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Статті в журналах з теми "Ionospheric radio wave propagation Mathematical models"
1
Liao, Xiaoqian, and Sheng Xu. "Comparative study of the polar region ionospheric NmF2 and IRI-2016 models." Journal of Physics: Conference Series 2306, no. 1 (November 1, 2022): 012003. http://dx.doi.org/10.1088/1742-6596/2306/1/012003.
Повний текст джерелаАнотація:
Abstract The propagation of radio waves can be significantly affected by the ionosphere, which have a serious impact on broadcasting, communication, positioning and navigation. The International Reference Ionosphere (IRI) provides multiple ionospheric parameters for given location, time and date. In order to study the applicability of the IRI-2016 model in polar ionosphere, long-term observations from the dynasonde at Tromso (TRO), EISCAT Svalbard Radar (ESR) at Longyearbyen (LYB) and digisonde DPS-4 at Zhongshan (ZHS) were used to analyze the prediction accuracy of IRI model, with the help of mathematical statistics, correlation coefficients and time series. The data of F2 layer peak electron density (NmF2) are sorted as monthly medians of NmF2 for each hours, months, and solar activities. The results show that there is a good correlation between IRI prediction and observations during solar minimum years, with the correlation coefficients larger than 0.8 except winter at Longyearbyen, better than that during solar maximum years. The correlation decreases as latitude increases. It is the best at Tromso, and better at Zhongshan than at Longyearbyen. This suggests that the IRI-2016 model is mostly applicable at the auroral latitude station Tromso. But the IRI-2016 model has poor applicability at the cusp latitude station, both Zhongshan and Longyearbyen.
2
Anduaga, Aitor. "The formation of ionospheric physics – confluence of traditions and threads of continuity." History of Geo- and Space Sciences 12, no. 1 (April 7, 2021): 57–75. http://dx.doi.org/10.5194/hgss-12-57-2021.
Повний текст джерелаАнотація:
Abstract. This paper examines how ionospheric physics emerged as a research speciality in Britain, Germany, and the United States in the first four decades of the 20th century. It argues that the formation of this discipline can be viewed as the confluence of four deep-rooted traditions in which scientists and engineers transformed, from within, research areas connected to radio wave propagation and geomagnetism. These traditions include Cambridge school's mathematical physics, Göttingen's mathematical physics, laboratory-based experimental physics, and Humboldtian-style terrestrial physics. Although focused on ionospheric physics, the paper pursues the idea that a dynamic conception of scientific tradition will provide a new perspective for the study of geosciences history.
3
Kolyadenko, Yu Yu, and N. А. Chursanov. "5 G communication network signal propagation models." Radiotekhnika, no. 205 (July 2, 2021): 161–68. http://dx.doi.org/10.30837/rt.2021.2.205.17.
Повний текст джерелаАнотація:
The next generation 5G / IMT-2020 technology, like any new technology, brings its own specific features to all aspects related to the practice of its application. One of these particularly important aspects is electromagnetic compatibility. At the stage of preparation for the introduction of 5G radio networks, called NewRadio, it is necessary to take early measures to assess effectively the electromagnetic compatibility conditions for these networks based on a thorough analysis of the features of 5G technology. Correct and accurate assessments of these conditions means successful provision of the electromagnetic compatibility of radio equipment of new networks.
The World Radio Communication Conference WRC-15 identified new radio frequency bands for 5G, including centimeter and millimeter wave bands. In general, this RF spectrum is located in three regions: below 1 GHz, 1 GHz to 6 GHz, and above 6 GHz (up to 100 GHz). From the EMC standpoint, the following can be distinguished as the main features of this spectrum: different nature of losses during signal propagation, in particular, a significant influence of additional factors (gases – oxygen, water vapor, etc.) on the level of losses previously unknown in cellular communication.
The mathematical model of signal propagation of 5 G communication networks has been developed which takes into account: the attenuation of signals in free space; attenuation of signals caused by the influence of walls and floor slabs, loss of signal energy, when space is filled with various objects; attenuation of signals caused by loss of energy of radio waves, when propagating through rains; signal attenuation due to loss of radio wave energy due to fog; signal attenuation, when propagating through tree leaves, slow and fast random fading.
4
Ren, Huantao, Qiangjun Xie, Jiajing Chai, and Yi Xue. "Analysis of Signal Reception Mechanism of Sky Wave Long-distance Maritime Communication." MATEC Web of Conferences 232 (2018): 04065. http://dx.doi.org/10.1051/matecconf/201823204065.
Повний текст джерелаАнотація:
Based on the principle of high frequency radio propagation, the signal reception mechanism of sky wave communication over oceans is investigated. Due to long distance signal transmission, the energy loss is inevitable, especially in the space and on the sea surface. Firstly, we establish the space propagation loss model by the ionospheric absorption, the free space propagation characteristics and other extra loss. Referring to the reflection principle of smooth ground and the Kirchhoff approximation, the energy loss models of the calm sea surface and the turbulent sea surface are obtained respectively. Then, through combining the space propagation loss model and the sea surface propagation loss models, we give out a formula of receiving point field strength. According to the signal to noise ratio, we summarize a complete and concise sky wave maritime communication calculation process, through which multi hops number of the receivable sky wave signal can be calculated accurately. The experimental results show the effectiveness.
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Dorogov, A. Yu, and A. I. Yashin. "SOFTWARE PACKAGE FOR MODELING HF-BAND PACKET RADIO NETWORKS." H&ES Research 12, no. 6 (2020): 26–37. http://dx.doi.org/10.36724/2409-5419-2020-12-6-26-37.
Повний текст джерелаАнотація:
It is noted that the complexity and constant variability of the ionosphere structure, the presence of many factors affecting the propagation of radio waves in such an environment, as well as the complex topology of communication networks lead to the need the computer modeling of data transmission in HF-band networks. The existing models of representation of ionospheric processes and digital radio channels are described. It is shown that to solve the problems of designing a radio data transmission network, complex modeling is necessary, taking into account the network topology, signal propagation losses in the radio channel, noise level, type of digital modulation, and radio forecast of communication conditions. In this paper, we consider a modeling complex for packet radio networks of HF-band data transmission with changing communication conditions. The complex consists of a set of interacting models implemented in the Matlab software environment. The software model for predicting communication conditions complies with ITU-R recommendation P. 533–13 of the International Telecommunication Union (ITU). The description of the model for the "Point-to-point" and "Area" modes is given and the results of its application for calculating extended radio lines are shown. The initial data and system parameters of the model are described. A model of the HF-band digital radio channel is presented. The communications System Toolbox package, which is part of the Matlab software environment, is used for this modeling. The model's input and output data are described. A model of Ionospheric Wave Frequency Dispatcher service of the radio network has been developed. This model is intended for building a wave schedule for stable operation of HF radio lines in the network. The rules for building a two-frequency and multi-frequency wave schedule are described. A scheme for modeling the operation of a packet radio network under changing communication conditions is proposed. The complex allows you to evaluate the probabilistic and temporal characteristics of radio lines and zonal radio coverage depending on geographical coordinates, time, month, solar activity and selected system parameters for a period of up to one year. Examples of using the modeling complex are given. The purpose of this work is to formulate the problem of simulation of HF radio networks under changing communication conditions.
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Krasheninnikov, Igor, and Givi Givishvili. "Possibilities of Estimating F2 Layer Peak Plasma Frequency Using HF Radiation from High Apogee Satellites over Arctic Region." Remote Sensing 13, no. 21 (October 21, 2021): 4225. http://dx.doi.org/10.3390/rs13214225.
Повний текст джерелаАнотація:
Based on the results of mathematical modeling, we consider the possibility to estimate the plasma frequency F2 layer maximum of the polar ionosphere (critical frequency, foF2) using frequency-sweeping radiation from a highly elliptical spacecraft orbit in the Arctic zone. Our modeling concerning the energy problem of radio sensing consisted of analyzing wave field parameters, received field strength, and SNR on two radio paths with the distances 1900 and 2500 km along the earth’s surface, with the satellite height varying from 10,000 to 30,000 km. Radio path orientations were selected to be close to the classical limit cases of radio wave propagation in the anisotropic ionospheric plasma: quasi-longitudinal approximation and, to a large extent, the quasi-transversal one for the quiet midday and midnight conditions. As a result of these simulations and following specific spacecraft conditions, working with an optimal probing signal was proposed for the appropriate emission power for the onboard transmitter. In the inverse problem of radio sounding of an ionized media, common mathematical inaccuracy in foF2 calculated from the transionogram, frequency dependence of the probing signals magneto-ionic group delay, was estimated. Considering and founding a possible realization of the method, physical prerequisites are discussed based on the experimental data of radio waves passing the 16,000 km long radio path for Moscow–Antarctica (UAS Vernadsky).
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الهذيلي, محمد احمد احمد, محمد محسن الشدادي, and عبدالباسط محمد البشة. "Analytical Study of Path Loss in Radio Wave Propagation Models of the GSM Cellular Communications Networks in the City of Sana'a." Journal of Science and Technology 23, no. 1 (October 28, 2018): 41–56. http://dx.doi.org/10.20428/jst.v23i1.1399.
Повний текст джерелаАнотація:
The rapid growth of wireless communication technologies has increased the importance of a proper network planning. Before the actual installation of the network and to ensure that the network is adequately covered, network designers rely heavily on wave propagation models, which are a set of mathematical expressions, and graphs derived from comprehensive field measurements and it is used to represent radio wave properties of a particular environment. The research aims to find a mathematical model to predict the propagation path loss of radio waves in Sana'a city for the appropriate planning of cellular communication systems. In this sense, the researcher applied a practical study to the city of Sana'a by taking three cells (base station) in three different regions (urban and suburban areas and the open area). The research focuses on three stages (the stage of measurements, the stage of analysis and the stage of analysis and comparison). In the results, we obtained three values for path loss constants a and c for the three regions, through which we obtain the logarithmic curves, which in turn has been transformed into mathematical models to be used as a reference for radio planning engineers in the city of Sana'a, the capital of the Republic of Yemen.
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Alpatov, Viktor, Susanna Bekker, Stanislav Kozlov, Andrey Lyakhov, Valentin Yakim, and Sergey Yakubovsky. "ANALYZING EXISTING APPLIED MODELS OF THE IONOSPHERE TO CALCULATE RADIO WAVE PROPAGATION AND A POSSIBILITY OF THEIR USE FOR RADAR-TRACKING SYSTEMS. II. DOMESTIC MODELS." Solar-Terrestrial Physics 6, no. 3 (September 22, 2020): 60–66. http://dx.doi.org/10.12737/stp-63202008.
Повний текст джерелаАнотація:
We consider the ionospheric models that are suitable for over-the-horizon HF and UHF band radars. Namely, there are three such models: the numerical model developed by IZMIRAN and Fedorov Institute of Applied Geophysics, the numerical model designed by ISTP SB RAS and IDG RAS, and the probabilistic model worked out by IDG RAS. We briefly describe these models and report the results of the analysis of their compliance with radar requirements. Probabilistic models are shown to be most promising; hence, they must be placed at the frontier of ionosphere simulation.
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Alpatov, Viktor, Susanna Bekker, Stanislav Kozlov, Andrey Lyakhov, Valentin Yakim, and Sergey Yakubovsky. "ANALYZING EXISTING APPLIED MODELS OF THE IONOSPHERE TO CALCULATE RADIO WAVE PROPAGATION AND A POSSIBILITY OF THEIR USE FOR RADAR-TRACKING SYSTEMS. II. DOMESTIC MODELS." Solnechno-Zemnaya Fizika 6, no. 3 (September 22, 2020): 73–81. http://dx.doi.org/10.12737/szf-63202008.
Повний текст джерелаАнотація:
We consider the ionospheric models that are suitable for over-the-horizon HF and UHF band radars. Namely, there are three such models: the numerical model developed by IZMIRAN and Fedorov Institute of Applied Geophysics, the numerical model designed by ISTP SB RAS and IDG RAS, and the probabilistic model worked out by IDG RAS. We briefly describe these models and report the results of the analysis of their compliance with radar requirements. Probabilistic models are shown to be most promising; hence, they must be placed at the frontier of ionosphere simulation.
10
Aksenov, Oleg, Stanislav Kozlov, Andrey Lyakhov, Vyacheslav Trekin, Yuriy Perunov, and Sergey Yakubovsky. "ANALYZING EXISTING APPLIED MODELS OF THE IONOSPHERE FOR CALCULATING RADIO WAVE PROPAGATION AND POSSIBILITY OF THEIR USE FOR RADAR SYSTEMS. I. CLASSIFICATION OF APPLIED MODELS AND THE MAIN REQUIREMENTS IMPOSED ON THEM FOR RADAR AIDS." Solar-Terrestrial Physics 6, no. 1 (April 1, 2020): 69–76. http://dx.doi.org/10.12737/stp-61202008.
Повний текст джерелаАнотація:
We review modern HF–X band radars covering over-the-horizon problems. The ionosphere significantly affects wave propagation in all the bands. We describe available correction techniques, which use additional evidence on the ionosphere, as well as models of different degrees of complexity. The fact that the field of view cannot be covered by ground-based instruments as well as the growing requirements to the precision and stability of the radars result in the impossibility of ionospheric correction with up-to-date models, hence the latter require further elaboration. We give a virtually full classification of the models. The article summarizes the requirements to the models for the radars depending on their function.
Дисертації з теми "Ionospheric radio wave propagation Mathematical models"
1
Habarulema, John Bosco. "A contribution to TEC modelling over Southern Africa using GPS data." Thesis, Rhodes University, 2010. http://hdl.handle.net/10962/d1005241.
Повний текст джерелаАнотація:
Modelling ionospheric total electron content (TEC) is an important area of interest for radio wave propagation, geodesy, surveying, the understanding of space weather dynamics and error correction in relation to Global Navigation Satellite Systems (GNNS) applications. With the utilisation of improved ionosonde technology coupled with the use of GNSS, the response of technological systems due to changes in the ionosphere during both quiet and disturbed conditions can be historically inferred. TEC values are usually derived from GNSS measurements using mathematically intensive algorithms. However, the techniques used to estimate these TEC values depend heavily on the availability of near-real time GNSS data, and therefore, are sometimes unable to generate complete datasets. This thesis investigated possibilities for the modelling of TEC values derived from the South African Global Positioning System (GPS)receiver network using linear regression methods and artificial neural networks (NNs). GPS TEC values were derived using the Adjusted Spherical Harmonic Analysis (ASHA) algorithm. Considering TEC and the factors that influence its variability as “dependent and independent variables” respectively, the capabilities of linear regression methods and NNs for TEC modelling were first investigated using a small dataset from two GPS receiver stations. NN and regression models were separately developed and used to reproduce TEC fluctuations at different stations not included in the models’ development. For this purpose, TEC was modelled as a function of diurnal variation, seasonal variation, solar and magnetic activities. Comparative analysis showed that NN models provide predictions of GPS TEC that were an improvement on those predicted by the regression models developed. A separate study to empirically investigate the effects of solar wind on GPS TEC was carried out. Quantitative results indicated that solar wind does not have a significant influence on TEC variability. The final TEC simulation model developed makes use of the NN technique to find the relationship between historical TEC data variations and factors that are known to influence TEC variability (such as solar and magnetic activities, diurnal and seasonal variations and the geographical locations of the respective GPS stations) for the purposes of regional TEC modelling and mapping. The NN technique in conjunction with interpolation and extrapolation methods makes it possible to construct ionospheric TEC maps and to analyse the spatial and temporal TEC behaviour over Southern Africa. For independent validation, modelled TEC values were compared to ionosonde TEC and the International Reference Ionosphere (IRI) generated TEC values during both quiet and disturbed conditions. This thesis provides a comprehensive guide on the development of TEC models for predicting ionospheric variability over the South African region, and forms a significant contribution to ionospheric modelling efforts in Africa.
2
Tshisaphungo, Mpho. "Validation of high frequency propagation prediction models over Africa." Thesis, Rhodes University, 2010. http://hdl.handle.net/10962/d1015239.
Повний текст джерелаАнотація:
The ionosphere is an important factor in high frequency (HF) radio propagation providing an opportunity to study ionospheric variability as well as the space weather conditions under which HF communication can take place. This thesis presents the validation of HF propagation conditions for the Ionospheric Communication Enhanced Profile Analysis and Circuit (ICEPAC) and Advanced Stand Alone Prediction System (ASAPS) models over Africa by comparing predictions with the measured data obtained from the International Beacon Project (IBP). Since these models were not developed using information on the African region, a more accurate HF propagation prediction tool is required. Two IBP transmitter stations are considered, Ruaraka, Kenya (1.24°S, 36.88°E) and Pretoria, South Africa (25.45°S, 28.10°E) with one beacon receiver station located in Hermanus, South Africa (34.27°S, 19.l2°E). The potential of these models in terms of HF propagation conditions is illustrated. An attempt to draw conclusions for future improvement of the models is also presented. Results show a low prediction accuracy for both ICEPAC and ASAPS models, although ICEPAC provided more accurate predictions for daily HF propagation conditions. This thesis suggests that the development of a new HF propagation prediction tool for the African region or the modification of one of the existing models to accommodate the African region, taking into account the importance of the African ionospheric region, should be considered as an option to ensure more accurate HF Propagation predictions over this region.
3
Pirkl, Ryan J. "Measurement-based investigations of radio wave propagation: an exposé on building corner diffraction." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33961.
Повний текст джерелаАнотація:
Predicting performance metrics for the next-generation of multi-mode and multi-antenna wireless communication systems demands site-specific knowledge of the wireless channel's underlying radio wave propagation mechanisms. This thesis describes the first measurement system capable of characterizing individual propagation mechanisms in situ. The measurement system merges a high-resolution spatio-temporal wireless channel sounder with a new field reconstruction technique to provide complete knowledge of the wireless channel's impulse response throughout a 2-dimensional region. This wealth of data may be combined with space-time filtering techniques to isolate and characterize individual propagation mechanisms. The utility of the spatio-temporal measurement system is demonstrated through a measurement-based investigation of diffraction around building corners. These measurements are combined with space-time filtering techniques and a new linear wedge diffraction model to extract the first semi-mpirical diffraction coefficient. Specific contributions of this thesis are:
* The first ultra-wideband single-input multiple-output (SIMO) channel sounder based upon the sliding correlator architecture.
* A quasi 2-dimensional field reconstruction technique based upon a conjoint cylindrical wave expansion of coherent perimeter measurements.
* A wireless channel ``filming' technique that records the time-domain evolution of the wireless channel throughout a 2-dimensional region.
* High-resolution measurements of the space-time wireless channel near a right-angled brick building corner.
* The application of space-time filtering techniques to isolate the edge diffraction problem from the overall wireless channel.
* An approximate uniform geometrical theory of diffraction (UTD)-style linear model describing diffraction by an impedance wedge.
* The first-ever semi-empirical diffraction coefficient extracted from in situ measurement data.
This thesis paves the way for several new avenues of research. The comprehensive measurement data provided by channel "filming" will enable researchers to develop and implement powerful space-time filtering techniques that facilitate measurement-based investigations of radio wave propagation. The measurement procedure described in this thesis may be adapted to extract realistic reflection and rough-surface scattering coefficients. Finally, exhaustive measurements of individual propagation mechanisms will enable the first semi-empirical propagation model that integrates empirical descriptions of propagation mechanisms into a UTD-style mechanistic framework.
4
Bradley, W. Scott. "Propagation modeling for land mobile satellite communications." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/74511.
Повний текст джерелаАнотація:
Satellite systems are being planned for two-way communication with mobile vehicles using UHF and L-band frequencies. Of special concern in the system design are the characteristics of propagation in suburban and rural areas where fading occurs due to multipath effects and vegetative shadowing. A review of the literature was performed to study these propagation impairments. Available experimental data are examined, compared, and summarized. Propagation through vegetation is studied in order to compare reported modeling efforts and to determine the parameter dependences of path loss. A simple deterministic path model is then presented to estimate vegetative path loss. An overall statistical model is also proposed to describe the signal level fading statistics. The statistical model is compared to data, and the deterministic path model is used to determine the mean of signal level distribution functions in the presence of shadowing.Master of Science
5
Elsden, Tom. "Numerical modelling of ultra low frequency waves in Earth's magnetosphere." Thesis, University of St Andrews, 2016. http://hdl.handle.net/10023/15663.
Повний текст джерелаАнотація:
Ultra Low Frequency (ULF) waves are a ubiquitous feature of Earth's outer atmosphere, known as the magnetosphere, having been observed on the ground for almost two centuries, and in space over the last 50 years. These waves represent small oscillations in Earth's magnetic field, most often as a response to the external influence of the solar wind. They are important for the transfer of energy throughout the magnetosphere and for coupling different regions together. In this thesis, various features of these oscillations are considered. A detailed background on the history and previous study of ULF waves relevant to our work is given in the introductory chapter. In the following chapters, we predominantly use numerical methods to model ULF waves, which are carefully developed and thoroughly tested. We consider the application of these methods to reports on ground and spaced based observations, which allows a more in depth study of the data. In one case, the simulation results provide evidence for an alternative explanation of the data to the original report, which displays the power of theoretical modelling. An analytical model is also constructed, which is tested on simulation data, to identify the incidence and reflection of a class of ULF wave in the flank magnetosphere. This technique is developed with the aim of future applications to satellite data. Further to this, we develop models both in Cartesian and dipole geometries to investigate some of the theoretical aspects of the coupling between various waves modes. New light is shed on the coupling of compressional (fast) and transverse (Alfvén) magnetohydrodynamic (MHD) wave modes in a 3D dipole geometry. Overall, this thesis aims to develop useful numerical models, which can be used to aid in the interpretation of ULF wave observations, as well as probing new aspects of the existing wave theory.
6
Wang, Huihui. "Modeling and wideband characterization of radio wave propagation in microcells." Thesis, 2005. http://hdl.handle.net/2152/1806.
Повний текст джерела
7
"Function-based and physics-based hybrid modular neural network for radio wave propagation modeling." 1999. http://library.cuhk.edu.hk/record=b5890075.
Повний текст джерелаАнотація:
by Lee Wai Hung.Thesis (M.Phil.)--Chinese University of Hong Kong, 1999.
Includes bibliographical references (leaves 118-121).
Abstracts in English and Chinese.
Chapter 1 --- INTRODUCTION --- p.1
Chapter 1.1 --- Background --- p.1
Chapter 1.2 --- Structure of Thesis --- p.8
Chapter 1.3 --- Methodology --- p.8
Chapter 2 --- BACKGROUND THEORY --- p.10
Chapter 2.1 --- Radio Wave Propagation Modeling --- p.10
Chapter 2.1.1 --- Basic Propagation Phenomena --- p.10
Chapter 2.1.1.1 --- Propagation in Free Space --- p.10
Chapter 2.1.1.2 --- Reflection and Transmission --- p.11
Chapter 2.1.2 --- Practical Propagation Models --- p.12
Chapter 2.1.2.1 --- Longley-Rice Model --- p.13
Chapter 2.1.2.2 --- The Okumura Model --- p.13
Chapter 2.1.3 --- Indoor Propagation Models --- p.14
Chapter 2.1.3.1 --- Alexander Distance/Power Laws --- p.14
Chapter 2.1.3.2 --- Saleh Model --- p.15
Chapter 2.1.3.3 --- Hashemi Experiments --- p.16
Chapter 2.1.3.4 --- Path Loss Models --- p.17
Chapter 2.1.3.5 --- Ray Optical Models --- p.18
Chapter 2.2 --- Ray Tracing： Brute Force approach --- p.20
Chapter 2.2.1 --- Physical Layout --- p.20
Chapter 2.2.2 --- Antenna Information --- p.20
Chapter 2.2.3 --- Source Ray Directions --- p.21
Chapter 2.2.4 --- Formulation --- p.22
Chapter 2.2.4.1 --- Formula of Amplitude --- p.22
Chapter 2.2.4.2 --- Power Reference E o --- p.23
Chapter 2.2.4.3 --- Power spreading with path length 1/d --- p.23
Chapter 2.2.4.4 --- Antenna Patterns --- p.23
Chapter 2.2.4.5 --- Reflection and Transmission Coefficients --- p.24
Chapter 2.2.4.6 --- Polarization --- p.26
Chapter 2.2.5 --- Mean Received Power --- p.26
Chapter 2.2.6 --- Effect of Thickness --- p.27
Chapter 2.3 --- Neural Network --- p.27
Chapter 2.3.1 --- Architecture --- p.28
Chapter 2.3.1.1 --- Multilayer feedforward network --- p.28
Chapter 2.3.1.2 --- Recurrent Network --- p.29
Chapter 2.3.1.3 --- Fuzzy ARTMAP --- p.29
Chapter 2.3.1.4 --- Self organization map --- p.30
Chapter 2.3.1.5 --- Modular Neural network --- p.30
Chapter 2.3.2 --- Training Method --- p.32
Chapter 2.3.3 --- Advantages --- p.33
Chapter 2.3.4 --- Definition --- p.34
Chapter 2.3.5 --- Software --- p.34
Chapter 3 --- HYBRID MODULAR NEURAL NETWORK --- p.35
Chapter 3.1 --- Input and Output Parameters --- p.35
Chapter 3.2 --- Architecture --- p.36
Chapter 3.3 --- Data Preparation --- p.42
Chapter 3.4 --- Advantages --- p.42
Chapter 3.5 --- Limitation --- p.43
Chapter 3.6 --- Applicable Environment --- p.43
Chapter 4 --- INDIVIDUAL MODULES IN HYBRID MODULAR NEURAL NETWORK --- p.45
Chapter 4.1 --- Conversion between spherical coordinate and Cartesian coordinate --- p.46
Chapter 4.1.1 --- Architecture --- p.46
Chapter 4.1.2 --- Input and Output Parameters --- p.47
Chapter 4.1.3 --- Testing result --- p.48
Chapter 4.2 --- Performing Rotation and translation transformation --- p.53
Chapter 4.3 --- Calculating a hit point --- p.54
Chapter 4.3.1 --- Architecture --- p.55
Chapter 4.3.2 --- Input and Output Parameters --- p.55
Chapter 4.3.3 --- Testing result --- p.56
Chapter 4.4 --- Checking if an incident ray hits a Scattering Surface --- p.59
Chapter 4.5 --- Calculating separation distance between source point and hitting point --- p.59
Chapter 4.5.1 --- Input and Output Parameters --- p.60
Chapter 4.5.2 --- Data Preparation --- p.60
Chapter 4.5.3 --- Testing result --- p.61
Chapter 4.6 --- Calculating propagation vector of secondary ray --- p.63
Chapter 4.7 --- Calculating polarization vector of secondary ray --- p.63
Chapter 4.7.1 --- Architecture --- p.64
Chapter 4.1.2 --- Input and Output Parameters --- p.65
Chapter 4.7.3 --- Testing result --- p.68
Chapter 4.8 --- Rejecting ray from simulation --- p.72
Chapter 4.9 --- Calculating receiver signal --- p.73
Chapter 4.10 --- Further comment on preparing neural network --- p.74
Chapter 4.10.1 --- Data preparation --- p.74
Chapter 4.10.2 --- Batch training --- p.75
Chapter 4.10.3 --- Batch size --- p.78
Chapter 5 --- CANONICAL EVALUATION OF MODULAR NEURAL NETWORK --- p.80
Chapter 5.1 --- Typical environment simulation compared with ray launching --- p.80
Chapter 5.1.1 --- Free space --- p.80
Chapter 5.1.2 --- Metal ground reflection --- p.81
Chapter 5.1.3 --- Dielectric ground reflection --- p.84
Chapter 5.1.4 --- Empty Hall --- p.86
Chapter 6 --- INDOOR PROPAGATION ENVIRONMENT APPLICATION --- p.90
Chapter 6.1 --- Introduction --- p.90
Chapter 6.2 --- Indoor measurement on the Third Floor of Engineering Building --- p.90
Chapter 6.3 --- Comparison between simulation and measurement result --- p.92
Chapter 6.3.1 --- Path 1 --- p.93
Chapter 6.3.2 --- Path 2 --- p.95
Chapter 6.3.3 --- Path 3 --- p.97
Chapter 6.3.4 --- Path 4 --- p.99
Chapter 6.3.5 --- Overall Performance --- p.100
Chapter 6.4 --- Delay Spread Analysis --- p.101
Chapter 6.4.1 --- Location 1 --- p.103
Chapter 6.4.2 --- Location 2 --- p.105
Chapter 6.4.3 --- Location 3 --- p.107
Chapter 6.4.4 --- Location 4 --- p.109
Chapter 6.4.5 --- Location 5 --- p.111
Chapter 6.5 --- Summary --- p.112
Chapter 7 --- CONCLUSION --- p.I
Chapter 7.1 --- Summary --- p.113
Chapter 7.2 --- Recommendations for Future Work --- p.115
PUBLICATION LIST --- p.117
BIBLIOGRAHY --- p.118
Книги з теми "Ionospheric radio wave propagation Mathematical models"
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I, Kleev A., Manenkov A. B, Kinber Boris Evseevich та Vsesoi͡uznai͡a shkola po difrakt͡sii i rasprostranenii͡u voln (9th : 1988 : Chistopolʹ, Russia), ред. Metod vspomogatelʹnykh istochnikov: Reshenie vneshnikh difrakt͡sionnykh zadach : materialy IX Vsesoi͡uznoĭ shkoly po difrakt͡sii i rasprostranenii͡u voln. Kazanʹ: Kazanskiĭ aviat͡sionnyĭ in-t im. A.N. Tupoleva, 1988.
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Magnetics, dielectrics, and wave propagation with MATLAB codes. Boca Raton: CRC Press, 2011.
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author, Zhu Ning Yan, and Institution of Engineering and Technology, eds. Scattering of waves by wedges and cones with impedance boundary conditions. Edison, NJ: Scitech Publishing, an imprint of the IET, 2013.
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Propagation Handbook for Wireless Communication System Design. London: Taylor and Francis, 2003.
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Metamaterials: Critique and alternatives. Hoboken, N.J: Wiley, 2008.
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Budden, K. G. Radio waves in the ionosphere: The mathematical theory of the reflection of radio waves from stratified ionised layers. Cambridge: Cambridge University Press, 2009.
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Giger, Adolf J. Low-angle microwave propagation: Physics and modeling. Boston: Artech House, 1991.
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Brussaard, G. Atmospheric modelling and millimetre wave propagation. London: Chapman & Hall, 1995.
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Lebherz, Manfred. Wellenausbreitungsmodelle zur Versorgungsplanung im VHF/UHF Bereich unter Berücksichtigung der Mehrwegeausbreitung. Baden-Baden: Nomos, 1991.
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Introduction to RF propagation. Hoboken, N.J: John Wiley & Sons, Inc., 2005.
Знайти повний текст джерелаТези доповідей конференцій з теми "Ionospheric radio wave propagation Mathematical models"
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Afanasiev, Nikolay T., and Stanislav O. Chudaev. "Mathematical Modeling of the Effect of Drift of Plasma Random Irregularities on the Spectral Line Width of an Ionospheric Sounder." In 2019 Russian Open Conference on Radio Wave Propagation (RWP). IEEE, 2019. http://dx.doi.org/10.1109/rwp.2019.8810162.
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"VALIDATION OF TWO NEW EMPIRICAL IONOSPHERIC MODELS IRI-PLAS AND NGM DESCRIBING CONDITIONS OF RADIO WAVE PROPAGATION IN SPACE." In Second International Conference on Telecommunications and Remote Sensing. SCITEPRESS - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004786001090118.
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Kryukovsky, Andrew S., Dmitry S. Lukin, Dmitry V. Rastyagaev, and Yulia I. Bova. "The method of mathematical modeling of wave fields and caustic structures in the process of propagation of electromagnetic radiation in the ionospheric plasma." In 2021 XXXIVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS). IEEE, 2021. http://dx.doi.org/10.23919/ursigass51995.2021.9560385.
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