scholarly journals Analysis of Assembly Error Effect on Stability Accuracy of Unmanned Aerial Vehicle Photoelectric Detection System

2020 ◽  
Vol 10 (7) ◽  
pp. 2311
Author(s):  
Keyan He ◽  
Huajie Hong ◽  
Guilin Jiang ◽  
Haipeng Gu
Keyword(s):  
Manufacturing Process ◽  
Detection System ◽  
Analysis Method ◽  
Process Improvements ◽  
Deviation Analysis ◽  
Photoelectric Detection ◽  
Key Performance Index ◽  
Typical Type ◽  
Aerial Vehicle ◽  
Assembly Error

A photoelectric detection system is a typical type of device widely used for detecting purposes based on unmanned aerial vehicles (UAV). Stability accuracy is the key performance index. Compared to traditional analysis methods aimed at unpredictable error-causing sources, assembly errors can be easily controlled during the manufacturing processes. In this research, an analysis method of assembly error effect on stability accuracy is proposed. First, by using kinematics analysis of homogeneous coordinate transformation, stability accuracy is comprehensively modeled and simulated. Then, by analyzing the manufacturing process, assembly errors of axis perpendicularities, run-outs and gyroscopes are defined and modeled. By simulating different carrier movements, the effects caused by assembly errors under various environments are studied. Finally, error sensitivity is proposed by using standard deviation analysis. Results show that the most sensitive assembly errors are identified, and ranked in order of sensitivity as follows: x-component of pitch axis perpendicularity, y-component of the azimuth gyroscope assembly, and z-component of the pitch gyroscope assembly. In conclusion, the results can be used as standards of manufacturing process improvements, and the proposed methods can be used to provide valuable references for real application scenarios.

Target infrared radiation calculation model and method based on finite element analysis method in infrared photoelectric detection system

Sensor Review ◽  
2017 ◽  
Vol 37 (1) ◽  
pp. 26-32
Author(s):  
Hanshan Li
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Infrared Radiation ◽  
Detection System ◽  
Calculation Model ◽  
Analysis Method ◽  
Element Analysis ◽  
Content Type ◽  
Finite Element Analysis Method ◽  
Photoelectric Detection

Purpose The purpose of this paper is to evaluate the detection performance of infrared photoelectric detection system and establish stable tracking platform. Design/methodology/approach This paper puts forward making use of the finite element analysis method to set up the infrared radiation characteristics calculation model of flying target in infrared photoelectric detection system; researches the target optical characteristics based on the target imaging detection theory; sets up the heat balance equation of target’s surface node and gives the calculation method of total radiation intensity of flying target; and deduces the target detection distance calculation function; studies the changed regulation of radiation energy that charge coupled device (CCD) gain comes from target surface infrared heat radiations under different sky background luminance and different target flight attitude. Findings Through calculation and experiment analysis, the results show that when the target’s surface area increases or the target flight velocity is higher, the radiation energy that CCD obtained is higher, which is advantageous to the target stable detection in infrared photoelectric detection system. Originality/value This paper uses the finite element analysis method to set up the infrared radiation characteristics calculation model of flying target and give the calculation and experiment results; those results can provide some data and improve the design method of infrared photoelectric detection system, and it is of value.

scholarly journals Design of bio-inspired binocular UAV detection system based on improved STC algorithm of scale transformation and occlusion detection

2021 ◽  
Vol 13 ◽  
pp. 175682932110048
Author(s):  
Huajun Song ◽  
Yanqi Wu ◽  
Guangbing Zhou
Keyword(s):  
Detection System ◽  
Rapid Development ◽  
Reference Value ◽  
Scale Transformation ◽  
Hardware System ◽  
Time Requirements ◽  
Aerial Vehicle ◽  
Spatio Temporal ◽  
Small Targets ◽  
Vision Detection

With the rapid development of drones, many problems have arisen, such as invasion of privacy and endangering security. Inspired by biology, in order to achieve effective detection and robust tracking of small targets such as unmanned aerial vehicles, a binocular vision detection system is designed. The system is composed of long focus and wide-angle dual cameras, servo pan tilt, and dual processors for detecting and identifying targets. In view of the shortcomings of spatio-temporal context target tracking algorithm that cannot adapt to scale transformation and easy to track failure in complex scenes, the scale filter and loss criterion are introduced to make an improvement. Qualitative and quantitative experiments show that the designed system can adapt to the scale changes and partial occlusion conditions in the detection, and meets the real-time requirements. The hardware system and algorithm both have reference value for the application of anti-unmanned aerial vehicle systems.

The Effect of Laser Focus Position on Laser Induced Plasma Characteristics

2014 ◽  
Vol 1035 ◽  
pp. 508-513
Author(s):  
Meng Ke Lu ◽  
Shu Rui Zhao ◽  
Kui Wen Guan ◽  
Yan Ling Wang
Keyword(s):  
Short Pulse ◽  
Detection System ◽  
Spectral Lines ◽  
The Self ◽  
Focus Position ◽  
Laser Induced Plasma ◽  
Photoelectric Detection ◽  
Complex Process ◽  
Laser Focus ◽  
Plasma Characteristics

Laser induced plasma is a relatively complex process which is closely related to many factors. In this paper, using a short pulse Nd:YAG laser and CCD photoelectric detection system, the variation of laser focus position effected by spectral intensity, the ratio of signal to background as well as the self-absorption of the plasma spectral lines with the standard spectra sample of aluminum for analysis samples was studied. Results show that: when the laser focus position is about 5mm under the surface of the sample, the relative intensity and the ratio of signal to background of the spectral lines are the strongest, and the spectral lines are sharp without obvious self-absorption.

Tebyan: Fake News Detection System (Preprint)

2021 ◽  
Author(s):  
Lamya Alderywsh ◽  
Aseel Aldawood ◽  
Ashwag Alasmari ◽  
Farah Aldeijy ◽  
Ghadah Alqubisy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Arab World ◽  
Detection System ◽  
Learning Algorithms ◽  
Performance Measure ◽  
Machine Learning Algorithms ◽  
Svm Classifier ◽  
Fake News ◽  
Typical Type ◽  
Performance Results

BACKGROUND There is a serious threat from fake news spreading in technologically advanced societies, including those in the Arab world, via deceptive machine-generated text. In the last decade, Arabic fake news identification has gained increased attention, and numerous detection approaches have revealed some ability to find fake news throughout various data sources. Nevertheless, many existing approaches overlook recent advancements in fake news detection, explicitly to incorporate machine learning algorithms system. OBJECTIVE Tebyan project aims to address the problem of fake news by developing a fake news detection system that employs machine learning algorithms to detect whether the news is fake or real in the context of Arab world. METHODS The project went through numerous phases using an iterative methodology to develop the system. This study analysis incorporated numerous stages using an iterative method to develop the system of misinformation and contextualize fake news regarding society's information. It consists of implementing the machine learning algorithms system using Python to collect genuine and fake news datasets. The study also assesses how information-exchanging behaviors can minimize and find the optimal source of authentication of the emergent news through system testing approaches. RESULTS The study revealed that the main deliverable of this project is the Tebyan system in the community, which allows the user to ensure the credibility of news in Arabic newspapers. It showed that the SVM classifier, on average, exhibited the highest performance results, resulting in 90% in every performance measure of sources. Moreover, the results indicate the second-best algorithm is the linear SVC since it resulted in 90% in performance measure with the societies' typical type of fake information. CONCLUSIONS The study concludes that conducting a system with machine learning algorithms using Python programming language allows the rapid measures of the users' perception to comment and rate the credibility result and subscribing to news email services.

scholarly journals GPS-Spoofing Attack Detection Technology for UAVs Based on Kullback–Leibler Divergence

Drones ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 8
Author(s):  
Elena Basan ◽  
Alexandr Basan ◽  
Alexey Nekrasov ◽  
Colin Fidge ◽  
Nikita Sushkin ◽  
...  
Keyword(s):  
Cyber Security ◽  
Detection System ◽  
Attack Detection ◽  
Abnormal Behavior ◽  
Mathematical Methods ◽  
Training Time ◽  
Detection Technology ◽  
Normal Behavior ◽  
Leibler Divergence ◽  
Aerial Vehicle

Here, we developed a method for detecting cyber security attacks aimed at spoofing the Global Positioning System (GPS) signal of an Unmanned Aerial Vehicle (UAV). Most methods for detecting UAV anomalies indicative of an attack use machine learning or other such methods that compare normal behavior with abnormal behavior. Such approaches require large amounts of data and significant “training” time to prepare and implement the system. Instead, we consider a new approach based on other mathematical methods for detecting UAV anomalies without the need to first collect a large amount of data and describe normal behavior patterns. Doing so can simplify the process of creating an anomaly detection system, which can further facilitate easier implementation of intrusion detection systems in UAVs. This article presents issues related to ensuring the information security of UAVs. Development of the GPS spoofing detection method for UAVs is then described, based on a preliminary study that made it possible to form a mathematical apparatus for solving the problem. We then explain the necessary analysis of parameters and methods of data normalization, and the analysis of the Kullback—Leibler divergence measure needed to detect anomalies in UAV systems.

Sign in / Sign up

Export Citation Format

Share Document