• Title/Summary/Keyword: High-Performance UAV

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Complex Field Network Coding with MPSK Modulation for High Throughput in UAV Networks

  • Mingfei Zhao;Rui Xue
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.8
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    • pp.2281-2297
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    • 2024
  • Employing multiple drones as a swarm to complete missions can sharply improve the working efficiency and expand the scope of investigation. Remote UAV swarms utilize satellites as relays to forward investigation information. The increasing amount of data demands higher transmission rate and complex field network coding (CFNC) is deemed as an effective solution for data return. CFNC applied to UAV swarms enhances transmission efficiency by occupying only two time slots, which is less than other network coding schemes. However, conventional CFNC applied to UAVs is combined with constant coding and modulation scheme and results in a waste of spectrum resource when the channel conditions are better. In order to avoid the waste of power resources of the relay satellite and further improve spectral efficiency, a CFNC transmission scheme with MPSK modulation is proposed in this paper. For the proposed scheme, the satellite relay no longer directly forwards information, but transmits information after processing according to the current channel state. The proposed transmission scheme not only maintains throughput advantage of CFNC, but also enhances spectral efficiency, which obtains higher throughput performance. The symbol error probability (SEP) and throughput results corroborated by Monte Carlo simulation show that the proposed transmission scheme improves spectral efficiency in multiples compared to the conventional CFNC schemes. In addition, the proposed transmission scheme enhances the throughput performance for different topology structures while keeping SEP below a certain value.

Improving Field Crop Classification Accuracy Using GLCM and SVM with UAV-Acquired Images

  • Seung-Hwan Go;Jong-Hwa Park
    • Korean Journal of Remote Sensing
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    • v.40 no.1
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    • pp.93-101
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    • 2024
  • Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

A Study on vertical mode system identification for a single tilt wing UAV (단일 틸트윙 방식 무인기의 수직모드 시스템 식별 기법 연구)

  • Seo, Ilwon;Kim, Seungkeun;Suk, Jinyoung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.42 no.11
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    • pp.937-946
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    • 2014
  • This paper presents system identification of a single tilt wing UAV. A Modified Equation Error Method(MEEM) and Extended Kalman Filter(EKF) are used for the identification of a single tilt wing UAV system in frequency-domain and time-domain, respectively. Simulated flight data is obtained from CNUX-3's vertical mode linear simulation with realistic sensor noise. System identification performance is analyzed with respect to a variety of design parameters of the MEEM. Also, High accuracy Fourier Transform(HFT) is applied to enhance the performance of MEEM. The results of the MEEM is compared with those of the EKF. Design parameters of the MEEM and initial conditions of the EKF are decided from optimization.

A Study on Trend Monitoring of a Long Endurance UAV s Gas Turbine to be Operated at Medium High Altitude

  • Kho, Seong-Hee;Ki, Ja-Young;Kong, Chang-Duk;Oh, Seong-Hwan;Kim, Ji-Hyun
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2008.03a
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    • pp.84-88
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    • 2008
  • The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results, it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

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A Review of Routing Plan for Unmanned Aerial Vehicle : Focused on In-Country Researches (국내 무인항공기의 경로계획 연구)

  • Kim, Jinwoo;Kim, Jinwook;Chae, Junjae
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.38 no.4
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    • pp.212-225
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    • 2015
  • UAV (Unmanned Aerial Vehicle), the pilotless plane or drone, draws researchers' attention at these days for its extended use to various area. The research was initiated for military use of the UAV, but the area of applicable field is extended to surveillance, communication, and even delivery for commercial use. As increasing the interest in UAV, the needs of research for operating the flying object which is not directly visible when it conducts a certain mission to remote place is obviously grown as much as developing high performance pilotless plane is required. One of the project supported by government is related to the use of UAV for logistics fields and controlling UAV to deliver the certain items to isolated or not-easy-to-access place is one of the important issues. At the initial stage of the project, the previous researches for controlling UAV need to be organized to understand current state of art in local researches. Thus, this study is one of the steps to develop the unmanned system for using in military or commercial. Specifically, we focused on reviewing the approaches of controlling UAV from origination to destination in previous in-country researches because the delivery involves the routing planning and the efficient and effective routing plan is critical to success to delivery mission using UAV. This routing plan includes the method to avoid the obstacles and reach the final destination without a crash. This research also present the classification and categorization of the papers and it could guide the researchers, who conduct researches and explore in comparable fields, to catch the current address of the research.

A Resource Scheduling Based on Iterative Sorting for Long-Distance Airborne Tactical Communication in Hub Network (허브 네트워크에서의 장거리 공중 전술 통신을 위한 반복 정렬 기반의 자원 스케줄링 기법)

  • Lee, Kyunghoon;Lee, Dong Hun;Lee, Dae-Hong;Jung, Sung-Jin;Choi, Hyung-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39C no.12
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    • pp.1250-1260
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    • 2014
  • In this paper, a novel resource scheduling, which is used for hub network based long distance airborne tactical communication, is proposed. Recently, some countries of the world has concentrated on developing data rate and networking performance of CDL, striving to keep pace with modern warfare, which is changed into NCW. And our government has also developed the next generation high capacity CDL. In hub network, a typical communication structure of CDL, hybrid FDMA/TDMA can be considered to exchange high rate data among multiple UAVs simultaneously, within limited bandwidth. However, due to different RTT and traffic size of UAV, idle time resource and unnecessary packet transmission delay can occur. And these losses can reduce entire efficiency of hub network in long distance communication. Therefore, in this paper, we propose RTT and data traffic size based UAV scheduling, which selects time/frequency resource of UAVs by using iterative sorting algorithm. The simulation results verified that the proposed scheme improves data rate and packet delay performance in low complexity.

Non-linear Control of Turbojet Engine for High Maneuverability UAV (고기동 무인항공기용 터보제트엔진의 비선형 제어)

  • Han, Dong-Ju;Oh, Seong-Hwan
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.40 no.5
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    • pp.431-438
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    • 2012
  • Non-linear turbojet engine controller with high operational performance has been designed for the high maneuverability UAV. The turbojet engine dynamic performance code has been developed to reflect the non-linear characteristics on controller design, by which the necessity of non-linear controller design was justified by investigating the limitation of linear model derived from the dynamic performance. The PI-like fuzzy controller was designed and enhanced by combining with conventional derivative control. This designed fuzzy controller proves its effectiveness by showing superior control performances over the conventional PID controller along with guaranteeing the safe operation within compressor surge, flame out and turbine temperature limits etc.

Onboard Active Vision Based Hovering Control for Quadcopter in Indoor Environments (실내 환경에서의 능동카메라 기반 쿼더콥터의 호버링 제어)

  • Jin, Tae-Seok
    • Journal of the Korean Society of Industry Convergence
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    • v.20 no.1
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    • pp.19-26
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    • 2017
  • In this paper, we describe the design and performance of UAV system toward compact and fully autonomous quadrotors, where they can complete logistics application, rescue work, inspection tour and remote sensing without external assistance systems like ground station computers, high-performance wireless communication devices or motion capture system. we propose high-speed hovering flyght height control method based on state feedback control with image information from active camera and multirate observer because we can get image of the information only every 30ms. Finally, we show the advantages of proposed method by simulations and experiments.

Aerodynamic Design of the Solar-Powered High Altitude Long Endurance (HALE) Unmanned Aerial Vehicle (UAV)

  • Hwang, Seung-Jae;Kim, Sang-Gon;Kim, Cheol-Won;Lee, Yung-Gyo
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.1
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    • pp.132-138
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    • 2016
  • Korea Aerospace Research Institute (KARI) is developing an electric-driven HALE UAV in order to secure system and operational technologies since 2010. Based on the flight tests and design experiences of the previously developed electric-driven UAVs, KARI has designed EAV-3, a solar-powered HALE UAV. EAV-3 weighs 53kg, the structure weight is 22kg, and features a flexible wing of 19.5m in span with the aspect ratio of 17.4. Designing the main wing and empennage of the EAV-3 the amount of the bending due to the flexible wing, 404mm at 1-G flight condition based on T-800 composite material, and side wind effects due to low cruise speed, $V_{cr}=6m/sec$, are carefully considered. Also, unlike the general aircraft there is no center of gravity shift during the flight because of the EAV-3 is the solar-electric driven UAV. Thus, static margin cuts down to 28.4% and center of gravity moves back to 31% of the Mean Aerodynamic Chord (MAC) comparing with the previously designed the EAV-2 and EAV-2H/2H+ to upgrade the flight performance of the EAV-3.

Trend Monitoring of A Turbofan Engine for Long Endurance UAV Using Fuzzy Logic

  • Kong, Chang-Duk;Ki, Ja-Young;Oh, Seong-Hwan;Kim, Ji-Hyun
    • International Journal of Aeronautical and Space Sciences
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    • v.9 no.2
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    • pp.64-70
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    • 2008
  • The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results. it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.