Volume 5, Issue 2

One of the dominant error sources for single frequency GPS users is the ionosphere. The magnitude of this error can vary from a few meters to hundreds of meters, especially during severe ionospheric disturbance periods. For undifferenced processing using a single frequency single receiver unit, the ionospheric error cannot be cancelled out using a differential process. Therefore, one needs to rely on using appropriate models or algorithms to correct this delay to achieve high accuracy point positioning. This paper reports on a study undertaken to evaluate two different ionospheric error mitigation methods for single frequency Precise Point Positioning (PPP) processing. The two methods studied were ionospheric modeling and ionosphere-free combination. The feasibility of using either of these methods was assessed using four processing options: code-only processing; code and carrier phase combination; single frequency ionosphere-free linear combination employing an additive combination of code and carrier phase measurements, which was abbreviated as the quasi-phase measurements; and the code and quasi-phase combination For this study, GPS static data were collected from different latitudinal regions and during both ionospheric disturbance and benign periods. The results from this investigation have revealed that the ionosphere-free combination, in particular the code and quasi-phase combination, provided the best point positioning results and could provide decimeter-level point positioning accuracy and precision. In addition, the solutions from the ionosphere-free linear combination were more stable when compared to the code and carrier phase ionospheric modeling method. This makes the linear combination the preferred method for single frequency PPP processing.

Accurate a priori Zenith Hydrostatic Delays (ZHDs) are required during the processing of space geodetic observations. The data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) are routinely processed and translated in terms of ZHDs by the Vienna University of Technology. The usual way to compute gridded ZHDs at a particular location is to correct the four nearest nodes of the grid for their difference in height with respect to the site height and to then interpolate these reduced values. This paper compares and discusses the performance achieved by five methods of reduction that have been proposed in the literature. The interpolated ZHD values are compared with the site-specific ones for a global network of 363 sites over a three-year period. The methods that only use vertical profiles of atmospheric pressure lead to annual signals that are correlated with ground temperature, while the methods that take temperature into account do not contain such annual signals. The reduction methods that use a constant temperature lead to errors of ~2 mm in terms of equivalent height. We also find that the a posteriori errors of the reduced gridded ZHDs are strongly correlated with the pressure over temperature ratio. We recommend that gridded ZHDs be reduced with the combination of both pressure and temperature when processing space geodetic observations.

It has been reported by various researchers that the tilt, or ‘off-leveling’, correction in the LaCoste and Romberg (LCR) airborne gravity measuring system is one of the most important steps to take into account during data processing. Because it directly affects the accuracies of the final gravity estimates, improper handling of this correction will induce systematic errors such as bias and drift. Although the final cross-over adjustments can partly remedy this situation, it is considered that short wavelength, random errors will definitely leak into the final results, especially when only a few sparse cross-over points are available. An exact formula for the tilt correction of the gravimeter's platform has been rigorously derived in this paper, which avoids the problems and assumptions present in classical methods.

A popular INS/GPS integration strategy is the loosely coupled approach, however its main disadvantage lies in its inability to provide measurement updates during periods of partial GPS availability. In such cases the INS navigation solution drifts over time. This paper proposes the construction of fictitious GPS satellites in order to facilitate GPS receiver position and velocity solutions in cases of partial GPS availability. The paper demonstrates the contribution of the proposed approach via several field experiments, in which the introduction of synthetic GPS measurements reduced the navigation errors obtained by the standalone INS and facilitated the classical implementation of loosely coupled integration.

To achieve the required navigation accuracy in some navigation applications, it is necessary to use a number of inertial sensors to obtain higher-quality acceleration/rotation rate measurements. For such redundant units, an inertial sensor fusion algorithm is required. This algorithm optimally combines all sensor outputs and generates a single inertial measurement that may be processed by any existing navigation software. In this study, a comprehensive framework for the inertial sensor fusion problem is presented for the skew-redundant inertial measurement units. An optimal sensor fusion algorithm is then developed for the skew-redundant units, where all of the inertial sensors are arbitrarily oriented in space without any lever-arm effect. An error model for the algorithm output is also derived, and it is shown that under certain conditions, the number of states for these error models can be greatly reduced. Simulation test results show that when inertial sensors with complimentary characteristics are used, the proposed fusion algorithm can be used to form high-accuracy inertial measurements, which inherit all the best characteristics of the constituent sensors in the skew-redundant units.