A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been deve...A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been developed.The main difference between our modeling method and those previous works is edge finite-element approach applied to solving the three-dimensional land frequency-domain electromagnetic responses generated by horizontal electric dipole source.Firstly,the edge finite-element equation is formulated through the Galerkin method based on Helmholtz equation of the electric fields.Secondly,in order to check the validity of the modeling code,the numerical results are compared with the analytical solutions for a homogeneous half-space model.Finally,other three models are simulated with three-dimensional electromagnetic responses.The results indicate that the method can be applied for solving three-dimensional electromagnetic responses.The algorithm has been demonstrated,which can be effective to modeling the complex geo-electrical structures.This efficient algorithm will help to study the distribution laws of3-D land frequency-domain controlled-source electromagnetic responses and to setup basis for research of three-dimensional inversion.展开更多
Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework...Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.展开更多
针对复杂水下环境中水下自主航行器(autonomous underwater vehicle,AUV)路径规划问题,提出一种改进启发式快速随机扩展树(rapidly-exploring random trees,RRT)的路径规划算法。针对路径点采样过程中缺乏目标导向性的问题,采用目标点...针对复杂水下环境中水下自主航行器(autonomous underwater vehicle,AUV)路径规划问题,提出一种改进启发式快速随机扩展树(rapidly-exploring random trees,RRT)的路径规划算法。针对路径点采样过程中缺乏目标导向性的问题,采用目标点概率偏置采样策略与目标偏向扩展策略,可使目标节点在随机采样时成为采样点。在路径点扩展过程中,使非目标采样点的扩展结点位置偏向于目标点的方向,从而增强算法在随机采样与扩展过程中的目标搜索能力。为解决水下路径规划过程中存在过多无效搜索空间的问题,在随机采样过程中引入启发式采样策略,构建包含所有初始路径的采样空间子集,减小采样空间范围,从而提高算法的空间搜索效率。针对AUV在水下环境中抗洋流扰动能力不足的问题,采用速度矢量合成法,使AUV速度矢量与洋流速度矢量合成后指向期望路径的方向,从而抵消水流的影响。在山峰地形中叠加多个Lamb涡流模拟水下流场环境,进行多次仿真实验。实验结果表明:改进启发式RRT算法解决了采样过程中随机性问题,显著缩小了搜索空间,兼顾了路径的安全性与平滑性,并使AUV具有良好的抗洋流扰动能力。展开更多
双机串轴运行中,负载转矩突变以及外部风浪干扰等都会影响串轴电机的转矩均衡性能,这对控制系统的灵活性和抗扰性提出较高要求。为此,在建立多相电机串轴系统数学模型的基础上,提出了基于主从结构的分绕组式多相电机矢量控制策略,并在...双机串轴运行中,负载转矩突变以及外部风浪干扰等都会影响串轴电机的转矩均衡性能,这对控制系统的灵活性和抗扰性提出较高要求。为此,在建立多相电机串轴系统数学模型的基础上,提出了基于主从结构的分绕组式多相电机矢量控制策略,并在转速环采用线性自抗扰控制(linear active disturbance rejection control,LADRC)。仿真和实验结果表明:当推进系统工况切换时,基于主从结构的分绕组控制实现了双机负载功率的自动再分配。同时,LADRC能对速度跟踪进行优化,提高了刚性连接串轴系统的转矩均衡性能和抗干扰性能。展开更多
为解决传统检测方法在处理复杂、动态以及数据长度实时变化的飞行轨迹数据时特征提取不准确、检测效率较低的问题,提出一种结合长短时记忆(Long Short-Term Memory, LSTM)网络和支持向量数据描述(Support Vector Data Description, SVDD...为解决传统检测方法在处理复杂、动态以及数据长度实时变化的飞行轨迹数据时特征提取不准确、检测效率较低的问题,提出一种结合长短时记忆(Long Short-Term Memory, LSTM)网络和支持向量数据描述(Support Vector Data Description, SVDD)的无监督异常检测方法。利用LSTM网络提取可变长度飞行轨迹的关键特征,并将其转化为固定长度的序列表示;通过SVDD算法构建多维超球分类器,对正常飞行轨迹进行建模,从而识别潜在异常轨迹。为进一步提升模型性能,引入基于梯度的优化算法(Gradient-Based training algorithm, GB),实现LSTM与SVDD参数的联合训练,大幅度提高检测精度和计算效率。仿真实验结果表明,新提出的基于梯度优化的长短时记忆网络和支持向量数据描述模型(Long Short-Term Memory network and Support Vector Data Description model based on Gradient-Based training algorithm optimization, LSTM-GBSVDD)的飞行轨迹异常检测方法在处理复杂、多变的飞行轨迹异常检测任务中表现出较好的有效性和优越性,有较强的应用前景。展开更多
基金Projects(41674080,41674079)supported by the National Natural Science Foundation of China
文摘A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been developed.The main difference between our modeling method and those previous works is edge finite-element approach applied to solving the three-dimensional land frequency-domain electromagnetic responses generated by horizontal electric dipole source.Firstly,the edge finite-element equation is formulated through the Galerkin method based on Helmholtz equation of the electric fields.Secondly,in order to check the validity of the modeling code,the numerical results are compared with the analytical solutions for a homogeneous half-space model.Finally,other three models are simulated with three-dimensional electromagnetic responses.The results indicate that the method can be applied for solving three-dimensional electromagnetic responses.The algorithm has been demonstrated,which can be effective to modeling the complex geo-electrical structures.This efficient algorithm will help to study the distribution laws of3-D land frequency-domain controlled-source electromagnetic responses and to setup basis for research of three-dimensional inversion.
文摘Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.
文摘针对复杂水下环境中水下自主航行器(autonomous underwater vehicle,AUV)路径规划问题,提出一种改进启发式快速随机扩展树(rapidly-exploring random trees,RRT)的路径规划算法。针对路径点采样过程中缺乏目标导向性的问题,采用目标点概率偏置采样策略与目标偏向扩展策略,可使目标节点在随机采样时成为采样点。在路径点扩展过程中,使非目标采样点的扩展结点位置偏向于目标点的方向,从而增强算法在随机采样与扩展过程中的目标搜索能力。为解决水下路径规划过程中存在过多无效搜索空间的问题,在随机采样过程中引入启发式采样策略,构建包含所有初始路径的采样空间子集,减小采样空间范围,从而提高算法的空间搜索效率。针对AUV在水下环境中抗洋流扰动能力不足的问题,采用速度矢量合成法,使AUV速度矢量与洋流速度矢量合成后指向期望路径的方向,从而抵消水流的影响。在山峰地形中叠加多个Lamb涡流模拟水下流场环境,进行多次仿真实验。实验结果表明:改进启发式RRT算法解决了采样过程中随机性问题,显著缩小了搜索空间,兼顾了路径的安全性与平滑性,并使AUV具有良好的抗洋流扰动能力。
文摘双机串轴运行中,负载转矩突变以及外部风浪干扰等都会影响串轴电机的转矩均衡性能,这对控制系统的灵活性和抗扰性提出较高要求。为此,在建立多相电机串轴系统数学模型的基础上,提出了基于主从结构的分绕组式多相电机矢量控制策略,并在转速环采用线性自抗扰控制(linear active disturbance rejection control,LADRC)。仿真和实验结果表明:当推进系统工况切换时,基于主从结构的分绕组控制实现了双机负载功率的自动再分配。同时,LADRC能对速度跟踪进行优化,提高了刚性连接串轴系统的转矩均衡性能和抗干扰性能。
文摘为解决传统检测方法在处理复杂、动态以及数据长度实时变化的飞行轨迹数据时特征提取不准确、检测效率较低的问题,提出一种结合长短时记忆(Long Short-Term Memory, LSTM)网络和支持向量数据描述(Support Vector Data Description, SVDD)的无监督异常检测方法。利用LSTM网络提取可变长度飞行轨迹的关键特征,并将其转化为固定长度的序列表示;通过SVDD算法构建多维超球分类器,对正常飞行轨迹进行建模,从而识别潜在异常轨迹。为进一步提升模型性能,引入基于梯度的优化算法(Gradient-Based training algorithm, GB),实现LSTM与SVDD参数的联合训练,大幅度提高检测精度和计算效率。仿真实验结果表明,新提出的基于梯度优化的长短时记忆网络和支持向量数据描述模型(Long Short-Term Memory network and Support Vector Data Description model based on Gradient-Based training algorithm optimization, LSTM-GBSVDD)的飞行轨迹异常检测方法在处理复杂、多变的飞行轨迹异常检测任务中表现出较好的有效性和优越性,有较强的应用前景。
