为解决无线网络信号在传输过程中由于受到其他信号的干扰,导致接收端接收的信号与原始信号相比存在误差的问题,该文在利用数据关联和卡尔曼滤波对信号进行融合(fusion method of signal filtering based on wavelet transform and Calma...为解决无线网络信号在传输过程中由于受到其他信号的干扰,导致接收端接收的信号与原始信号相比存在误差的问题,该文在利用数据关联和卡尔曼滤波对信号进行融合(fusion method of signal filtering based on wavelet transform and Calman,FSWC)的基础上,利用FARIMA(p,d,q)模型和数据关联来建立一种新的信号融合算法(signal fusion based on wavelet transform and date association,SFTD)。通过仿真实验分别研究融合信号与干扰距离、发送速率、容量、功率的变化情况。仿真结果表明:随着干扰距离的增加,容量开始呈现正相关趋势,直至趋于平稳,并且发送速率、容量、功率对融合信号也产生较大影响;SFTD算法比FSWC算法具有更好的信号状态融合准确性。展开更多
With the development of unmanned driving technology,intelligent robots and drones,high-precision localization,navigation and state estimation technologies have also made great progress.Traditional global navigation sa...With the development of unmanned driving technology,intelligent robots and drones,high-precision localization,navigation and state estimation technologies have also made great progress.Traditional global navigation satellite system/inertial navigation system(GNSS/INS)integrated navigation systems can provide high-precision navigation information continuously.However,when this system is applied to indoor or GNSS-denied environments,such as outdoor substations with strong electromagnetic interference and complex dense spaces,it is often unable to obtain high-precision GNSS positioning data.The positioning and orientation errors will diverge and accumulate rapidly,which cannot meet the high-precision localization requirements in large-scale and long-distance navigation scenarios.This paper proposes a method of high-precision state estimation with fusion of GNSS/INS/Vision using a nonlinear optimizer factor graph optimization as the basis for multi-source optimization.Through the collected experimental data and simulation results,this system shows good performance in the indoor environment and the environment with partial GNSS signal loss.展开更多
Reliability evaluation for aircraft engines is difficult because of the scarcity of failure data. But aircraft engine data are available from a variety of sources. Data fusion has the function of maximizing the amount...Reliability evaluation for aircraft engines is difficult because of the scarcity of failure data. But aircraft engine data are available from a variety of sources. Data fusion has the function of maximizing the amount of valu- able information extracted from disparate data sources to obtain the comprehensive reliability knowledge. Consid- ering the degradation failure and the catastrophic failure simultaneously, which are competing risks and can affect the reliability, a reliability evaluation model based on data fusion for aircraft engines is developed, Above the characteristics of the proposed model, reliability evaluation is more feasible than that by only utilizing failure data alone, and is also more accurate than that by only considering single failure mode. Example shows the effective- ness of the proposed model.展开更多
文摘为解决无线网络信号在传输过程中由于受到其他信号的干扰,导致接收端接收的信号与原始信号相比存在误差的问题,该文在利用数据关联和卡尔曼滤波对信号进行融合(fusion method of signal filtering based on wavelet transform and Calman,FSWC)的基础上,利用FARIMA(p,d,q)模型和数据关联来建立一种新的信号融合算法(signal fusion based on wavelet transform and date association,SFTD)。通过仿真实验分别研究融合信号与干扰距离、发送速率、容量、功率的变化情况。仿真结果表明:随着干扰距离的增加,容量开始呈现正相关趋势,直至趋于平稳,并且发送速率、容量、功率对融合信号也产生较大影响;SFTD算法比FSWC算法具有更好的信号状态融合准确性。
基金supported in part by the Guangxi Power Grid Company’s 2023 Science and Technol-ogy Innovation Project(No.GXKJXM20230169)。
文摘With the development of unmanned driving technology,intelligent robots and drones,high-precision localization,navigation and state estimation technologies have also made great progress.Traditional global navigation satellite system/inertial navigation system(GNSS/INS)integrated navigation systems can provide high-precision navigation information continuously.However,when this system is applied to indoor or GNSS-denied environments,such as outdoor substations with strong electromagnetic interference and complex dense spaces,it is often unable to obtain high-precision GNSS positioning data.The positioning and orientation errors will diverge and accumulate rapidly,which cannot meet the high-precision localization requirements in large-scale and long-distance navigation scenarios.This paper proposes a method of high-precision state estimation with fusion of GNSS/INS/Vision using a nonlinear optimizer factor graph optimization as the basis for multi-source optimization.Through the collected experimental data and simulation results,this system shows good performance in the indoor environment and the environment with partial GNSS signal loss.
基金Supported by the National Natural Science Foundation of China and Aviation Fund(60879001)the Natural Science Foundation of Jiangsu Province(BK2009378)+1 种基金the Fundamental Research Fund of Nanjing University of Aeronautics and Astronautics(NS2010179)the Qinglan Project of Jiangsu Province~~
文摘Reliability evaluation for aircraft engines is difficult because of the scarcity of failure data. But aircraft engine data are available from a variety of sources. Data fusion has the function of maximizing the amount of valu- able information extracted from disparate data sources to obtain the comprehensive reliability knowledge. Consid- ering the degradation failure and the catastrophic failure simultaneously, which are competing risks and can affect the reliability, a reliability evaluation model based on data fusion for aircraft engines is developed, Above the characteristics of the proposed model, reliability evaluation is more feasible than that by only utilizing failure data alone, and is also more accurate than that by only considering single failure mode. Example shows the effective- ness of the proposed model.