scholarly journals Unmanned Aerial Vehicle Recognition Based on Clustering by Fast Search and Find of Density Peaks (CFSFDP) with Polarimetric Decomposition

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 364 ◽  
Author(s):  
Hao Wu ◽  
Bo Pang ◽  
Dahai Dai ◽  
Jiani Wu ◽  
Xuesong Wang
Keyword(s):  
Decomposition Methods ◽  
Polarization Property ◽  
Geometrical Structures ◽  
Fast Search ◽  
Vehicle Recognition ◽  
Radar Images ◽  
Density Peaks ◽  
Aerial Vehicle ◽  
Polarization Characteristics

Unmanned aerial vehicles (UAV) have become vital targets in civilian and military fields. However, the polarization characteristics are rarely studied. This paper studies the polarization property of UAVs via the fusion of three polarimetric decomposition methods. A novel algorithm is presented to classify and recognize UAVs automatically which includes a clustering method proposed in “Science”, one of the top journals in academia. Firstly, the selection of the imaging algorithm ensures the quality of the radar images. Secondly, local geometrical structures of UAVs can be extracted based on Pauli, Krogager, and Cameron polarimetric decomposition. Finally, the proposed algorithm with clustering by fast search and find of density peaks (CFSFDP) has been demonstrated to be better than the original methods under the various noise conditions with the fusion of three polarimetric decomposition methods.

scholarly journals A Novel Semi-Supervised Learning Method Based on Fast Search and Density Peaks

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-23 ◽  
Author(s):  
Fei Gao ◽  
Teng Huang ◽  
Jinping Sun ◽  
Amir Hussain ◽  
Erfu Yang ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Recognition Performance ◽  
Learning Method ◽  
Fisher Discriminant Analysis ◽  
Learning Methods ◽  
Density Peak ◽  
Fast Search ◽  
Radar Images ◽  
Density Peaks ◽  
Major Interest

Radar image recognition is a hotspot in the field of remote sensing. Under the condition of sufficiently labeled samples, recognition algorithms can achieve good classification results. However, labeled samples are scarce and costly to obtain. Our major interest in this paper is how to use these unlabeled samples to improve the performance of a recognition algorithm in the case of limited labeled samples. This is a semi-supervised learning problem. However, unlike the existing semi-supervised learning methods, we do not use unlabeled samples directly and, instead, look for safe and reliable unlabeled samples before using them. In this paper, two new semi-supervised learning methods are proposed: a semi-supervised learning method based on fast search and density peaks (S2DP) and an iterative S2DP method (IS2DP). When the labeled samples satisfy a certain requirement, S2DP uses fast search and a density peak clustering method to detect reliable unlabeled samples based on the weighted kernel Fisher discriminant analysis (WKFDA). Then, a labeling method based on clustering information (LCI) is designed to label the unlabeled samples. When the labeled samples are insufficient, IS2DP is used to iteratively search for reliable unlabeled samples for semi-supervision. Then, these samples are added to the labeled samples to improve the recognition performance of S2DP. In the experiments, real radar images are used to verify the performance of our proposed algorithm in dealing with the scarcity of the labeled samples. In addition, our algorithm is compared against several semi-supervised deep learning methods with similar structures. Experimental results demonstrate that the proposed algorithm has better stability than these methods.

Study of the route correction system for the on-board navigation system of an unmanned aerial vehicle on the grounds of radar images of the terrain

2020 ◽  
pp. 129-134
Keyword(s):  
Predictive Model ◽  
Unmanned Aerial Vehicle ◽  
Predictive Models ◽  
Navigation System ◽  
Error Compensation ◽  
Compensation Scheme ◽  
Radar Images ◽  
Aerial Vehicle ◽  
System Errors ◽  
Correction System

The system of route correction of an unmanned aerial vehicle (UAV) is considered. For the route correction the on-board radar complex is used. In conditions of active interference, it is impossible to use radar images for the route correction so it is proposed to use the on-board navigation system with algorithmic correction. An error compensation scheme of the navigation system in the output signal using the algorithm for constructing a predictive model of the system errors is applied. The predictive model is building using the genetic algorithm and the method of group accounting of arguments. The quality comparison of the algorithms for constructing predictive models is carried out using mathematical modeling.

scholarly journals THE POWER LINE HEIGHT ANALYSIS CHART DRAWING BASE ON MAPMATRIX

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 327-333
Author(s):  
Y. R. He ◽  
W. W. Ma ◽  
X. R. Wang ◽  
J. Q. Dai ◽  
J. L. Zheng
Keyword(s):  
Point Cloud ◽  
Remote Sensing Data ◽  
Field Investigation ◽  
Power Line ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Aerial Vehicle

Abstract. The power patrol has been completed by manual field investigation, which is inefficient, costly and unsafe. In order to extract the height of the power line and its surrounding ground objects more quickly and conveniently, and better service for power line patrol. This paper uses remote sensing data of unmanned aerial vehicle to carry out aerial triangulation, stereo model establishment and binocular stereo vision height extraction base on MapMatrix software, then obtains the power line height analysis chart. Then LiDAR point cloud data is used to verify the accuracy of the power line height analysis chart. The results show that this method not only meets the standard of power line patrol, but also improves the efficiency and quality of power line patrol.

scholarly journals Digital surveying and 3D modelling structural shape pipelines for instability monitoring in historical buildings: a strategy of versatile mesh models for ruined and endangered heritage

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 84
Author(s):  
Raffaella De Marco ◽  
Sandro Parrinello
Keyword(s):  
Laser Scanner ◽  
Structural Behaviour ◽  
Structural Shape ◽  
Built Heritage ◽  
Levels Of Detail ◽  
Aerial Vehicle ◽  
The Church ◽  
Mesh Models

Cultural heritage and the attendant variety of built heritage demands a scientific approach from European committees: one related to the difficulties in its protection and management. This is primarily due to the lack of emergency protocols related to the structural knowledge and documentation pertaining to architecture and its ruins, specifically in terms of the goals of protection and intervention for endangered heritage affected by mechanical instabilities. Here, we focus on a rapid and reliable structural documentation pipeline for application to historical built heritage, and we introduce a case study of the Church of the Annunciation in Pokcha, Russia, while we also review the incorporation of integrated 3D survey products into reality-based models. This practice increases the possibility of systematising data through methodological phases and controlling the quality of numerical components into 3D polygonal meshes, with millimetric levels of detail and triangulation through the integration of terrestrial laser scanner and unmanned aerial vehicle survey data. These models are aimed at emphasising morphological qualities related to structural behaviour, thus highlighting areas of deformation and instability of the architectural system for analysis via computational platforms in view of obtaining information related to tensional behaviour and emergency risks.

scholarly journals Improving V2X-6G network capacity using a new UAV-based approach in a Cloud/ICN architecture, case Study: VANET network

2021 ◽  
Vol 297 ◽  
pp. 01019
Author(s):  
Abdeslam Houari ◽  
Tomader Mazri
Keyword(s):  
Mobile Networks ◽  
Network Capacity ◽  
Intelligent Environment ◽  
New Approach ◽  
The Road ◽  
Road Users ◽  
Aerial Vehicle ◽  
On The Road

6G of mobile networks plays a crucial role in improving the capacity and enhancing the quality of services of Vehicle-to-Everything (V2X) based networks evolving in an intelligent environment. VANET is a promising project in the intelligent transportation field using V2X communications. The emergence of several 5G and 6G technologies has raised several challenges for scientists and researchers to allow vehicles and road users to enjoy several services while ensuring their safety on the road. Among these technologies, the unmanned aerial vehicle (UAV), which can perform different tasks for road users and vehicle drivers such as data caching, packet relaying and processing. In this article, we present a new approach based on 6G Unmanned Aerial Vehicles (UAV) technology on a vehicular cloud architecture while exploiting the exchange support of information-centric networking (ICN) for the improvement of network capacity.

scholarly journals PPS: Energy-Aware Grid-Based Coverage Path Planning for UAVs Using Area Partitioning in the Presence of NFZs

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3742
Author(s):  
Alia Ghaddar ◽  
Ahmad Merei ◽  
Enrico Natalizio
Keyword(s):  
Minimum Energy ◽  
Energy Aware ◽  
Coverage Path Planning ◽  
Minimum Energy Consumption ◽  
Aerial Vehicle ◽  
Monitoring And Surveillance ◽  
Area Monitoring ◽  
Grid Based ◽  
Quality Of Coverage

Area monitoring and surveillance are some of the main applications for Unmanned Aerial Vehicle (UAV) networks. The scientific problem that arises from this application concerns the way the area must be covered to fulfill the mission requirements. One of the main challenges is to determine the paths for the UAVs that optimize the usage of resources while minimizing the mission time. Different approaches rely on area partitioning strategies. Depending on the size and complexity of the area to monitor, it is possible to decompose it exactly or approximately. This paper proposes a partitioning method called Parallel Partitioning along a Side (PPS). In the proposed method, grid-mapping and grid-subdivision of the area, as well as area partitioning are performed to plan the UAVs path. An extra challenge, also tackled in this work, is the presence of non-flying zones (NFZs). These zones are areas that UAVs must not cover or pass over it. The proposal is extensively evaluated, in comparison with existing approaches, to show that it enables UAVs to plan paths with minimum energy consumption, number of turns and completion time while at the same time increases the quality of coverage.

scholarly journals Active stabilization of unmanned aerial vehicle imaging platform

2020 ◽  
Vol 26 (19-20) ◽  
pp. 1791-1803 ◽  
Author(s):  
Mohit Verma ◽  
Vicente Lafarga ◽  
Mael Baron ◽  
Christophe Collette
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Vibration Isolation ◽  
Isolation System ◽  
Aerial Vehicles ◽  
Active Stabilization ◽  
Aerial Vehicle ◽  
Active Vibration ◽  
Improved Performance

The advancement in technology has seen a rapid increase in the use of unmanned aerial vehicles for various applications. These unmanned aerial vehicles are often equipped with the imaging platform like a camera. During the unmanned aerial vehicle flight, the camera is subjected to vibrations which hamper the quality of the captured images/videos. The high-frequency vibrations from the unmanned aerial vehicle are transmitted to the camera. Conventionally, passive rubber mounts are used to isolate the camera from the drone vibrations. The passive mounts are able to provide reduction in response near the resonance. However, this comes at the cost of amplification of response at the higher frequency. This article proposes an active vibration isolation system which exhibits improved performance at the higher frequencies than the conventional system. The active isolation system consists of a contact-less voice coil actuator supported by four springs. Experiments are carried out to study the effect of vibrations on the quality of images captured. The characterization of drone vibrations is also carried out by recording the acceleration during different flight modes. The performance of the proposed isolation system is experimentally validated on a real drone camera subjected to the recorded drone acceleration spectrum. The isolation system is found to perform better than the conventional rubber mounts and is able to reduce the vibrations to a factor of one-fourth. It can be effectively used to improve the image acquisition quality of the unmanned aerial vehicles.

scholarly journals Validation Methods of Geometric 3D-CityGML Data for Urban Wind Simulations

2019 ◽  
Vol 128 ◽  
pp. 10006 ◽  
Author(s):  
Younis Saida Saeedrashed ◽  
Ali Cemal Benim
Keyword(s):  
Healing Process ◽  
Flow Simulation ◽  
Software Tools ◽  
Geometrical Structures ◽  
Geometric Data ◽  
3D City Model ◽  
City Model ◽  
Closed Shells

Validation of the geometric data such as 3D city model is quite crucial for simulation tasks, since the simulation process strongly correlates to the quality of geometric data being meshed. Validation methodology and healing of the 3D city models using different tools are presented. The most common inherited geometrical errors are checked and analyzed. Accordingly, an appropriate healing process to the case study is performed, which illustrates that the required closed solids and closed shells are obtained within the geometrical structures of the 3D city model being processed. Also, in this paper we compare some related open source and commercial software tools for the validation and healing process. It is noticed that they differ from each other in performing the required healing process. Some of them are quite good in healing specific errors, whereas not successful in healing the rest of errors. The goal of the paper is to obtain more understanding of the geometric validation and healing capabilities of various software tools, and the qualities of generated meshes, to lead to more effective and reliable simulations in the field of urban wind flow simulation.

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