Volume 5, Issue 1

Starting with a one-dimensional B-spline curve, the multi-scale representation of signals is presented using spline wavelets on unit intervals. The results are generalized to an n -dimensional B-spline surface; the decomposition equations for the signals are derived; and the multi-scale representation of signals by the n -dimensional surface is given. The signals are arranged in grids with a density higher than that of the measurements. As an example, the multi-scale representation of signals by a three-dimensional surface is computed using a surface that changes with time. Coordinates of points on the surface are measured by a laser scanner yielding a high point density that accounts for the edges of the surface. It is shown that the number of coefficients which define the three-dimensional surface can be considerably reduced through data compression.

Automation of processes, in combination with quality assurance, is an important development in civil engineering. One of the critical components of quality assurance relates to geometry. In order to determine and control geometric elements, measurement and evaluation processes of engineering geodesy must be integrated with construction processes. The quality of products and processes is a complex, multi-faceted field and this complexity is considered here by a new model that describes quality on the basis of characteristics and parameters. The model that has been developed for engineering geodesy processes in civil engineering has been applied to describe the quality of the geometry of a building.

For many countries, regional networks of Continuously Operating Reference Station (CORS) are the basic infrastructure to support the needs of users requiring positioning with centimeter-scale accuracy. However, nationwide NRTK (RTK Network) coverage is often not economically viable for countries with large rural regions. In contrast, for administrative reasons and social proximity sometimes several networks may cover the same territory. Reference station placement affects the quality of the positioning services and the cost of the network. Spain has a high density of regional NRTK networks. Indeed, the Region of Murcia has two such networks: REGAM and MERISTEMUM. REGAM uses the MAC (Master Auxiliary Concept) and MERISTEMUM uses the VRS (Virtual Reference Station), which are currently the most commonly used approaches to generate network RTK corrections. Control tests based on simultaneous determination of position have been performed in the Region of Murcia to analyze the performance of the REGAM and MERISTEMUM networks. The results confirm that both the VRS and MAC network solutions provide centimeter-scale accuracy: the positioning error for the test points inside the NRTK cells is lesser than 1.5 cm in planimetry and around 3.5 cm in height. The ambiguity resolution, the coverage and the connection to the networks services were highly satisfactory.

Traditionally, in GPS precise point positioning (PPP), ionosphere-free linear combinations of dual-frequency carrier-phase and pseudorange measurements are used. Unfortunately, with these linear combinations only the first-order ionospheric delay term is removed and higher order ionospheric delay terms are usually not taken into account. Such residual error components may deteriorate the PPP solution and slow down the convergence time. In this paper the second-order ionospheric delay term is modeled and it is shown that its effect on GPS satellite orbit varies from 2.3 mm to 23.8 mm in the radial direction, 3.6 mm to 18.8 mm in the along-track direction and 2 mm to 16.3 mm in the cross-track direction. In addition, GPS satellite clock corrections showed a difference of up to 0.067 ns. To examine the effect of the second-order ionospheric delay on the PPP solution, new data sets from several IGS stations were processed using a modified version of GPSPace software, which was originally developed by Natural Resources Canada (NRCan). The modified GPSPace accepts the second-order ionospheric corrections as well as the newly developed US National Oceanic and Atmospheric Administration (NOAA) tropospheric signal delay model (NOAATrop). The estimated precise satellite orbit and clock corrections, with second-order ionospheric delay accounted for, were used in all PPP data processing. It is shown that accounting for the second-order ionospheric delay and applying the NOAATrop model improved the PPP solution convergence time by about 15% and improved the accuracy estimation by 3 mm.

Deformation monitoring has been carried out in two epochs on Turtle Mountain, Alberta, using a high-precision total station and a terrestrial laser scanner. From the total station observations, coordinates have been computed for seven signalized target points in a least-squares network adjustment. Then, a deformation analysis using a Multi-Parameter Transformation has been performed to derive movements between epochs. The two point clouds obtained with the laser scanner were registered using the iterative closest point algorithm. Differences in elevation between the two point clouds were then derived for the entire scene. Results indicate a downward movement of South Peak, and no significant horizontal deformations were found.