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Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration 被引量:1
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作者 Lujuan Dang Badong Chen +2 位作者 Yulong Huang Yonggang Zhang Haiquan Zhao 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2022年第3期450-465,共16页
Traditional cubature Kalman filter(CKF)is a preferable tool for the inertial navigation system(INS)/global positioning system(GPS)integration under Gaussian noises.The CKF,however,may provide a significantly biased es... Traditional cubature Kalman filter(CKF)is a preferable tool for the inertial navigation system(INS)/global positioning system(GPS)integration under Gaussian noises.The CKF,however,may provide a significantly biased estimate when the INS/GPS system suffers from complex non-Gaussian disturbances.To address this issue,a robust nonlinear Kalman filter referred to as cubature Kalman filter under minimum error entropy with fiducial points(MEEF-CKF)is proposed.The MEEF-CKF behaves a strong robustness against complex nonGaussian noises by operating several major steps,i.e.,regression model construction,robust state estimation and free parameters optimization.More concretely,a regression model is constructed with the consideration of residual error caused by linearizing a nonlinear function at the first step.The MEEF-CKF is then developed by solving an optimization problem based on minimum error entropy with fiducial points(MEEF)under the framework of the regression model.In the MEEF-CKF,a novel optimization approach is provided for the purpose of determining free parameters adaptively.In addition,the computational complexity and convergence analyses of the MEEF-CKF are conducted for demonstrating the calculational burden and convergence characteristic.The enhanced robustness of the MEEF-CKF is demonstrated by Monte Carlo simulations on the application of a target tracking with INS/GPS integration under complex nonGaussian noises. 展开更多
关键词 Cubature Kalman filter(CKF) inertial navigation system(ins)/global positioning system(GPS)integration minimum error entropy with fiducial points(MEEF) non-Gaussian noise
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A New Approach to Estimate True Position of Unmanned Aerial Vehicles in an INS/GPS Integration System in GPS Spoofing Attack Conditions 被引量:5
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作者 Mohammad Majidi Alireza Erfanian Hamid Khaloozadeh 《International Journal of Automation and computing》 EI CSCD 2018年第6期747-760,共14页
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 tw... 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 integ- ration 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 estim- ating 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. 展开更多
关键词 Inertial navigation system ins)/global positioning system (GPS) integration unmanned aerial vehicles (UAVs) position estimation SPOOFING particle based filters
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IMU/GPS数据同步电路的研究与实现 被引量:3
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作者 刘广孚 张为公 +1 位作者 李旭 郭亮 《仪器仪表学报》 EI CAS CSCD 北大核心 2006年第z2期1353-1354,共2页
数据同步是INS/GPS组合导航中数据融合的重要前提。对IMU/GPS组合系统中的数据同步技术进行研究,在IMU没有同步脉冲的情况下,提出了一种以GPS的1PPS(秒同步脉冲信号)为参考时标,由CPLD和8253实现的数据同步方法。实验证明了方案的设... 数据同步是INS/GPS组合导航中数据融合的重要前提。对IMU/GPS组合系统中的数据同步技术进行研究,在IMU没有同步脉冲的情况下,提出了一种以GPS的1PPS(秒同步脉冲信号)为参考时标,由CPLD和8253实现的数据同步方法。实验证明了方案的设计是成功的。 展开更多
关键词 惯性导航系统 全球定位系统 惯性测量单元 数据同步 8253计数器 CPLD
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