Simple GNSS navigation receivers, developed for the mass market, can be used for positioning with sub centimeter accuracy in a wireless sensor network if the read-out of the carrier phase data is possible and all data...Simple GNSS navigation receivers, developed for the mass market, can be used for positioning with sub centimeter accuracy in a wireless sensor network if the read-out of the carrier phase data is possible and all data is permanently broadcast to a central computer for near real time processing of the respective base lines. Experiences gained in two research projects related to landslide monitoring are depicted in terms of quality and reliability of the results by the developed approach. As far as possible a modular system set up with commercial off-the-shelf components, e.g., standard WLAN fur commtmication, solar batteries with solar panels for autarkic power supply and in cooperation of existing proofed program tools is chosen. The challenge of the still ongoing development is to have a flexible and robust GNSS based sensor network available - concerned not only for landslide monitoring in future.展开更多
The visibility for low earth orbit（LEO） satellites provided by the BeiDou-2 system is analyzed and compared with the global positioning system（GPS）. In addition, the spaceborne receivers＇ observations are simulat...The visibility for low earth orbit（LEO） satellites provided by the BeiDou-2 system is analyzed and compared with the global positioning system（GPS）. In addition, the spaceborne receivers＇ observations are simulated by the BeiDou satellites broadcast ephemeris and LEO satellites orbits. The precise orbit determination（POD） results show that the along-track component accuracy is much better over the service area than the non-service area, while the accuracy of the other two directions keeps at the same level over different areas. However, the 3-dimensional（3D） accuracy over the two areas shows almost no difference. Only taking into consideration the observation noise and navigation satellite ephemeris errors, the 3D accuracy of the POD is about30 cm. As for the precise relative orbit determination（PROD）, the 3D accuracy is much better over the eastern hemisphere than that of the western hemisphere. The baseline length accuracy is 3.4 mm over the service area, and it is still better than 1 cm over the non-service area. This paper demonstrates that the BeiDou regional constellation could provide global service to LEO satellites for the POD and the PROD. Finally, the benefit of geostationary earth orbit（GEO） satellites is illustrated for POD.展开更多
Low-precision training has emerged as a practical approach,saving the cost of time,memory,and energy during deep neural networks(DNNs)training.Typically,the use of lower precision introduces quantization errors that n...Low-precision training has emerged as a practical approach,saving the cost of time,memory,and energy during deep neural networks(DNNs)training.Typically,the use of lower precision introduces quantization errors that need to be minimized to maintain model performance,often neglecting to consider the potential benefits of reducing training precision.This paper rethinks low-precision training,highlighting the potential benefits of lowering precision:(1)low precision can serve as a form of regularization in DNN training by constraining excessive variance in the model;(2)layer-wise low precision can be seen as an alternative dimension of sparsity,orthogonal to pruning,contributing to improved generalization in DNNs.Based on these analyses,we propose a simple yet powerful technique-DPC(Decreasing Precision with layer Capacity),which directly assigns different bit-widths to model layers,without the need for an exhaustive analysis of the training process or any delicate low-precision criteria.Thorough extensive experiments on five datasets and fourteen models across various applications consistently demonstrate the effectiveness of the proposed DPC technique in saving computational cost(-16.21%--44.37%)while achieving comparable or even superior accuracy(up to+0.68%,+0.21%on average).Furthermore,we offer feature embedding visualizations and conduct further analysis with experiments to investigate the underlying mechanisms behind DPC’s effectiveness,enhancing our understanding of low-precision training.Our source code will be released upon paper acceptance.展开更多
文摘Simple GNSS navigation receivers, developed for the mass market, can be used for positioning with sub centimeter accuracy in a wireless sensor network if the read-out of the carrier phase data is possible and all data is permanently broadcast to a central computer for near real time processing of the respective base lines. Experiences gained in two research projects related to landslide monitoring are depicted in terms of quality and reliability of the results by the developed approach. As far as possible a modular system set up with commercial off-the-shelf components, e.g., standard WLAN fur commtmication, solar batteries with solar panels for autarkic power supply and in cooperation of existing proofed program tools is chosen. The challenge of the still ongoing development is to have a flexible and robust GNSS based sensor network available - concerned not only for landslide monitoring in future.
基金co-supported by the National Natural Science Foundation of China (Nos: 61002033, 61370013)the Program for New Century Excellent Talents in University and the Scientific Research Foundation for the Returned Overseas Chinese Scholars of Ministry of Education of China
文摘The visibility for low earth orbit（LEO） satellites provided by the BeiDou-2 system is analyzed and compared with the global positioning system（GPS）. In addition, the spaceborne receivers＇ observations are simulated by the BeiDou satellites broadcast ephemeris and LEO satellites orbits. The precise orbit determination（POD） results show that the along-track component accuracy is much better over the service area than the non-service area, while the accuracy of the other two directions keeps at the same level over different areas. However, the 3-dimensional（3D） accuracy over the two areas shows almost no difference. Only taking into consideration the observation noise and navigation satellite ephemeris errors, the 3D accuracy of the POD is about30 cm. As for the precise relative orbit determination（PROD）, the 3D accuracy is much better over the eastern hemisphere than that of the western hemisphere. The baseline length accuracy is 3.4 mm over the service area, and it is still better than 1 cm over the non-service area. This paper demonstrates that the BeiDou regional constellation could provide global service to LEO satellites for the POD and the PROD. Finally, the benefit of geostationary earth orbit（GEO） satellites is illustrated for POD.
基金supported by the National Key R&D Program of China(Grant No.2021YFB0301200)the National Natural Science Foundation of China(Grant No.62025208).
文摘Low-precision training has emerged as a practical approach,saving the cost of time,memory,and energy during deep neural networks(DNNs)training.Typically,the use of lower precision introduces quantization errors that need to be minimized to maintain model performance,often neglecting to consider the potential benefits of reducing training precision.This paper rethinks low-precision training,highlighting the potential benefits of lowering precision:(1)low precision can serve as a form of regularization in DNN training by constraining excessive variance in the model;(2)layer-wise low precision can be seen as an alternative dimension of sparsity,orthogonal to pruning,contributing to improved generalization in DNNs.Based on these analyses,we propose a simple yet powerful technique-DPC(Decreasing Precision with layer Capacity),which directly assigns different bit-widths to model layers,without the need for an exhaustive analysis of the training process or any delicate low-precision criteria.Thorough extensive experiments on five datasets and fourteen models across various applications consistently demonstrate the effectiveness of the proposed DPC technique in saving computational cost(-16.21%--44.37%)while achieving comparable or even superior accuracy(up to+0.68%,+0.21%on average).Furthermore,we offer feature embedding visualizations and conduct further analysis with experiments to investigate the underlying mechanisms behind DPC’s effectiveness,enhancing our understanding of low-precision training.Our source code will be released upon paper acceptance.
