A New Approach to Estimate True Position of Unmanned Aerial Vehicles in an INS/GPS Integration System in GPS Spoofing Attack Conditions
文献类型：期刊论文
| 作者 | Mohammad Majidi3; Alireza Erfanian2; Hamid Khaloozadeh1 |
| 刊名 | International Journal of Automation and Computing
 |
| 出版日期 | 2018 |
| 卷号 | 15期号:6页码:747-760 |
| 关键词 | Inertial navigation system (INS)/global positioning system (GPS) integration unmanned aerial vehicles (UAVs) position estimation spoofing particle based filters. |
| ISSN号 | 1476-8186 |
| DOI | 10.1007/s11633-018-1137-8 |
| 英文摘要 | This paper presents a new approach to estimate the true position of an unmanned aerial vehicle (UAV) in the conditions of spoofing attacks on global positioning system (GPS) receivers. This approach consists of two phases, the spoofing detection phase which is accomplished by hypothesis test and the trajectory estimation phase which is carried out by applying the adapted particle filters to the integrated inertial navigation system (INS) and GPS. Due to nonlinearity and unfavorable impacts of spoofing signals on GPS receivers, deviation in position calculation is modeled as a cumulative uniform error. This paper also presents a procedure of applying adapted particle swarm optimization filter (PSOF) to the INS/GPS integration system as an estimator to compensate spoofing attacks. Due to memory based nature of PSOF and benefits of each particle′s experiences, application of PSOF algorithm in the INS/GPS integration system leads to more precise positioning compared with general particle filter (PF) and adaptive unscented particle filer (AUPF) in the GPS spoofing attack scenarios. Simulation results show that the adapted PSOF algorithm is more reliable and accurate in estimating the true position of UAV in the condition of spoofing attacks. The validation of the proposed method is done by root mean square error (RMSE) test. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/42449]  |
| 专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
| 作者单位 | 1.Faculty of Electrical Engineering, K.N.Toosi University of Technology, Tehran 16315-1355, Iran 2.Faculty of Electrical Engineering, Malek-Ashtar University of Technology, Tehran 15875-1774, Iran 3.Department of Electrical Engineering, Malek-Ashtar University of Technology, Tehran 15875-1774, Iran |
| 推荐引用方式 GB/T 7714 | Mohammad Majidi,Alireza Erfanian,Hamid Khaloozadeh. A New Approach to Estimate True Position of Unmanned Aerial Vehicles in an INS/GPS Integration System in GPS Spoofing Attack Conditions[J]. International Journal of Automation and Computing,2018,15(6):747-760. |
| APA | Mohammad Majidi,Alireza Erfanian,&Hamid Khaloozadeh.(2018).A New Approach to Estimate True Position of Unmanned Aerial Vehicles in an INS/GPS Integration System in GPS Spoofing Attack Conditions.International Journal of Automation and Computing,15(6),747-760. |
| MLA | Mohammad Majidi,et al."A New Approach to Estimate True Position of Unmanned Aerial Vehicles in an INS/GPS Integration System in GPS Spoofing Attack Conditions".International Journal of Automation and Computing 15.6(2018):747-760. |
入库方式： OAI收割
来源：自动化研究所
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