防止恶意无人机入侵电力巡检区的管控方法

doi:10.11959/j.issn.2096-109x.2018052

Abstract

Abstract:

In recent years,the exploitation and deployment of UAV (unmanned aerial vehicle) has grown rapidly.The number of UAV is increasing and it is becoming more and more important in many areas.For example,the power inspection method has be upgraded from the original manual inspection to unmanned intelligent inspection.However,malicious UAV intrude on the power patrol work area and also bring about safety problems to the power plant's production.Because the electronic fence technology (geo-fencing) lacks the real time and flexibility when it controls the UAV,a novel control method to prevent malicious UAV from invading the power inspection area is proposed.The experimental results demonstrate the effectivity of our proposed method.

Key words: power plant, power inspection, UAV control area, geo-fencing, avoidance

CLC Number:

TP309.1

Peng WANG,Xiaolong HAO,Yaokang ZHU,Guang YANG,Yang CUI,Qiwei PENG,Daojing HE. Control method to prevent malicious UAV intrusion into electricity inspection area[J]. Chinese Journal of Network and Information Security, 2018, 4(6): 70-76.

Figures/Tables 12

References 19

[1]	DU B Q , LIU S Z . A common obstacle avoidance module based on fuzzy algorithm for unmanned aerial vehicle[C]// IEEE International Conference on Cyber Technology in Automation,Control,and Intelligent Systems (CYBER). 2016.
[2]	ILLE M , NAMERIKAWA T . Collision avoidance between multi-UAV-systems considering formation control using MPC[C]// IEEE International Conference on Advanced Intelligent Mechatronics. 2017: 651-656.
[3]	GURRIET T , CIARLETTA L . Towards a generic and modular geofencing strategy for civilian UAV[C]// International Conference on Unmanned Aircraft Systems. 2016: 540-549.
[4]	WANG E , . Identification of flight safety zones for unmanned aerial systems using geo-fencing data provided by prebuilt maps[C]// The 11th International Microsystems,Packaging,Assembly and Circuits Technology Conference (IMPACT). 2016.
[5]	QIU Q , CAO L , FANG J Y . Comparative study of parallel point-in-polygon algorithm in dynamic scheduling and static scheduling[J]. Geography and Geo-Information Science, 2013.
[6]	FARLIK J , KRATKY M , CASAR J ,et al. Radar cross section and detection of small unmanned aerial vehicles[C]// International Conference on Mechatronics- Mechatronika. 2017.
[7]	KLARE J , BIALLAWONS O , CERUTTI-MAORI D . Detection of UAV using the MIMO radar MIRA-CLE Ka[C]// European Conference on Synthetic Aperture Radar. 2016.
[8]	PENG X Z , LIN H Y , DAI J M . Path planning and obstacle avoidance for vision guided quadrotor UAV navigation[C]// IEEE International Conference on Control and Automation. 2016: 984-989.
[9]	MOSES A , RUTHERFORD M J , VALAVANIS K P . Radar-based detection and identification for miniature air vehicles[C]// IEEE International Conference on Control Applications. 2011: 933-940.
[10]	PRATYUSHA P L , NAIDU V P S . Geo-fencing for unmanned aerial vehicle[J]. International Journal of Computer Applications, 2013.
[11]	BAI G , XIANG X , ZHU H ,et al. Research on obstacles avoidance technology for UAV based on improved PTAM algorithm[C]// IEEE International Conference on Progress in Informatics and Computing. 2016: 543-550.
[12]	ZHANG X L . Key issues in electricity inspection under the new situation[J]. Heilongjiang Science, 2016.
[13]	CHAUFFAUT C , DEFAY F , BURLION L ,et al. UAV obstacle avoidance scheme using an output to input saturation transformation technique[C]// International Conference on Unmanned Aircraft Systems. 2016: 227-234.
[14]	GAO X J.CHENG X F.ZHI Y . Research on environment and threat model in UAV path planning[J]. Aeronautical Computing Technique, 2013.
[15]	JAMES T . System safety modeling of alternative geofencing configurations for small UAS[J]. International Journal of Aviation,Aeronautics,and Aerospace, 2016.
[16]	QUIGLEY M , . ROS:an open-source robot operating system[C]// IEEE ICRA Workshop on Open Source Robotics. 2009.
[17]	CAO W , XU S . A workflow based multi-UAV cooperation architecture[C]// International Conference on Information Management. 2017: 496-499.
[18]	SHARMA R , GHOSE D . Swarm intelligence based collision avoidance between realistically modelled UAV clusters[C]// IEEE American Control Conference. 2007: 3892-3897.
[19]	RIISGARD S . SLAM for dummies-a tutorial approach to simultaneous localization and mapping[J]. Journal of the Marine Biological Association of the United Kingdom, 2000,(4): 699-705.

Metrics

Recommended 0

No Suggested Reading articles found!

Control method to prevent malicious UAV intrusion into electricity inspection area

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 12

References 19

Related Articles 4

Metrics

Recommended 0

[1]	Xunxun CHEN, Mingzhe LI, Ning LYU, Liang HUANG. Intrinsic assurance: a systematic approach towards extensible cybersecurity [J]. Chinese Journal of Network and Information Security, 2023, 9(1): 92-102.
[2]	Wenfu LIU, Jianmin PANG, Xin ZHOU, Nan LI, Feng YUE. Research on network risk assessment based on attack graph of expected benefits-rate [J]. Chinese Journal of Network and Information Security, 2022, 8(4): 87-97.
[3]	Aiqun HU, Lanting FANG, Tao LI. Research on bionic mechanism based endogenous security defense system [J]. Chinese Journal of Network and Information Security, 2021, 7(1): 11-19.
[4]	San DU,Hui SHU,Fei KANG. Design and implementation of hardware-based dynamic instruction set randomization framework [J]. Chinese Journal of Network and Information Security, 2017, 3(11): 29-39.