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The electronic equipment of combat aircraft of 4th and 5th generation
Hron, Kvido ; Koštial, Rostislav (referee) ; Dubnický, Lukáš (advisor)
Modern aerial combat requires sophisticated electronic equipment to enhance the combat capabilities of fighter jets. This work focuses on the electronic equipment of fighter jets, emphasizing their advanced technological capabilities and operational significance. The study examines the development of electronic warfare systems, radar technologies, communication setups, and self-protection measures across different generations of fighter jets. The paper highlights the crucial role of electronic equipment in improving pilot situational awareness, survivability, and mission effectiveness in modern aerial combat scenarios. Additionally, the work explores the integration of advanced sensors, processors, and artificial intelligence algorithms in fourth- and fifth-generation fighter jets, elucidating their impact on mission success and operational superiority. By providing insights into the electronic equipment and capabilities of these advanced aerial platforms, this study contributes to a deeper understanding of the evolving aerial combat environment in the 21st century.
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Real-time propojení senzorů pro navigaci
Kaczmarek, Adrian ; Rohm, Witold ; Klingbeil, Lasse ; Tchórzewski, Janusz
The development of satellite techniques in the field of precise positioning and the availability of mobile devices with a built-in multi-GNSS (Global Navigation Satellite System) receiver allow us to determine positions with better accuracy than a dozen or so years ago. At the same time, there is a growing demand from users for more and more accurate positioning while reducing the costs of the final device (e.g., a navigation system for autonomous lawn mowers). This work presents the concept of a solution that integrates different positioning techniques: gyroscopes, odometers, and GNSS using a loosely coupled Kalman filter. The sensor integration model was developed for horizontal components (2D) with simultaneous determination of azimuth and precise position. Additionally, the integration filter uses a dynamic weight matrix, the values of which are selected depending on the type of GNSS solution (FIX, FLOAT, etc.). Tests of the measurement platform were carried out under ideal conditions and in places where the horizon is obscured (passes along a high wall, under openwork steel trusses, etc.). The accuracies obtained during tests using EKF and the dynamic weight matrix are RMS 0.019 m for the North and East components. However, the accuracy of the azimuth determination was 0.59°. In addition, the presentation will present a platform concept that integrates low-cost sensors in real time.
This work was supported by Wroclaw University of Environmental and Life Sciences (Poland) under the project “POMOST” (grant no. N110/0002/22).
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LIDAR and Stereocamera in Localization of Mobile Robots
Vyroubalová, Jana ; Drahanský, Martin (referee) ; Orság, Filip (advisor)
LIDAR (2D) has been widely used for mapping, localization and navigation in mobile robotics. However, its usage is limited to simple environments. This problem can be solved by adding more sensors and processing these data together. This paper explores a method how measurements from a stereo camera and LIDAR are fused to dynamical mapping. An occupancy grid map from LIDAR data is used as prerequisite and extended by a 2D grid map from stereo camera. This approach is based on the ground plane estimation in disparity map acquired from the stereo vision. For the ground plane detection, RANSAC and Least Squares methods are used. After obstacles determination, 2D occupancy map is generated. The output of this method is 2D map as a fusion of complementary maps from LIDAR and camera. Experimental results obtained from RUDA robot and MIT Stata Center Data Set are good enough to determine that this method is a benefit, although my implementation is still a prototype. In this paper, we present the applied methods, analyze the results and discuss the modifications and possible extensions to get better results.
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Sensor fusion for detecting and locating people in a room
Vondráček, Jakub ; Dobossy, Barnabás (referee) ; Najman, Jan (advisor)
This diploma thesis deals with the problem of fusion of several sensors for the purpose of detecting and locating people in a room. It is primarily about using measured sensors and implementing them in such a way that their connection creates a system that has obvious advantages compared to more expensive single sensor solutions. In the first part of the work, research is carried out, which presents the basic issues of detection, localization and counting of people in rooms. To be used in the practical part of the work, it is also indicated here which specific sensors can be used to achieve these functions and which control units are suitable for such a system. Finally, it summarizes specific components and software tools, which are further supplemented in the practical part of the work. The rationale for this selection is also included. The second part of the thesis describes the specific design of the resulting system, which can perform the functions of detection, localization and counting of people in the room. This practical proposal is described including all starting points, connections and especially the algorithm that was used for sensor fusion. The entire system is subsequently tested, based on which its functioning is evaluated. In the last section of the thesis, the created system is supplemented with a model of a cover and wall mount.
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LIDAR and Stereocamera in Localization of Mobile Robots
Vyroubalová, Jana ; Drahanský, Martin (referee) ; Orság, Filip (advisor)
LIDAR (2D) has been widely used for mapping, localization and navigation in mobile robotics. However, its usage is limited to simple environments. This problem can be solved by adding more sensors and processing these data together. This paper explores a method how measurements from a stereo camera and LIDAR are fused to dynamical mapping. An occupancy grid map from LIDAR data is used as prerequisite and extended by a 2D grid map from stereo camera. This approach is based on the ground plane estimation in disparity map acquired from the stereo vision. For the ground plane detection, RANSAC and Least Squares methods are used. After obstacles determination, 2D occupancy map is generated. The output of this method is 2D map as a fusion of complementary maps from LIDAR and camera. Experimental results obtained from RUDA robot and MIT Stata Center Data Set are good enough to determine that this method is a benefit, although my implementation is still a prototype. In this paper, we present the applied methods, analyze the results and discuss the modifications and possible extensions to get better results.
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