Simulation of Lightning Flash and Detection Using Time of Arrival Method Based on Four Broadband Antennas

Author(s):  
Saeed Vahabi Mashak ◽  
Hadi Nabipour Afrouzi ◽  
Zulkurnain Abdul-Malek
2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Saeed Vahabi-Mashak ◽  
Zulkurnain Abdul-Malek ◽  
Kamyar Mehranzamir ◽  
Hadi Nabipour-Afrouzi ◽  
Behnam Salimi ◽  
...  

Various methods are used to locate cloud-to-ground lightning flashes. Even though a higher cost is incurred, a network of sensor stations is preferable to a single station due to the improved accuracy. For a single station measuring system, the accuracy of its analyses is mostly based on the chosen mathematical equations which can be solved in either linear or nonlinear mode. The sensitivity of the measuring equipment used is also particularly significant. This paper concentrates on the modelling of time of arrival (TOA) technique for locating a lightning flash by utilizing three broadband antennas. Consequently, by employing the developed model, the influences of geometric parameters on the accuracy of the model are evaluated. Therefore, a Matlab based simulation of the measuring system is developed. In the developed codes, randomly located lightning flash with its corresponding electromagnetic radiation was modelled. Results show that parameters such as lightning path shape, distance of the leader, and leader location can directly affect the accuracy of the TOA technique for extracting the azimuth and elevation.


2021 ◽  
Author(s):  
Alok Taori ◽  
Arun Suryavanshi ◽  
Biswadip Gharai ◽  
Sunil Pawar ◽  
M. V. R. Seshasai

Abstract A network of 25 lightning detection sensors (LDS) has been established by National Remote Sensing Centre (NRSC), Indian Space Research Organization (ISRO). In the present network, sensors are located in the north-east, east coastal, central and southern locations of India. Geo-location of the lightning occurrences is estimated using time of arrival algorithm. Thus obtained lightning occurrences have been used to derive climate variables (ECVs) and to understand the vulnerable regions. We carry out overlay analysis on a Geographical Information System (GIS) platform on the monthly aggregate number of CG flash occurrences to identify the vulnerable Indian states during July 2019 to November 2020. We note that December-January reported the least number of cloud-to-ground (CG) flash occurrences while, August-September were the months with most number of CG flash occurrences. We also note that during the period under the scrutiny in this report, Chattisgarh, Jharkhand, Odisha, Maharashtra and Madhya Pradesh states recorded the most number of CG lightning flash occurrences.


Author(s):  
Ahmad Idil Abd Rahman ◽  
◽  
Muhammad Akmal Bahari ◽  
Zikri Abadi Baharudin ◽  
◽  
...  

2018 ◽  
Vol 77 (6) ◽  
pp. 232-330
Author(s):  
A. V. Komissarov ◽  
E. A. Makarova ◽  
S. V. Muktepavel ◽  
I. A. Nestrakhov ◽  
I. N. Spesivtseva

Abstract. In modern conditions for passenger complex of Russian Railways, important tasks include improvement of transportation quality, maintenance of stable positions in a competitive environment and increasing demand. To address these issues, a customer-oriented approach is applied based on the segmentation of transport market in relation to certain groups of passengers. Performance of children's transportation is of particular relevance and social significance. Railways are charged with a huge range of work, including sale of travel documents, preparation and equipping of passenger cars, provision of food during the trip, instructing workers, ensuring security during the embarkation/disembarkation of passengers, etc. Children can travel as individually with accompanying persons and as part of organized groups. Processes of planning, organizing, monitoring the transportation of this age category of passengers are associated with the analysis of a large amount of reference and regulatory and reporting documentation. On the basis of the ACS “Express-3”, a program-analytical complex “Children's transportation” was developed and implemented, which allows to receive data at the regional and network levels in the operational (train number, day) and statistical (period of dates, month) modes. This information technology provides analytical support for key transportation management functions — planning, control, analysis. Planning of transportation of organized children's groups is carried out on the basis of a study of the dynamics of data on the number of applications received and travel documents issued, determining the routes of trains, periods of the highest intensity of passenger traffic, obtaining information about the stations of embarkation and disembarkation. To perform the functions of monitoring the embarkation and disembarkation at the destination station of groups of children, the employees involved receive information on the train number, car number, date and time of arrival, number of children in the group using the Children's Transportation software. For the analysis of transportation of children's age categories, a functional has been developed that ensures the construction of aggregated reporting based on trains data that completed the trip. Users receive reporting information in table form, including “strict” (designed according to the approved layout) and “flexible” forms (construction is performed according to specified parameters). Software and analytical complex is designed for managers and specialists of the passenger unit of the JSC “Russian Railways”, has a modular principle of increasing functionality and provides a solution to current problems in the system of organizing children's transport service.


2021 ◽  
pp. 1-15
Author(s):  
O. Basturk ◽  
C. Cetek

ABSTRACT In this study, prediction of aircraft Estimated Time of Arrival (ETA) is proposed using machine learning algorithms. Accurate prediction of ETA is important for management of delay and air traffic flow, runway assignment, gate assignment, collaborative decision making (CDM), coordination of ground personnel and equipment, and optimisation of arrival sequence etc. Machine learning is able to learn from experience and make predictions with weak assumptions or no assumptions at all. In the proposed approach, general flight information, trajectory data and weather data were obtained from different sources in various formats. Raw data were converted to tidy data and inserted into a relational database. To obtain the features for training the machine learning models, the data were explored, cleaned and transformed into convenient features. New features were also derived from the available data. Random forests and deep neural networks were used to train the machine learning models. Both models can predict the ETA with a mean absolute error (MAE) less than 6min after departure, and less than 3min after terminal manoeuvring area (TMA) entrance. Additionally, a web application was developed to dynamically predict the ETA using proposed models.


Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 782
Author(s):  
Shuo Cao ◽  
Honglei Qin ◽  
Li Cong ◽  
Yingtao Huang

Position information is very important tactical information in large-scale joint military operations. Positioning with datalink time of arrival (TOA) measurements is a primary choice when a global navigation satellite system (GNSS) is not available, datalink members are randomly distributed, only estimates with measurements between navigation sources and positioning users may lead to a unsatisfactory accuracy, and positioning geometry of altitude is poor. A time division multiple address (TDMA) datalink cooperative navigation algorithm based on INS/JTIDS/BA is presented in this paper. The proposed algorithm is used to revise the errors of the inertial navigation system (INS), clock bias is calibrated via round-trip timing (RTT), and altitude is located with height filter. The TDMA datalink cooperative navigation algorithm estimate errors are stated with general navigation measurements, cooperative navigation measurements, and predicted states. Weighted horizontal geometric dilution of precision (WHDOP) of the proposed algorithm and the effect of the cooperative measurements on positioning accuracy is analyzed in theory. We simulate a joint tactical information distribution system (JTIDS) network with multiple members to evaluate the performance of the proposed algorithm. The simulation results show that compared to an extended Kalman filter (EKF) that processes TOA measurements sequentially and a TDMA datalink navigation algorithm without cooperative measurements, the TDMA datalink cooperative navigation algorithm performs better.


Sign in / Sign up

Export Citation Format

Share Document