On the reliability of the VCV Matrix: A case study based on GAMIT and Bernese GPS Software

Commonly, the variance-covariance (VCV) matrix derived from GPS processing software underestimates the magnitude of the error, mainly due to the fact that physical correlations are normally neglected. The GAMIT and Bernese software packages serve the scientific community as important tools for GPS measurement processing and analyzing, especially in precise applications. Therefore, the reliability of the VCV matrices derived by the GAMIT and Bernese packages is of great importance. Formal accuracies derived from both software need to be scaled by applying a scaling factor (SF) that multiplies the software-derived formal errors. However, to the best of our knowledge, no standard approach approved by the GPS community exists. In this report, an analysis is carried out in order to test the reliability and the validity of the VCV matrices in both software, and to provide SFs needed to calculate the realistic accuracies reflecting the actual error levels. The method applied in this study allows deriving SFs for formal accuracies obtained from GAMIT and Bernese. The results attained from the time series of eight days for eight baselines (lengths of 20–415 km) indicate that the overall SF for GAMIT is more than 10 times smaller than for Bernese (1.9 and 23.0, respectively). Although no distance-dependent SF was detected in either case, the session-duration dependence was detected for the Bernese software, while no clear session-duration dependence was observed for the GAMIT. Furthermore, no receiver/antenna dependence could be deduced from the results of this analysis.     

Wet tropospheric effects on precise relative GPS height determination

Summary Considerable interest has been generated recently in the use of the Global Positioning System (GPS) for precise height determination. A major error source in these measurements is the propagation delay due to atmospheric water vapour. In order to achieve the high precisions required for such applications as absolute sea-level monitoring improvement of wet delay modelling is necessary. Results from a GPS campaign show a significant correlation (0.91) between the variability of the wet delay measured using a water vapour radiometer (WVR) at the Onsala site and the absolute value of the residual error in the height determination of a 134 km baseline from Onsala to Jönköping. This correlation indicates that the atmosphericvariability as inferred from the WVR data includes information on the quality of the GPS height estimate. During periods of high atmospheric activity, e.g., during the passage of a weather front, the use of a six-parameter gradient model reduces the spread for the vertical coordinate from 40 mm to 20 mm (with standard deviations of 17 mm and 9 mm respectively) over the 134 km baseline (less than 1 × 10^–7) using 8 hour data spans on 11 different days over a six month period.     

Precise aircraft single-point positioning using GPS post-mission orbits and satellite clock corrections

Summary Aircraft single point position accuracy is assessed through a comparison of the single point coordinates with corresponding DGPS-derived coordinates. The platform utilized for this evaluation is a Naval Air Warfare Center P-3 Orion aircraft. Data was collected over a period of about 40 hours, spread over six days, off Florida's East Coast in July 94, using DGPS reference stations in Jacksonville, FL, and Warminster, PA. The analysis of results shows that the consistency between aircraft single point and DGPS coordinates obtained in single point positioning mode and DGPS mode is about 1 m (rms) in latitude and longitude, and 2 m (rms) in height, with instantaneous errors of up to a few metres due to the effect of the ionosphere on the single point L1 solutions.     

Spectrum estimation using maximum entropy and multiresolution considerations

Summary Given a sample autocovariance sequence of finite length for some observed random process, the spectrum estimation problem involves the extension of this sequence for the required Fourier transformation. The maximum entropy approach which is based on the optimal use of information contents, leads to a dual sequence of reflection coefficients with reciprocal spectrum of the process. The estimation of the maximum entropy spectrum implies results identical to those using autoregressive modeling in one dimension under appropriate white noise assumptions. In cases of a non-white noise component, the approach is generalized to an autoregressive-moving-average model. Recent developments in multiresolution analysis with spectral domain decompositions also offer possibilities of subband spectrum estimation for specific applications. Using a simulated data sequence with two close frequencies, the estimated spectrum from a two-level decomposition with autoregressive modeling shows better resolution than with conventional processing. Geodetic and geophysical applications are briefly indicated.     

Assessing the Resolving Power of Photographic Systems Used forTerrestrial Remote Sensing

It is often necessary to measure the resolving power of an imaging system comprising "off the shelf" components by a method that can also describe resolution in the object space. Furthermore, the results should allow useful comparisons to be made with alternative systems, where these have undergone a similar evaluation procedure. An example is given of measuring the resolving power of two imaging systems employing catadioptric objectives by a method that does not necessitate extensive laboratory tests, but utilizes the photographic product provided through field trials, or in the course of operational use. While the method reported does not claim to be a rigorous evaluation of the resolving power, it has been found to provide a convenient and practical guide to the image quality associated with a complete camera system, and its relation to the object space.     

Position and velocity reliability testing in degraded GPS signal environments

Reliability testing, namely receiver autonomous integrity monitoring (RAIM), consists of statistical testing of least-squares residuals of observations, e.g., on an epoch-by-epoch basis aiming towards reliable navigation fault detection and exclusion (FDE). In this paper, classic RAIM and FDE methods are extended with testing of range-rate residuals to find inconsistent velocity solutions in order to contribute to the reliability of the system with special focus on degraded signal environments. Reliability enhancement efforts discussed include a Backward-FDE scheme based on statistical outlier detection and an iteratively reweighted robust estimation technique, a modified Danish method. In addition, measurement weighting assigned to code and Doppler observations is assessed in the paper in order to allow fitting a priori variance models to the estimation processes. The schemes discussed are also suitable in terms of computational convenience for a combined GPS/Galileo system. The objective of this paper is to assess position and velocity reliability testing and enhancement in urban and indoor conditions and to analyze the navigation accuracy conditions with high sensitivity GPS (HSGPS) tests. The results show the necessity of weighted estimation and FDE for reliability enhancement in degraded signal-environment navigation.     

Response of GPS occultation signals to atmospheric gravity waves and retrieval of gravity wave parameters

We show that the amplitude of the Global Positioning System (GPS) signals in the radio occultation (RO) experiments is an indicator of the activity of the gravity waves (GW) in the atmosphere. The amplitude of the GPS RO signals is more sensitive to the atmospheric wave structures than is the phase. Early investigations used only the phase of the GPS occultation signals for statistical investigation of the GW activity in the height interval 10–40 km on a global scale. In this study, we use the polarization equations and Hilbert transform to find the 1-D GW radio image in the atmosphere by analyzing the amplitude of the RO signal. The radio image, also called the GW portrait, consists of the phase and amplitude of the GW as functions of height. We demonstrate the potential of this method using the amplitude data from GPS/Meteorology (GPS/MET) and satellite mission Challenge Mini-satellite Payload (CHAMP) RO events. The GW activity is nonuniformly distributed with the main contribution associated with the tropopause and the secondary maximums related to the GW breaking regions. Using our method we find the vertical profiles of the horizontal wind perturbations and its vertical gradient associated with the GW influence. The estimated values of the horizontal wind perturbations are in fairly good agreement with radiosonde data. The horizontal wind perturbations v(h) are ±1 to ±5 m s with vertical gradients dv/dh ±0.5 to ±15 m s km at height 10–40 km. The height dependence of the GW vertical wavelength was inferred through the differentiation of the GW phase. Analysis of this dependence using the dispersion relationship for the GW gives the estimation of the projection of the horizontal background wind velocity on the direction of the GW propagation. For the event considered, the magnitude of this projection changes between 1.5 and 10 m s at heights of 10–40 km. We conclude that the amplitude of the GPS occultation signals contain important information about the wave processes in the atmosphere on a global scale.     

Uniting space, ground, and underwater measurements for improved estimates of rain rate

Global precipitation is monitored from a variety of platforms including spaceborne, ground-, and ocean-based platforms. Intercomparisons of these observations are crucial to validating the measurements and providing confidence for each measurement technique. Probability distribution functions of rain rates are used to compare satellite and ground-based radar observations. A preferred adjustment technique for improving rain rate distribution estimates is identified using measurements from ground-based radar and rain gauges within the coverage area of the radar. The underwater measurement of rainfall shows similarities to radar measurements, but with intermediate spatial resolution and high temporal resolution. Reconciling these different measurement techniques provides understanding and confidence for all of the methods.     

An update on the IEM surface backscattering model

The integral equation approach to modeling scattering from rough surfaces was introduced in 1992. At that time, it was noted that there was a need to find a transition reflection coefficient that could change its argument from the incident angle to the specular angle as frequency or roughness scale got large. One such reflection coefficient was published in 2001. In this letter, we would like to include this reflection coefficient in the integral equation model to interpret several multifrequency backscattering measurements from surfaces with surface parameters defined by the investigators who acquired the data.