-33 satellites have completely changed the spatial density patterns in low earth orbits. This has increased the risk of collision between active satellites and debris created by them. Aftermath, the risk assessment of possible collisions called as conjunction analysis of working satellites from day to day has become more crucial. Spatial density models are useful in understanding the long-term likelihood of a collision in a particular region of space and helpful in pre-launch orbit planning. In this paper we present an algorithmic procedure for automatically estimating exact model parameters corresponding to the peak location and number of peaks using wavelets that will speed up the parameter estimation process for the models with peaks.     

Influence of nuclear de-excitation on observables relevant for space exploration

The composition of the space radiation environment inside spacecrafts is modified by the interaction with shielding material, with equipment and even with the astronauts’ bodies. Accurate quantitative estimates of the effects of nuclear reactions are necessary, for example, for dose estimation and prediction of single-event-upset rates. To this end, it is necessary to construct predictive models for nuclear reactions, which usually consist of an intranuclear-cascade or quantum-molecular-dynamics stage, followed by a nuclear-de-excitation stage.     

Ionospheric disturbance associated with radiation accidents of Fukushima I nuclear power plant damaged by the M9.0 2011 Tohoku Earthquake

Transient ionospheric disturbances in the total electron content (TEC) are examined before and after the M9.0 2011 off the Pacific coast of Tohoku Earthquake to find ionospheric responses to the radiation caused by Fukushima I nuclear power plant accident, which was damaged by the earthquake and tsunamis. The TEC is derived from records of a ground-based receiving network of GPS Earth Observation Network (GEONET) in Japan. Both small enhancement and disturbance of TEC were detected over the nuclear power plant after the radiation was suddenly enhanced on March 14 of 2011, while similar signatures were not detected in the other sudden radiation enhancements. Further, no continuous enhancement and disturbance lasting for more than an hour were observed over the nuclear power plant. Therefore, the results indicate that radioactive materials may not cause the ionospheric disturbance or disturb the ionosphere in highly specific circumstance even if such effects exist.