Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 5
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

This work aims to study the vertical planning method for the terrain area as part of the process of construction geodetic support. Such planning will be carried out based on the aerial survey data from UAVs, which allow the creation of a high-quality digital elevation model (DEM) with sufficient node density for reliable surface terrain modelling. During the study, we test the hypothesis of the possibility of using archival aerial photographs from UAVs to model the terrain of the local area. Both the actual achievable accuracy of terrain modeling in the course of photogrammetric processing of archived aerial photographs, and methods for creating a polygonal terrain model using input spatial data in the form of clouds of 3D points of a given density require analysis. To do this, we will perform comparisons of the accuracy of calculating earth masses, carried out based on the digital triangulation elevation models (TIN). These models were based on different algorithms for creating Delaunay triangulation with different degrees of 3D point sparsity.We proposed to use sparsity of dense clouds of points representing the surface of the terrain and which were obtained by the photogrammetric method. Computer terrain modelling and calculation of vertical planning parameters were performed by us for the area with flat terrain at angles up to 3.5 degrees. We evaluated the potential of archived UAV aerial photographs and algorithms for creating Delaunay triangulation at different densities of its nodes for calculating the volumes of earth masses.
Go to article

Bibliography

Abris Design Group (2021). https://abris.aero/category/produkts-en/#FLIRT%20Arrow.
Aguilar, F.J., Rivas, J.R., Nemmaoui, A. et al. (2019). UAV-Based Digital Terrain Model Generation under Leaf-Off Conditions to Support Teak Plantations Inventories in Tropical Dry Forests. A Case of the Coastal Region of Ecuador. Sensors, 19(8), 1934. DOI: 10.3390/s19081934.
Akgul, M., Yurtseven, H., Gulci, S. et al. (2018). Evaluation of UAV- and GNSS-Based DEMs for Earthwork Volume. Arab. J. Sci. Eng., 43, 1893–1909. DOI: 10.1007/s13369-017-2811-9.
Al-Jabbar Hadi, A.A. and Alhaydary, M. (2018). Calculations of earthwork quantity by using civil 3d. J. Engineer. Sustain. Dev., 6, 13–20. DOI: 10.31272/jeasd.2018.6.2.
Baran, P.I. and Marushchak, M.P. (2011). Methods of vertical planning for construction sites. Geodesy Cartogr., 6, 9–15.
Burshtynska, Kh.V. and Zayats, O.S. (2002). Research of accuracy of construction of digital models of a relief on the basis of cartographic data. Geodesy Cartogr., 2, 26–31.
Christ, A., Europe, E., and Horlbeck, I. (2018). Simplify Your 3D Models – Collaborative Engineering Based on Lightweight CAD Data. Product Data Journal, 2, 28–31. http://prostep.epaper.pro/ journal-2018-02/en/#28.
Chudý, R., Iring, M., and Feciskanin, R. (2013). Evaluation of the data quality of digital elevation models in the context of INSPIRE. Geoscience Engineering, 2, 9–24. DOI: 10.2478/gse-2014-0053.
Dorozhinsky, O. and Tukay, R. (2008). Photogrammetry. Textbook. Lviv: Lviv Polytechnic National University Publishing House.
Garasymchuk, I.F. (2003). Operational method elaboration of the soil volume determination. PhD thesis (geodesy). National University “Lviv Polytechnic”. Lviv.
Haronian, E. and Sacks, R. (2020). Production process evaluation for earthworks. In Tommelein, I.D. and Daniel, E. (eds.), Proceedings of 28th Annual Conference of the International Group for Lean Construction (IGLC28), Berkeley, California, USA. DOI: 10.24928/2020/0020.
Hlotov, V., Hunina, R´ ., Kolesnichenko, V. et al. (2018). Development and investigation of UAV for aerial surveying. Geodesy Cartogr. Aerial Photogr., 87, 48–57. DOI: 10.23939/istcgcap2018.01.048.
Hamid I.H.A., Narendrannathan, N., Choy L.E. et al. (2019). Innovation in earthwork practices. In IOP Conference Series Materials Science and Engineering, 512:012054. DOI: 10.1088/1757- 899X/512/1/012054.
Kolb, I.Z. (2000). The analytical aerial triangulation when the coordinates of centers of projection are known. PhD thesis (geodesy). Lviv Polytechnic National University, Lviv.
Kong, N.T. (2011). Research and development of a high-performance algorithm for constructing digital elevation models. PhD thesis (geodesy). Moscow State University of Geodesy and Cartography, Moscow.
Kostov, G. (2016). Vertical planning based on 3d terrestrial laser scanning and GNSS technologies. In XXV International symposium on modern technologies, education and professional practice in geodesy and related fields. Sofia, November 3-4, 2016.
Liu, Q., Duan, Q., Zhao, P. et al. (2021). Summary of calculation methods of engineering earthwork. J. Phys. Conference Series, 1802, 032002. DOI: 10.1088/1742-6596/1802/3/032002.
Ministry of Justice of Ukraine. (1998). Instruction on topographic survey in scales 1:5000, 1:2000, 1:1000 and 1:500 (GKNTA-2.04-02-98), approved by the order of Ukrgeodeskartografiya dated 09.04.98, No. 56, registered in the Ministry of Justice of Ukraine on 23.06.98, No. 393/2833.
Novakovsky, B.A. and Permyakov, R.V. (2019). Complex geoinformation-photogrammetric modeling of relief: a tutorial. Moscow: Publishing house MIIGAiK.
Ostrovsky, A. (2015a). Criteria of quality, accuracy and completeness digital elevation models. Engineer. Geodesy, 62, 23–31.
Ostrovsky, A.V. (2015b). Review of some methods of relief approximation. Mìstobuduvannâ ta teritorìal’ne planuvannâ, 58, 380–391.
Ostrovsky, A.V. (2016). Features of using kriging method for approximating relief. Journal of Lviv National Agrarian University. Architecture and Farm Building, 17, 33–41. Photomod. (2019). Digital photogrammetric system Photomod. Version 6.0.1 User Guide. Creation of a digital elevation model. Moscow: Rakurs.
Qiu, L. (2017). Vertical urban planning and flood control and drainage using GIS technology. Open House International, 42(3), 10–14. DOI: 10.1108/OHI-03-2017-B0003.
Ravibabu, M.V. and Jain, K. (2008). Digital elevation model accuracy aspects. J. Appl. Sci., 8(1), 134–139. DOI: 10.3923/jas.2008.134.139.
Rudyj, R.M. (2016). Application of artificial neural networks for classifying surface areas with a certain relief. Geodesy Cartogr. Aerial Photogr., 83, 124–132. DOI: 10.23939/istcgcap2016.01.124.
Schultz, R.V., Belous, M.V., Annenkov, A.O. et al. (2013). Features of engineering and geodetic support for the construction of Arena Lviv stadium. Mìstobuduvannâ ta teritorìal’ne planuvannâ, 50, 759– 766.
Schultz, R.V. and Ostrovsky, A.V. (2016). Investigation of the statistical distribution of residual deviations for various approaches to digital elevation modeling. Scientific Journal, 1/2(18), 44–52.
Toth, C., Jozkow, G., and Grejner-Brzezinska, D. (2015). Mapping with small UAS: A point cloud accuracy assessment. J. Appl. Geod., 9(4), 213–226. DOI: 10.1515/jag-2015-0017.
Zhilin, L., Qing, Z., and Chris, G. (2005). Digital terrain modeling: principles and methodology. CRC Press.
Go to article

Authors and Affiliations

Ihor Trevoho
1
ORCID: ORCID
Apollinariy Ostrovskiy
1
Ihor Kolb
2
Olena Ostrovska
3
Viacheslav Zhyvchuk
4

  1. Lviv Polytechnic National University, Lviv, Ukraine
  2. Hetman Petro Sahaidachnyi National Army Academy, Lviv, Ukraine
  3. Lviv Technical and Economic College of Lviv Polytechnic National University, Lviv, Ukraine
  4. 2Hetman Petro Sahaidachnyi National Army Academy, Lviv, Ukraine
Download PDF Download RIS Download Bibtex

Abstract

Estimating the pathloss and signal strength of the transmitted signal at specific distances is one of the main objectives of network designers. This paper aims to provide generalized pathloss models appropriate for urban areas in Muscat the capital city of the Sultanate of Oman environment. The research includes studying different models of pathloss for the 4G cellular network at Muttrah Business District (MBD) at Muscat. Different models (Free Space model, Okumura Hata, Extended Sakagami, Cost231 Hata, ECC-33 Hata – Okumura extended, Ericsson, Egli, and SUI) are used with 800MHz. The results of the prediction models are compared with real measured data by calculating RMSE. The generalized models are created by modified original models to get accepted RMSE values. Different cells at MBD are tested by modified models. The RMSE values are then calculated for verification purposes. To validate the modified pathloss models of 4G, they are also applied at different cells in a different city in the capital. It has approximately the same environment as MBD. The modified pathloss models provided accepted predictions in new locations.
Go to article

Authors and Affiliations

Nawal Al-Aamri
1
Zia Nadir
1
Hassan Al-Lawati
1
Mohammed Bait Suwailam
1

  1. ECE Dept. at College of Engineering at SQU, Muscat, Sultanate of Oman
Download PDF Download RIS Download Bibtex

Abstract

This paper presents a simple DFT-based golden section searching algorithm (DGSSA) for the single tone frequency estimation. Because of truncation and discreteness in signal samples, Fast Fourier Transform (FFT) and Discrete Fourier Transform (DFT) are inevitable to cause the spectrum leakage and fence effect which lead to a low estimation accuracy. This method can improve the estimation accuracy under conditions of a low signal-to-noise ratio (SNR) and a low resolution. This method firstly uses three FFT samples to determine the frequency searching scope, then – besides the frequency – the estimated values of amplitude, phase and dc component are obtained by minimizing the least square (LS) fitting error of three-parameter sine fitting. By setting reasonable stop conditions or the number of iterations, the accurate frequency estimation can be realized. The accuracy of this method, when applied to observed single-tone sinusoid samples corrupted by white Gaussian noise, is investigated by different methods with respect to the unbiased Cramer-Rao Low Bound (CRLB). The simulation results show that the root mean square error (RMSE) of the frequency estimation curve is consistent with the tendency of CRLB as SNR increases, even in the case of a small number of samples. The average RMSE of the frequency estimation is less than 1.5 times the CRLB with SNR = 20 dB and N = 512.
Go to article

Authors and Affiliations

Xin Liu
Yongfeng Ren
Chengqun Chu
Wei Fang
Download PDF Download RIS Download Bibtex

Abstract

Nowadays, the world is turning into technology, fast internet and high signal quality. To ensure high signal quality, the network planners have to predict the pathloss and signal strength of the transmitted signal at specific distances in the design stage. The aim of this research is to provide a generalized pathloss model to suit the urban area in Muscat Governorate in the Sultanate of Oman. The research covers 5G network pathloss in the Muttrah Business District (MBD) area. It includes Close In (CI) model and Alpha Beta Gamma (ABG) model with 3.45GHz. The results of 5G models were compared with real experimental data in MBD by calculating Root Mean Square Error RMSE. Other cells at MBD area were used for reverification. To validate the modified pathloss models of 5G, they were applied at different cells in Alkhoud area. Furthermore, this paper also deals the effect of Specific Absorption Rate (SAR) on the human brain for ensuring safety due to close proximity to cell towers. The SAR values were calculated indirectly from the electric field strength of different antennas. Calculated results were compared with the international standards defined limits on the human brain.
Go to article

Authors and Affiliations

Nawal Al-Aamri
1
Zia Nadir
1
Mohammed Bait-Suwailam
1
Hassan Al-Lawati
1

  1. ECE Dept. at College of Engineering at SQU, Muscat, Sultanate of Oman
Download PDF Download RIS Download Bibtex

Abstract

Localization is one of the oldest mathematical and technical problems that have been at the forefront of research and development for decades. In a wireless sensor network (WSN), nodes are not able to recognize their position. To solve this problem, studies have been done on algorithms to achieve accurate estimation of nodes in WSNs. In this paper, we present an improvement of a localization algorithm namely Gaussian mixture semi-definite programming (GM-SDP-2). GMSDP is based on the received signal strength (RSS) to achieve a maximum likelihood location estimator. The improvement lies in the placement of anchors through the Fuzzy C-Means clustering method where the cluster centers represent the anchors’ positions. The simulation of the algorithm is done in Matlab and is based on two evaluation metrics, namely normalized root-mean-squared error (RMSE) and cumulative distribution function (CDF). Simulation results show that our improved algorithm achieves better performance compared to those using a predetermined placement of anchors.
Go to article

Authors and Affiliations

Sidi Mohammed Hadj Irid
1
Mourad Hadjila
1
Mohammed Hicham Hachemi
2
Sihem Souiki
3
Reda Mosteghanemi
1
Chaima Mostefai
1

  1. Dept. of Telecommunications, Faculty of Technology, University of Abou Bekr Belkaid, Tlemcen, Algeria
  2. Dept. of Electronics, Faculty of Electrical Engineering, University of Science and Technology of Oran - Mohamed Boudiaf (USTO-MB), Oran, Algeria
  3. Dept. of Telecom, Faculty of Technology, University of Belhadj Bouchaib, Ain Temouchent, Algeria

This page uses 'cookies'. Learn more