scholarly journals A Fast Estimation Method for Satellite in Orbit Management

2020 ◽  
Vol 316 ◽  
pp. 04007
Author(s):  
Zhen Cui ◽  
Ye Ji ◽  
Bin Chen ◽  
Yang Yang
Keyword(s):  
Real Time ◽  
Satellite Telemetry ◽  
Estimation Method ◽  
Decisive Role ◽  
Telemetry Data ◽  
The Real ◽  
Fast Estimation ◽  
Fault Handling ◽  
Rapid Processing ◽  
The Impact

The management of satellites in orbit requires accurate and rapid processing to minimize the impact of failures. Especially for fault handling involving energy security, the real-time nature of the process plays a decisive role. This paper proposes a fast estimation method based on satellite telemetry data. Through the analysis of the shape of the telemetry curve, the geometric method, the correlation analysis of the telemetry data on the satellite, or the physical principles, the required parameters are quickly obtained to facilitate rapid emergency processing. This method is applied to satellite in-orbit management, which can greatly improve the real-time performance of fault processing, and has good engineering practical value.

scholarly journals Learning-Type Anchors-Driven Pose Estimation for the Autolanding Fixed-Wing UAVs

2021 ◽  
Author(s):  
Dengqing Tang ◽  
Lincheng Shen ◽  
Xiaojiao Xiang ◽  
Han Zhou ◽  
Tianjiang Hu
Keyword(s):  
Real Time ◽  
Pose Estimation ◽  
Stereo Vision ◽  
Vision System ◽  
Estimation Method ◽  
Satellite System ◽  
Training Dataset ◽  
Estimation Accuracy ◽  
The Impact ◽  
Outdoor Experiments

<p>We propose a learning-type anchors-driven real-time pose estimation method for the autolanding fixed-wing unmanned aerial vehicle (UAV). The proposed method enables online tracking of both position and attitude by the ground stereo vision system in the Global Navigation Satellite System denied environments. A pipeline of convolutional neural network (CNN)-based UAV anchors detection and anchors-driven UAV pose estimation are employed. To realize robust and accurate anchors detection, we design and implement a Block-CNN architecture to reduce the impact of the outliers. With the basis of the anchors, monocular and stereo vision-based filters are established to update the UAV position and attitude. To expand the training dataset without extra outdoor experiments, we develop a parallel system containing the outdoor and simulated systems with the same configuration. Simulated and outdoor experiments are performed to demonstrate the remarkable pose estimation accuracy improvement compared with the conventional Perspective-N-Points solution. In addition, the experiments also validate the feasibility of the proposed architecture and algorithm in terms of the accuracy and real-time capability requirements for fixed-wing autolanding UAVs.</p>

scholarly journals Applying a Model for Trip Assignment and Dynamic Routing of Automated Taxis with Congestion: System Performance in the City of Delft, The Netherlands

2018 ◽  
Vol 2672 (8) ◽  
pp. 588-598 ◽  
Author(s):  
Xiao Liang ◽  
Gonçalo Homem de Almeida Correia ◽  
Bart van Arem
Keyword(s):  
The Netherlands ◽  
Real Time ◽  
Traffic Congestion ◽  
Programming Model ◽  
Profit Maximization ◽  
The Real ◽  
Real Size ◽  
The Impact ◽  
The City

This paper proposes a method of assigning trips to automated taxis (ATs) and designing the routes of those vehicles in an urban road network, and also considering the traffic congestion caused by this dynamic responsive service. The system is envisioned to provide a seamless door-to-door service within a city area for all passenger origins and destinations. An integer programming model is proposed to define the routing of the vehicles according to a profit maximization function, depending on the dynamic travel times, which varies with the ATs’ flow. This will be especially important when the number of automated vehicles (AVs) circulating on the roads is high enough that their routing will cause delays. This system should be able to serve not only the reserved travel requests, but also some real-time requests. A rolling horizon scheme is used to divide one day into several periods in which both the real-time and the booked demand will be considered together. The model was applied to the real size case study city of Delft, the Netherlands. The results allow assessing of the impact of the ATs movements on traffic congestion and the profitability of the system. From this case-study, it is possible to conclude that taking into account the effect of the vehicle flows on travel time leads to changes in the system profit, the satisfied percentage and the driving distance of the vehicles, which highlights the importance of this type of model in the assessment of the operational effects of ATs in the future.

Impact of Vibrations and Electronic Coherence on Electron Transfer in Flat Molecular Wires

MRS Advances ◽  
2017 ◽  
Vol 2 (14) ◽  
pp. 811-816 ◽  
Author(s):  
Oscar Grånäs ◽  
Grigory Kolesov ◽  
Efthimios Kaxiras
Keyword(s):  
Electron Transfer ◽  
Excited State ◽  
Real Time ◽  
Density Functional ◽  
Molecular Wires ◽  
The Real ◽  
Velocity Autocorrelation ◽  
Td Dft ◽  
Electronic Coherence ◽  
The Impact

ABSTRACTElectron transfer in molecular wires are of fundamental importance for a range of optoelectronic applications. The impact of electronic coherence and ionic vibrations on transmittance are of great importance to determine the mechanisms, and subsequently the type of wires that are most promising for applications. In this work, we use the real-time formulation of time-dependent density functional theory to study electron transfer through oligo-p-phenylenevinylene (OPV) and the recently synthesized carbon bridged counterpart (COPV). A system prototypical of organic photovoltaics is setup by bridging a porphyrin-fullerene dyad, allowing a photo-excited electron to flow between the Zn-porphyrin (ZnP) chromophore and the C60 electron acceptor through the molecular wire. The excited state is described using the fully self-consistent ∆-SCF method. The state is then propagated in time using the real-time TD-DFT scheme, while describing ionic vibrations with classical nuclei. The charge transferred between porphyrin and C60 is calculated and correlated with the velocity autocorrelation functions of the ions. This provides a microscopic insight to vibrational and tunneling contributions to electron transport in linked porphyrin-fullerene dyads. We elaborate on important details in describing the excited state and trajectory sampling.

scholarly journals An RGB-D-Based Cross-Field of View Pose Estimation System for a Free Flight Target in a Wind Tunnel

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Sheng Liu ◽  
Yuan Feng ◽  
Kang Shen ◽  
Yangqing Wang ◽  
Shengyong Chen
Keyword(s):  
Wind Tunnel ◽  
Real Time ◽  
Pose Estimation ◽  
Dynamic Testing ◽  
Estimation Method ◽  
Spatial Relationship ◽  
Field Of View ◽  
Free Flight ◽  
The Real ◽  
Estimation System

Estimating the real-time pose of a free flight aircraft in a complex wind tunnel environment is extremely difficult. Due to the high dynamic testing environment, complicated illumination condition, and the unpredictable motion of target, most general pose estimating methods will fail. In this paper, we introduce a cross-field of view (FOV) real-time pose estimation system, which provides high precision pose estimation of the free flight aircraft in the wind tunnel environment. Multiview live RGB-D streams are used in the system as input to ensure the measurement area can be fully covered. First, a multimodal initialization method is developed to measure the spatial relationship between the RGB-D camera and the aircraft. Based on all the input multimodal information, a so-called cross-FOV model is proposed to recognize the dominating sensor and accurately extract the foreground region in an automatic manner. Second, we develop an RGB-D-based pose estimation method for a single target, by which the 3D sparse points and the pose of the target can be simultaneously obtained in real time. Many experiments have been conducted, and an RGB-D image simulation based on 3D modeling is implemented to verify the effectiveness of our algorithm. Both the real scene’s and simulation scene’s experimental results demonstrate the effectiveness of our method.

scholarly journals Multi-Time Scale Rolling Economic Dispatch for Wind/Storage Power System Based on Forecast Error Feature Extraction

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2124 ◽  
Author(s):  
Li Han ◽  
Rongchang Zhang ◽  
Xuesong Wang ◽  
Yu Dong
Keyword(s):  
Power System ◽  
Real Time ◽  
Wind Power ◽  
Power Unit ◽  
Time Scale ◽  
Forecast Error ◽  
Thermal Power ◽  
Time Error ◽  
The Real ◽  
The Impact

This paper looks at the ability to cope with the uncertainty of wind power and reduce the impact of wind power forecast error (WPFE) on the operation and dispatch of power system. Therefore, several factors which are related to WPFE will be studied. By statistical analysis of the historical data, an indicator of real-time error based on these factors is obtained to estimate WPFE. Based on the real-time estimation of WPFE, a multi-time scale rolling dispatch model for wind/storage power system is established. In the real-time error compensation section of this model, the previous dispatch plan of thermal power unit is revised according to the estimation of WPFE. As the regulating capacity of thermal power unit within a short time period is limited, the estimation of WPFE is further compensated by using battery energy storage system. This can not only decrease the risk caused by the wind power uncertainty and lessen wind spillage, but also reduce the total cost. Thereby providing a new method to describe and model wind power uncertainty, and providing economic, safe and energy-saving dispatch plan for power system. The analysis in case study verifies the effectiveness of the proposed model.

scholarly journals InSAR Baseline Estimation for Gaofen-3 Real-Time DEM Generation

2018 ◽  
Author(s):  
Huan Lu ◽  
Zhiyong Suo ◽  
Zhenfang Li ◽  
Jinwei Xie ◽  
Qingjun Zhang
Keyword(s):  
Real Time ◽  
Estimation Method ◽  
Shuttle Radar Topography Mission ◽  
The Real ◽  
Digital Elevation ◽  
Orbit Fitting ◽  
Elevation Model ◽  
Interferometric Sar ◽  
Baseline Estimation ◽  
Baseline Error

For Interferometry Synthetic Aperture Radar (InSAR), the normal baseline is one of the main factors that affect the accuracy of the ground elevation. For Gaofen-3 (GF-3) InSAR processing, the poor accuracy of the real-time orbit determination resulting in a large baseline error, leads to the modulation error in azimuth and the slope error in range for timely Digital Elevation Model (DEM) generation. In order to address this problem, a baseline estimation method based on external DEM is proposed in this paper. Firstly, according to the characteristic of the real-time orbit of GF-3 images, orbit fitting is executed to remove the non-linear error factor. Secondly, the height errors are obtained in slant-range plane between Shuttle Radar Topography Mission (SRTM) DEM and the GF-3 generated DEM after orbit fitting. At the same time, the height errors are used to estimate the baseline error which has a linear variation. In this way, the orbit error can be calibrated by the estimated baseline error. Finally, DEM generation is performed by using the modified baseline and orbit. This procedure is implemented iteratively to achieve a higher accuracy DEM. Based on the results of GF-3 interferometric SAR data for Hebei, the effectiveness of the proposed algorithm is verified and the accuracy of GF-3 real-time DEM products can be improved extensively.

scholarly journals Learning-Type Anchors-Driven Pose Estimation for the Autolanding Fixed-Wing UAVs

2021 ◽  
Author(s):  
Dengqing Tang ◽  
Lincheng Shen ◽  
Xiaojiao Xiang ◽  
Han Zhou ◽  
Tianjiang Hu
Keyword(s):  
Real Time ◽  
Pose Estimation ◽  
Stereo Vision ◽  
Vision System ◽  
Estimation Method ◽  
Satellite System ◽  
Training Dataset ◽  
Estimation Accuracy ◽  
The Impact ◽  
Outdoor Experiments

<p>We propose a learning-type anchors-driven real-time pose estimation method for the autolanding fixed-wing unmanned aerial vehicle (UAV). The proposed method enables online tracking of both position and attitude by the ground stereo vision system in the Global Navigation Satellite System denied environments. A pipeline of convolutional neural network (CNN)-based UAV anchors detection and anchors-driven UAV pose estimation are employed. To realize robust and accurate anchors detection, we design and implement a Block-CNN architecture to reduce the impact of the outliers. With the basis of the anchors, monocular and stereo vision-based filters are established to update the UAV position and attitude. To expand the training dataset without extra outdoor experiments, we develop a parallel system containing the outdoor and simulated systems with the same configuration. Simulated and outdoor experiments are performed to demonstrate the remarkable pose estimation accuracy improvement compared with the conventional Perspective-N-Points solution. In addition, the experiments also validate the feasibility of the proposed architecture and algorithm in terms of the accuracy and real-time capability requirements for fixed-wing autolanding UAVs.</p>

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