scholarly journals Complex processing of signals of integrated unmanned aerial vehicles surveillance system with the use of target designation

Radiotekhnika ◽  
2020 ◽  
pp. 148-161
Author(s):  
V.М. Kartashov ◽  
V.M. Oleinikov ◽  
V.I. Leonidov ◽  
V.V. Voronin ◽  
A.I. Kapusta ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Surveillance System ◽  
Low Cost ◽  
Integrated System ◽  
Potential Threat ◽  
Technical Problems ◽  
Aerial Vehicles ◽  
Wide Range ◽  
Target Designation ◽  
The Impact

One of the urgent scientific and technical problems of our time is the development of methods and means of protecting various objects against the impact of unmanned aerial vehicles (UAVs) which carry a significant potential threat to various areas of human activity – military, economic and everyday life. Significant technical capabilities, a wide range and relatively low cost of UAVs, combined with the difficulties of their observation and control, are the main features of this problem. Currently, radar, acoustic, optical and infrared methods with the appropriate facilities are widely used to detect and observe unmanned aerial vehicles. The article discusses the information capabilities of each of the methods and tools that are a part of an integrated system for detecting, measuring coordinates and parameters of UAV motion. It is shown that the radar method has the best search capabilities, while optical, infrared and acoustic methods are inferior to it. An algorithm for sequential connection of information resources available in an integrated system is discussed, taking into account the availability of search capabilities of the relevant means. New effective methods of complex processing of multimodal signals and images in a complex integrated surveillance system for unmanned aerial vehicles, built taking into account the natural spatial separation of various information channels and using target designation, have been synthesized. The features of combining multimodal information with the use of neural network technologies when using target designations in an integrated system are shown.

scholarly journals Methods for detection-recognition of radar, acoustic, optical and infrared signals of unmanned aerial vehicles

Radiotekhnika ◽  
2021 ◽  
pp. 138-153
Author(s):  
V.M. Kartashov ◽  
V.A. Pososhenko ◽  
V.V. Voronin ◽  
V.I. Kolesnik ◽  
A.I. Kapusta ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Energy Detection ◽  
Potential Threat ◽  
Aerial Vehicles ◽  
Intelligent Analysis ◽  
Number Of Publications ◽  
Measurement Of Coordinates ◽  
The Military ◽  
The Impact ◽  
Physical Principles

The protection of various objects against the impact of unmanned aerial vehicles (UAVs), which carry a potential threat in the military, economic and everyday areas of human activity, is one of the urgent tasks of our time. Currently, there are a large number of publications devoted to the description of methods and systems based on different physical principles designed to detect and observe UAVs against the background of existing interference. They consider the reception channels, methods of processing the received information signals and their subsequent intelligent analysis. It is shown, that the known methods of energy detection of UAV signals are insufficiently effective, since the operation is performed, as a rule, against a background of noise that has certain structural similarities with the UAV signal. Considerable attention is paid to the methods for interpreting the obtained data using trained neural networks. Since the number of publications in this area is constantly increasing, the task of analyzing, generalizing and systematizing the data available in the literature is relevant in accordance with this. The article is an overview and it is devoted to the generalization and systematization of known methods of receiving and processing radar, acoustic, optical and infrared signals for detection-recognition, measurement of coordinates and parameters of UAV movement.

scholarly journals Detection of unmanned aerial vehicle using radio wave scatter on acoustic disturbances of the environment created by aircraft

Radiotekhnika ◽  
2021 ◽  
pp. 122-130
Author(s):  
V.M. Kartashov ◽  
O.I. Kharchenko ◽  
V.A. Pososhenko ◽  
V.I. Kolesnik ◽  
A.B. Yegorov ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Technical Problem ◽  
Technical Problems ◽  
Acoustic Disturbances ◽  
Aerial Vehicles ◽  
Wide Range ◽  
Radio Signals ◽  
Range Of Functions ◽  
Aerial Vehicle

Unmanned aerial vehicles (UAVs) have recently become widespread, because they are capable of performing a wide range of functions useful for mankind. At the same time, UAVs are a source of potential threats in a number of areas of human activity, namely, military, economic, and everyday life. Therefore, an urgent scientific and technical problem of detecting and observing UAVs has been formed recently to prevent them from performing unauthorized actions. The main means of UAV surveillance are radar (both active and passive), optical, infrared, acoustic stations, as well as complex systems in which joint processing of information obtained using these information channels is carried out. However, in general, the scientific and technical problem of monitoring UAVs, especially small UAVs, remains unresolved: the efficiency of UAV detection using all these methods remains insufficient, and the needs of practice are far from being fully satisfied with the available means. This article is devoted to the analysis of currently known scientific and practical results aimed to assess the possibility of detecting UAVs by radio signals scattered by acoustic disturbances of the environment created by UAVs, and to formulate urgent scientific and technical problems in this aria of knowledge.

scholarly journals Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3338
Author(s):  
Ivan Vajs ◽  
Dejan Drajic ◽  
Nenad Gligoric ◽  
Ilija Radovanovic ◽  
Ivan Popovic
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Relative Humidity ◽  
Low Cost ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Lower Accuracy ◽  
Wide Range ◽  
The Impact ◽  
Monitoring Stations

Existing government air quality monitoring networks consist of static measurement stations, which are highly reliable and accurately measure a wide range of air pollutants, but they are very large, expensive and require significant amounts of maintenance. As a promising solution, low-cost sensors are being introduced as complementary, air quality monitoring stations. These sensors are, however, not reliable due to the lower accuracy, short life cycle and corresponding calibration issues. Recent studies have shown that low-cost sensors are affected by relative humidity and temperature. In this paper, we explore methods to additionally improve the calibration algorithms with the aim to increase the measurement accuracy considering the impact of temperature and humidity on the readings, by using machine learning. A detailed comparative analysis of linear regression, artificial neural network and random forest algorithms are presented, analyzing their performance on the measurements of CO, NO2 and PM10 particles, with promising results and an achieved R2 of 0.93–0.97, 0.82–0.94 and 0.73–0.89 dependent on the observed period of the year, respectively, for each pollutant. A comprehensive analysis and recommendations on how low-cost sensors could be used as complementary monitoring stations to the reference ones, to increase spatial and temporal measurement resolution, is provided.

scholarly journals Enhanced Particle Swarm Optimization for Path Planning of Unmanned Aerial Vehicles

2020 ◽  
Vol 14 (1) ◽  
pp. 67-78
Author(s):  
Kai Yit Kok ◽  
Parvathy Rajendran
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Aerial Vehicles ◽  
Trial And Error Method ◽  
The Impact ◽  
Enhanced Particle Swarm Optimization ◽  
Error Method

This paper presents an enhanced particle swarm optimization (PSO) for the path planning of unmanned aerial vehicles (UAVs). An evolutionary algorithm such as PSO is costly because every application requires different parameter settings to maximize the performance of the analyzed parameters. People generally use the trial-and-error method or refer to the recommended setting from general problems. The former is time consuming, while the latter is usually not the optimum setting for various specific applications. Hence, this study focuses on analyzing the impact of input parameters on the PSO performance in UAV path planning using various complex terrain maps with adequate repetitions to solve the tuning issue. Results show that inertial weight parameter is insignificant, and a 1.4 acceleration coefficient is optimum for UAV path planning. In addition, the population size between 40 and 60 seems to be the optimum setting based on the case studies.

scholarly journals Eyes in the Sky: Assessing the Feasibility of Low-Cost, Ready-to-Use Unmanned Aerial Vehicles to Monitor Primate Populations Directly

2019 ◽  
Vol 91 (1) ◽  
pp. 69-82
Author(s):  
Brandon P. Semel ◽  
Sarah M. Karpanty ◽  
Faramalala Francette Vololonirina ◽  
Ando Nantenaina Rakotonanahary
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Low Cost ◽  
Aerial Vehicles

scholarly journals Model-Based Autonomous Navigation with Moment of Inertia Estimation for Unmanned Aerial Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2467 ◽  
Author(s):  
Hery Mwenegoha ◽  
Terry Moore ◽  
James Pinchin ◽  
Mark Jabbal
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Navigation System ◽  
Process Model ◽  
Unscented Kalman Filter ◽  
Low Cost ◽  
Moment Of Inertia ◽  
Model Parameters ◽  
Main Process ◽  
Model Based ◽  
Aerial Vehicles

The dominant navigation system for low-cost, mass-market Unmanned Aerial Vehicles (UAVs) is based on an Inertial Navigation System (INS) coupled with a Global Navigation Satellite System (GNSS). However, problems tend to arise during periods of GNSS outage where the navigation solution degrades rapidly. Therefore, this paper details a model-based integration approach for fixed wing UAVs, using the Vehicle Dynamics Model (VDM) as the main process model aided by low-cost Micro-Electro-Mechanical Systems (MEMS) inertial sensors and GNSS measurements with moment of inertia calibration using an Unscented Kalman Filter (UKF). Results show that the position error does not exceed 14.5 m in all directions after 140 s of GNSS outage. Roll and pitch errors are bounded to 0.06 degrees and the error in yaw grows slowly to 0.65 degrees after 140 s of GNSS outage. The filter is able to estimate model parameters and even the moment of inertia terms even with significant coupling between them. Pitch and yaw moment coefficient terms present significant cross coupling while roll moment terms seem to be decorrelated from all of the other terms, whilst more dynamic manoeuvres could help to improve the overall observability of the parameters.

scholarly journals Frontier Progress of Unmanned Aerial Vehicles Optical Wireless Technologies

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5476
Author(s):  
Jupeng Ding ◽  
Hongye Mei ◽  
Chih-Lin I ◽  
Hui Zhang ◽  
Wenwen Liu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Transmission Rate ◽  
Experimental Testing ◽  
High Reliability ◽  
Communication Link ◽  
Optical Wireless ◽  
Wireless Technology ◽  
Technical Problems ◽  
Practical Applications ◽  
Aerial Vehicles

With the continuous maturity of unmanned aerial vehicles (UAV) in materials, communications, and other related technologies, the UAV industry has developed rapidly in recent years. In order to cope with the diversified emerging business forms, the explosive growth of the scale of data traffic, number of terminal connections, high reliability, low-latency, and high transmission rate provided by the fifth generation (5G) network will inject new vitality into the development of the UAVs industry. In this paper, optical wireless technology is introduced into the UAV platform, combining theory with practical applications. We explain many research advances and key technologies in the four aspects of “air, space, earth, and sea” to achieve a strong and broadband communication link. This discussion focuses on link modeling, parameter optimization, experimental testing, and the status quo of UAVs in different application scenarios with optical wireless link configurations. At the same time, based on the current situation of UAV optical wireless technology, the technical problems and the research direction in the future are also discussed.

scholarly journals Accurate Landing of Unmanned Aerial Vehicles Using Ground Pattern Recognition

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1532 ◽  
Author(s):  
Jamie Wubben ◽  
Francisco Fabra ◽  
Carlos T. Calafate ◽  
Tomasz Krzeszowski ◽  
Johann M. Marquez-Barja ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Unmanned Aerial Vehicles ◽  
High Precision ◽  
Low Cost ◽  
Target Position ◽  
Flight Behavior ◽  
Ground Pattern ◽  
Aerial Vehicles ◽  
Exact Position ◽  
Precision Landing

Over the last few years, several researchers have been developing protocols and applications in order to autonomously land unmanned aerial vehicles (UAVs). However, most of the proposed protocols rely on expensive equipment or do not satisfy the high precision needs of some UAV applications such as package retrieval and delivery or the compact landing of UAV swarms. Therefore, in this work, a solution for high precision landing based on the use of ArUco markers is presented. In the proposed solution, a UAV equipped with a low-cost camera is able to detect ArUco markers sized 56 × 56 cm from an altitude of up to 30 m. Once the marker is detected, the UAV changes its flight behavior in order to land on the exact position where the marker is located. The proposal was evaluated and validated using both the ArduSim simulation platform and real UAV flights. The results show an average offset of only 11 cm from the target position, which vastly improves the landing accuracy compared to the traditional GPS-based landing, which typically deviates from the intended target by 1 to 3 m.

scholarly journals Internet of Unmanned Aerial Vehicles—A Multilayer Low-Altitude Airspace Model for Distributed UAV Traffic Management

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4779 ◽  
Author(s):  
Nader S. Labib ◽  
Grégoire Danoy ◽  
Jedrzej Musial ◽  
Matthias R. Brust ◽  
Pascal Bouvry
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Traffic Management ◽  
Complex Problem ◽  
Experimental Simulation ◽  
Aerial Vehicles ◽  
Safe Management ◽  
Wide Range ◽  
Abstract Level ◽  
Low Altitude ◽  
New Research

The rapid adoption of Internet of Things (IoT) has encouraged the integration of new connected devices such as Unmanned Aerial Vehicles (UAVs) to the ubiquitous network. UAVs promise a pragmatic solution to the limitations of existing terrestrial IoT infrastructure as well as bring new means of delivering IoT services through a wide range of applications. Owning to their potential, UAVs are expected to soon dominate the low-altitude airspace over populated cities. This introduces new research challenges such as the safe management of UAVs operation under high traffic demands. This paper proposes a novel way of structuring the uncontrolled, low-altitude airspace, with the aim of addressing the complex problem of UAV traffic management at an abstract level. The work, hence, introduces a model of the airspace as a weighted multilayer network of nodes and airways and presents a set of experimental simulation results using three UAV traffic management heuristics.

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