scholarly journals AOTF-based hyperspectral imaging system for unmanned aerial vehicles

2019 ◽  
Author(s):  
Vladislav Batshev ◽  
Vitold Pozhar ◽  
Alexander Machikhin ◽  
Maxim Gaponov ◽  
Sergey Shirokov ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Hyperspectral Imaging ◽  
Imaging System ◽  
Aerial Vehicles

scholarly journals Convolutional neural network target detection in hyperspectral imaging for maritime surveillance

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141984299
Author(s):  
Sara Freitas ◽  
Hugo Silva ◽  
José Miguel Almeida ◽  
Eduardo Silva
Keyword(s):  
Neural Network ◽  
Anomaly Detection ◽  
Convolutional Neural Network ◽  
Unmanned Aerial Vehicles ◽  
Hyperspectral Imaging ◽  
Imaging System ◽  
Spectral Angle Mapper ◽  
Maritime Surveillance ◽  
Aerial Vehicles ◽  
Spectral Angle

This work addresses a hyperspectral imaging system for maritime surveillance using unmanned aerial vehicles. The objective was to detect the presence of vessels using purely spatial and spectral hyperspectral information. To accomplish this objective, we implemented a novel 3-D convolutional neural network approach and compared against two implementations of other state-of-the-art methods: spectral angle mapper and hyperspectral derivative anomaly detection. The hyperspectral imaging system was developed during the SUNNY project, and the methods were tested using data collected during the project final demonstration, in São Jacinto Air Force Base, Aveiro (Portugal). The obtained results show that a 3-D CNN is able to improve the recall value, depending on the class, by an interval between 27% minimum, to a maximum of over 40%, when compared to spectral angle mapper and hyperspectral derivative anomaly detection approaches. Proving that 3-D CNN deep learning techniques that combine spectral and spatial information can be used to improve the detection of targets classification accuracy in hyperspectral imaging unmanned aerial vehicles maritime surveillance applications.

scholarly journals Computationaly Simple Obstacle Avoidance Control Law for Small Unmanned Aerial Vehicles

2015 ◽  
Vol 9 (1) ◽  
pp. 50-56 ◽  
Author(s):  
Jakub Cieśluk ◽  
Zdzisław Gosiewski ◽  
Leszek Ambroziak ◽  
Sławomir Romaniuk
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Obstacle Avoidance ◽  
Imaging System ◽  
Information Source ◽  
Digital Camera ◽  
Control Law ◽  
Simulation Studies ◽  
Aerial Vehicles ◽  
Avoidance Control ◽  
Computational Simplicity

Abstract The investigations of the system which allow to avoid obstacles by the unmanned aerial vehicles (UAV) are presented in the paper. The system is designed to enable the full autonomous UAV flight in an unknown environment. As an information source about obstacles digital camera was used. Developed algorithm uses the existing relations between the imaging system and the parameters read from the UAV autopilot. Synthesis of the proposed obstacle avoidance control law was oriented for computational simplicity. Presented algorithm was checked during simulation studies and in-flight tests.

scholarly journals Unmanned aerial vehicles supporting imagery intelligence using the structured light technology

2021 ◽  
Vol 58 (2) ◽  
pp. 35-45
Author(s):  
Leszek Ułanowicz ◽  
Ryszard Sabak
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Image Recognition ◽  
Imaging System ◽  
Structured Light ◽  
Three Dimensional ◽  
Measurement Data ◽  
Recognition System ◽  
Measurement Technology ◽  
Vision Measurement ◽  
Aerial Vehicles

One of the possible tasks for unmanned aerial vehicles (UAVs) is field capturing of object images. The field capturing of object images (scenes) is possible owing to the UAV equipped with photographic cameras, TV cameras, infrared camer-as or synthetic aperture radars (SAR). The result of the recognition is a metric mapping of space, i.e. 2D flat images. In order to increase the quality of image recognition, it is necessary to search for and develop stereoscopic visualization with the possibility of its mobile use. A pioneering approach presented in the research paper is using a UAV with an imagery intelligence system based on structured light technology for air reconnaissance of object over a selected area or in a given direction in the field. The outcome of imagery intelligence is a three-dimensional (3D imaging) information on the geometry of an observed scene. The visualization with a stereoscopic interface proposed in the work allows for a natural perception of the depth of the scene and mutual spatial relationships, as well as seeing which objects are closer and which are further. The essence of the article is to present the application of three-dimensional vision measurement technology on UAVs. The paper presents an analysis of the possibilities of using UAVs for image recognition and a method of image recognition based on the technology of structural lighting using the method of projection of Gray’a fringes and codes. The designed image recognition system based on the structural lighting technology is described. It also discusses task modules forming a measuring head, i.e., projection, detection and calculation modules, and the exchange of control or measurement data between imaging system components. It presents the results of tests on the possibility of rapidly acquiring images using a UAV. The test results and the analyses indicate that using a UAV with an imaging technology based on structural light can contribute to improving the abilities to detect, identify, locate and monitor objects at close range, within a selected direction outdoors or indoors.

scholarly journals Development of a VNIR/SWIR Multispectral Imaging System for Vegetation Monitoring with Unmanned Aerial Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5507 ◽  
Author(s):  
Alexander Jenal ◽  
Georg Bareth ◽  
Andreas Bolten ◽  
Caspar Kneer ◽  
Immanuel Weber ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicles ◽  
Multispectral Imaging ◽  
Imaging System ◽  
Short Wave ◽  
Vegetation Monitoring ◽  
Sensing Applications ◽  
Aerial Vehicles ◽  
Remote Sensing Applications ◽  
Short Wave Infrared

Short-wave infrared (SWIR) imaging systems with unmanned aerial vehicles (UAVs) are rarely used for remote sensing applications, like for vegetation monitoring. The reasons are that in the past, sensor systems covering the SWIR range were too expensive, too heavy, or not performing well enough, as, in contrast, it is the case in the visible and near-infrared range (VNIR). Therefore, our main objective is the development of a novel modular two-channel multispectral imaging system with a broad spectral sensitivity from the visible to the short-wave infrared spectrum (approx. 400 nm to 1700 nm) that is compact, lightweight and energy-efficient enough for UAV-based remote sensing applications. Various established vegetation indices (VIs) for mapping vegetation traits can then be set up by selecting any suitable filter combination. The study describes the selection of the individual components, starting with suitable camera modules, the optical as well as the control and storage parts. Special bandpass filters are used to select the desired wavelengths to be captured. A unique flange system has been developed, which also allows the filters to be interchanged quickly in order to adapt the system to a new application in a short time. The characterization of the system was performed in the laboratory with an integrating sphere and a climatic chamber. Finally, the integration of the novel modular VNIR/SWIR imaging system into a UAV and a subsequent first outdoor test flight, in which the functionality was tested, are described.

Development of thickened semi-synthetic engine oil M-5z / 20 AERO for four-stroke gasoline engines aircraft piston of unmanned aerial vehicles (UAVs)

2020 ◽  
Vol 06 ◽  
pp. 44-47
Author(s):  
A.A. Moykin ◽  
◽  
A.S. Medzhibovsky ◽  
S.A. Kriushin ◽  
M.V. Seleznev ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Engine Oil ◽  
Motor Oil ◽  
Gasoline Engines ◽  
State Research Institute ◽  
Technical Requirements ◽  
Aerial Vehicles ◽  
State Research ◽  
Industrial Batch ◽  
The Russian Federation

Nowadays, the creation of remotely-piloted aerial vehicles for various purposes is regarded as one of the most relevant and promising trends of aircraft development. FAU "25 State Research Institute of Chemmotology of the Ministry of Defense of the Russian Federation" have studied the operation features of aircraft piston engines and developed technical requirements for motor oil for piston four-stroke UAV engines, as well as a new engine oil M-5z/20 AERO in cooperation with NPP KVALITET, LLC. Based on the complex of qualification tests, the stated operational properties of the experimental-industrial batch of M-5z/20 AERO oil are generally confirmed.

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