Volume 1, Issue 4

The kinematic survey of roads and railways is becoming a much more common data acquisition method. The development of the Mobile Road Mapping System (MoSES) has reached a level that allows the use of kinematic survey technology for high precision applications. The system is equipped with cameras and laser scanners. For high accuracy requirements, the scanners become the main sensor group because of their geometric precision and reliability. To guarantee reliable survey results, specific calibration procedures have to be applied, which can be divided into the scanner sensor calibration as step 1, and the geometric transformation parameter estimation with respect to the vehicle coordinate system as step 2. Both calibration steps include new methods for sensor behavior modeling and multisensor system integration. To verify laser scanner quality of the MoSES system, the results are regularly checked along different test routes. It can be proved that a standard deviation of 0.004 m for height of the scanner points will be obtained, if the specific calibrations and data processing methods are applied. This level of accuracy opens new possibilities to serve engineering survey applications using kinematic measurement techniques. The key feature of scanner technology is the full digital coverage of the road area. Three application examples illustrate the capabilities. Digital road surface models generated from MoSES data are used, especially for road surface reconstruction tasks along highways. Compared to static surveys, the method offers comparable accuracy at higher speed, lower costs, much higher grid resolution and with greater safety. The system's capability of gaining 360 profiles leads to other complex applications like kinematic tunnel surveys or the precise analysis of bridge clearances.

The integration of Global Positioning System (GPS) with Inertial Navigation System (INS) has been widely used in many applications for positioning and orientation purposes. Traditionally, random walk (RW), Gauss-Markov (GM), and autoregressive (AR) processes have been used to develop the stochastic model in classical Kalman filters. The main disadvantage of classical Kalman filter is the potentially unstable linearization of the nonlinear dynamic system. Consequently, a nonlinear stochastic model is not optimal in derivative-based filters due to the expected linearization error. With a derivativeless-based filter such as the unscented Kalman filter or the divided difference filter, the filtering process of a complicated highly nonlinear dynamic system is possible without linearization error. This paper develops a novel nonlinear stochastic model for inertial sensor error using a wavelet network (WN). A wavelet network is a highly nonlinear model, which has recently been introduced as a powerful tool for modelling and prediction. Static and kinematic data sets are collected using a MEMS-based IMU (DQI-100) to develop the stochastic model in the static mode and then implement it in the kinematic mode. The derivativeless-based filtering method using GM, AR, and the proposed WN-based processes are used to validate the new model. It is shown that the first-order WN-based nonlinear stochastic model gives superior positioning results to the first-order GM and AR models with an overall improvement of 30% when 30 and 60 seconds GPS outages are introduced.

The Sichuan-Yunnan region is located in the southeast of the Tibetan Plateau. The pattern of its crustal motion and deformation plays an important role in understanding the continental tectonic deformation. In this paper, 249 high precision GPS velocities are used to estimate the crustal motion and deformation in the region by employing the rigid block motion model and the strain rate model, respectively. On the basis of the inversion results, we form statistic tests to identify the two crustal movement models. As a result, the strain-rate model is more suitable for describing the crustal movement model in the region. The Qiangtang block, the north-western Sichuan sub-block, the middle Yunnan sub-block, the Baoshan sub-block and the Jinggu sub-block show a clockwise rotation, and their velocities are from high to low. With respect to the Eurasia plate, the Qiantang block moves N114.6 ± 1.3 °E at a rate of 17.0 ± 0.6 mm/yr; the north-western Sichuan sub-block moves N134.2 ± 1.8 °E at a rate of 15.9 ± 0.7 mm/yr; the middle Yunnan sub-block moves N157.1 ± 1.7 °E at a rate of 13.1 ± 0.6 mm/ yr, the Baoshan sub-block moves N193.4 ± 5.1 °E at a rate of 9.0 ± 1.1 mm/yr and the Jinggu sub-block moves to N182.2 ± 3.7 °E at a rate of 7.7 ± 0.7 mm/ yr. The Sichuan-Yunnan rhombic sub-block in the region is of high shearing strain rate and surface dilatation rate, which are up to 25.5 ± 7.6 10 -9 /yr and 7.5 ± 7.6 10 -9 /yr in the north-western Sichuan sub-block and 37.1 ± 4.8 10 -9 /yr and 12.8 ± 4.8 10 -9 /yr in the middle Yunnan subblock, respectively. The main fault velocities in the Sichuan-Yunnan region are about 10 mm/yr. The characteristics of the Sichuan-Yunnan crustal motion and deformation do not support the hypothesis of “the continental deformation as discontinuous deformation”.

The intensive brown coal mining activities occurring since the mid-fifties of the last century in the Lower Rhine Embayment have caused massive landscape changes. Less obvious but equally dramatic are the effects on the Earth's surface such as ground movements which are mainly due to groundwater withdrawal associated with the ongoing open pit mining activities. Larger discontinuities in the pattern of motion tend to appear at pre-existing fault lines and are causing sizable damage to buildings and roads. Precision levellings and traverses carried out in regular intervals by the State Survey of Nordrhein-Westfalen (Germany) and the mining company RWE Power have been supplemented by GPS observations in recent years, to measure the ground motions and monitor their behaviour with high accuracy. As a recent example, the measurements of the local deformation GPS network ‘Donatussprung’, a section of the Erft Fault system where the surface trace can be identified from topography and effects on buildings and roads, have revealed displacements of up to 6 mm/y in horizontal and 22 mm/y in vertical direction with high accuracy. Vertical and horizontal motions due to recent tectonics in this region are smaller by at least an order of magnitude. The observed pattern of vertical and horizontal velocity vectors shows a remarkable difference in the motion of point groups on either side of the fault. The scenario suggested by these measurements indicates that the sediment layers on the Erft Block are indeed sinking in proportion to the groundwater withdrawal, but that near the fault the pattern of motions is strongly influenced by the fault geometry. Modelling options include mining subsidence troughs as well as fault slip motion.

The purpose of this paper is to develop an improved local geoid model for Hungary combining GPS and leveling height data with a local gravimetric geoid model, via corrector surface, which accounts for datum inconsistencies, long-wavelength geoid errors and vertical network distortions. The improved model is the so-called GPS-gravimetric geoid, which can be constructed by adding the corrector surface to the original gravimetric geoid. The corrector surface can be represented by means of a Thin Plate Spline Interpolation (TPSI) and finite element solution. In this work 194 GPS/leveling points with a local gravimetric geoid were used to calculate the corrector surface and the combined geoid model. To estimate the realistic error of the solution 110 GPS/ leveling points were used as external control points. Attention is called to the importance of the homogeneous distribution of the GPS/leveling data. The mean accuracy of geoid heights of the used 110 control stations was 1–2 cm after the surface fitting.

In the geodesy science, the heights determined by Global Positioning System (GPS) measurements are related to the perpendicular distance above the reference ellipsoid, while heights above Mean Sea Level (MSL) are determined with respect to geoid. The datum that defines the MSL (also called the geoid) is a complex surface that requires dense and accurate gravity data to define its shape. Determining the geoid in Iraq is not an easy matter, mainly because of the lack of necessary data at the present time. In the present study, ellipsoidal heights were derived from GPS measurements (with respect to the WGS84 reference ellipsoid) at specific locations inside the campus of Mosul University. Orthometric heights (MSL) data of the test locations were then obtained by subtracting geoid undulations (geoid height) derived from the global field model EGM96 (The Earth Gravitational Model 1996). From the result of the measurements, a geoid map was produced for the study area. This study is considered as primary attempt. It is anticipated to determine the geoid separation for the whole territory of Iraq in future.