With the rapid development of the satellite navigation industry, low-cost and high-precision Global Navigation Satellite System (GNSS) positioning has recently become a research hotspot. The traditional application of GNSS may be further extended thanks to the low cost of measuring instruments, but effective methods are also desperately needed due to the low quality of the data obtained using these instruments. Thus, in this paper, we propose the analysis and evaluation of the ambiguity fixed-rate and positioning accuracy of single-frequency Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) data, collected from a low-cost u-blox receiver, based on the Constrained LAMBDA (CLAMBDA) method with a baseline length constraint, instead of the classical LAMBDA method. Three sets of experiments in different observation environments, including two sets of static short-baseline experiments and a set of dynamic vehicle experiments, are adopted in this paper. The experiment results show that, compared to classical LAMBDA method, the CLAMBDA method can significantly improve the success rate of the GNSS ambiguity resolution. When the ambiguity is fixed correctly, the baseline solution accuracy reaches 0.5 and 1 cm in a static scenario, and 1 and 2 cm on a dynamic platform.

This article describes GIS-based models successfully developed for predicting the coverage of Cityphone cellular network, visualizing the predicted signal strength, and analyzing the field strength coverage. In order to predict the signal coverage strength of communication network more accurately, the spatial and nonspatial databases of a mobile cellular network are combined by GIS and produce the necessary parameters. A GIS model named COST-231-Walfisch–Ikegami model (WIM) is developed for signal coverage prediction in Ho Chi Minh City. Radio-line-of-sight and nonradio-line-of-sight conditions can be determined by this model. In addition, in case of nonradio-line-of-sight conditions, average building height, building separation, building width, incident radio path, and road orientation with respect to the direct radio path were obtained using GIS. Road orientation loss, multiscreen diffraction loss, and shadowing gain were predicted more accurate by this model. The scale of maps in the experiment was 1:2000 and the average of floor height was 3 m because there were no exact building height measurements. Statistical results show that the path loss predicted by the COST 231 WIM overcame the real path loss of each cell station. And this method can be used for signal coverage prediction of mobile cellular network in urban areas. Compared to the current situation with the Ho Chi Minh City Posts and Telecommunications system, this model can be effectively applied to improve the Cityphone mobile network quality as well as capability. Developed GIS models can help designers in predicting cell station coverage using real spatial maps that make the results more reliable. This research can help network operators improve the network quality and capability with the best investment efficiently.

The degree of automation and efficiency are among the most important factors that influence the availability of Terrestrial light detection and ranging (LiDAR) Scanning (TLS) registration algorithms. This paper proposes an Ortho Projected Feature Images (OPFI) based 4 Degrees of Freedom (DOF) coarse registration method, which is fully automated and with high efficiency, for TLS point clouds acquired using leveled or inclination compensated LiDAR scanners. The proposed 4DOF registration algorithm decomposes the parameter estimation into two parts: (1) the parameter estimation of horizontal translation vector and azimuth angle; and (2) the parameter estimation of the vertical translation vector. The parameter estimation of the horizontal translation vector and the azimuth angle is achieved by ortho projecting the TLS point clouds into feature images and registering the ortho projected feature images by Scale Invariant Feature Transform (SIFT) key points and descriptors. The vertical translation vector is estimated using the height difference of source points and target points in the overlapping regions after horizontally aligned. Three real TLS datasets captured by the Riegl VZ-400 and the Trimble SX10 and one simulated dataset were used to validate the proposed method. The proposed method was compared with four state-of-the-art 4DOF registration methods. The experimental results showed that: (1) the accuracy of the proposed coarse registration method ranges from 0.02 m to 0.07 m in horizontal and 0.01 m to 0.02 m in elevation, which is at centimeter-level and sufficient for fine registration; and (2) as many as 120 million points can be registered in less than 50 s, which is much faster than the compared methods.