No abstract

The EGM2008 model is nowadays one of the description of the global gravitational field at the highest resolution. It is delivered with two, not fully consistent, sources of information on its error: spherical harmonic coefficient variances and a geographical map of error variances, e.g. in terms of geoid undulation. In the present work, the gravity field information derived from a GOCE satellite-only global model is used to improve the accuracy of EGM2008 model in the low to medium frequencies, especially in areas where no data were available at the time of EGM2008 computation. The key issue is to set up the error covariance matrices of the two models for an optimal least-squares combination: the full error covariance matrix of GOCE spherical harmonic coefficients is approximated by an order-wise block-diagonal matrix, while for EGM2008, the pointwise error variances are taken from the provided geoid error map and the error spatial correlations from the coefficient variances. Due to computational reasons the combination is directly performed in terms of geoid values over a regular grid on local areas. Repeating the combination for overlapping areas all over the world and then performing a harmonic analysis, a new combined model is obtained. It is called GECO and extends up to the EGM2008 maximum degree. Comparisons with other recent combined models, such as EIGEN-6C4, and a local geoid based on new gravity datasets in Antarctica are performed to evaluate its quality. The main conclusion is that the proposed combination, weighting the different input contributions not only on a global basis but also according to some local error information, can perform even better than other more sophisticated combinations in areas where the input global error description is not reliable enough

The recent access to GNSS (Global Navigation Satellite System) phase observations on smart devices, enabled by Google through its Android operating system, opens the possibility to apply precise positioning techniques using off-the-shelf, mass-market devices. The target of this work is to evaluate whether this is feasible, and which positioning accuracy can be achieved by relative positioning of the smart device with respect to a base station. Positioning of a Google/HTC Nexus 9 tablet was performed by means of batch least-squares adjustment of L1 phase double-differenced observations, using the open source goGPS software, over baselines ranging from approximately 10 m to 8 km, with respect to both physical (geodetic or low-cost) and virtual base stations. The same positioning procedure was applied also to a co-located u-blox low-cost receiver, to compare the performance between the receiver and antenna embedded in the Nexus 9 and a standard low-cost single-frequency receiver with external patch antenna. The results demonstrate that with a smart device providing raw GNSS phase observations, like the Nexus 9, it is possible to reach decimeter-level accuracy through rapid-static surveys, without phase ambiguity resolution. It is expected that sub-centimeter accuracy could be achieved, as demonstrated for the u-blox case, if integer phase ambiguities were correctly resolved.

No abstract

Flight height is a fundamental parameter for correcting the gamma signal produced by terrestrial radionuclides measured during airborne surveys. The frontiers of radiometric measurements with UAV require light and accurate altimeters flying at some 10 m from the ground. We equipped an aircraft with seven altimetric sensors (three low-cost GNSS receivers, one inertial measurement unit, one radar altimeter and two barometers) and analyzed ~3 h of data collected over the sea in the (35–2194) m altitude range. At low altitudes (H < 70 m) radar and barometric altimeters provide the best performances, while GNSS data are used only for barometer calibration as they are affected by a large noise due to the multipath from the sea. The ~1 m median standard deviation at 50 m altitude affects the estimation of the ground radioisotope abundances with an uncertainty less than 1.3%. The GNSS double-difference post-processing enhanced significantly the data quality for H > 80 m in terms of both altitude median standard deviation and agreement between the reconstructed and measured GPS antennas distances. Flying at 100 m the estimated uncertainty on the ground total activity due to the uncertainty on the flight height is of the order of 2%.