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Institution

National University of Defense Technology

EducationChangsha, China
About: National University of Defense Technology is a education organization based out in Changsha, China. It is known for research contribution in the topics: Radar & Synthetic aperture radar. The organization has 39430 authors who have published 40181 publications receiving 358979 citations. The organization is also known as: Guófáng Kēxuéjìshù Dàxué & NUDT.


Papers
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Journal ArticleDOI
TL;DR: A covert spoofing algorithm of an unmanned aerial vehicle (UAV) based on GPS/inertial-navigation-system-integrated navigation is analyzed and theoretically proves the fact that when the acceleration component of the counterfeit GPS signal is the difference between the UAV's current acceleration and the spoofing control input, theUAV can be covert spoofed.
Abstract: A covert spoofing algorithm of an unmanned aerial vehicle (UAV) based on GPS/inertial-navigation-system-integrated navigation is analyzed in this paper. The proposed algorithm theoretically proves the fact that when the acceleration component of the counterfeit GPS signal is the difference between the UAV's current acceleration and the spoofing control input, the UAV can be covert spoofed. To avoid adverse consequences (detection or crash) caused by frequent changes in UAV flight during the GPS spoofing attacks, the proposed algorithm requires that the deception trajectory planned by the GPS spoofer is slowly changing relative to the reference trajectory, which is pre-set by the UAV. Simulation results have verified the correctness of the proposed covert spoofing algorithm of UAV. Moreover, the spoofing effect is more distinct when the deception trajectory planning is considered.

78 citations

Journal ArticleDOI
TL;DR: The transfer learning ability on deep CNN for airport detection on satellite images had been first evaluated in this letter and showed a great improvement over other the state-of-the-art methods.
Abstract: This letter proposes a method using convolutional neural networks (CNNs) for airport detection on optical satellite images. To efficiently build a deep CNN with limited satellite image samples, a transfer learning approach had been employed by sharing the common image features of the natural images. To decrease the computing cost, an efficient region proposal method had been proposed based on the prior knowledge of the line segments distribution in an airport. The transfer learning ability on deep CNN for airport detection on satellite images had been first evaluated in this letter. The proposed method was tested on an image data set, including 170 different airports and 30 nonairports. The detection rate could reach 88.8% in experiments with seconds’ computation time, which showed a great improvement over other the state-of-the-art methods.

78 citations

Journal ArticleDOI
TL;DR: A team led by Xuezhong Wu at the National University of Defense Technology, China, reports what they claim are record quality factors and decay times for MEMS silicon disk gyroscopes.
Abstract: The disk resonator gyroscope is an attractive candidate for high-performance MEMS gyroscopes. This gyroscope consists of a sensor and readout electronics, and the characteristics of the sensor directly determine the performance. For the sensor, a high-quality factor and long decaying time constant are the most important characteristics required to achieve high performance. We report a disk resonator gyroscope with a measured quality factor of 510 k and decaying time constant of 74.9 s, which is a record for MEMS silicon disk resonator gyroscopes, to the best of our knowledge. To improve the quality factor of the DRG, the quality factor improvement mechanism is first analyzed, and based on this mechanism two stiffness-mass decoupled methods, i.e., spoke length distribution optimization and lumped mass configuration design, are proposed and demonstrated. A disk resonator gyroscope prototype is fabricated based on these design strategies, and the sensor itself shows an angle random walk as low as 0.001°/√h, demonstrating true potential to achieve navigation-grade performance. The gyroscope with readout electronics shows an angle random walk of 0.01°/√h and a bias instability of 0.04°/h at room temperature without compensation, revealing that the performance of the gyroscope is severely limited by the readout electronics, which should be further improved. We expect that the quality factor improvement methods can be used in the design of other MEMS gyroscopes and that the newly designed DRG can be further improved to achieve navigation-grade performances for high-end industrial, transportation, aerospace, and automotive applications. A disk resonator gyroscope demonstrates a high-quality factor of 510 k and decay time constant of 74.9 s. High-performance MEMS gyroscopes are in demand for a range of high-end applications. Disk resonator gyroscopes are particularly promising candidates due to inherent mode matching and high thermal stability. However, many applications demand high-quality factors and long decay times. Now, a team led by Xuezhong Wu at the National University of Defense Technology, China, reports what they claim are record quality factors and decay times for MEMS silicon disk gyroscopes. Two mechanisms for stiffness-mass decoupling are attributed to the high performance, which the authors say could be used for the design of other MEMS gyroscopes.

78 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present an improved study of their previous work [Phys. Rev. D 80, 056004] to investigate the possibility that the newly observed ${Z}_{c}(3900)$ is a $S$-wave $\overline{D}{D}^{*}$ molecular state.
Abstract: In the framework of QCD sum rules, we present an improved study of our previous work [Phys. Rev. D 80, 056004 (2009)], particularly on the $\overline{D}{D}^{*}$ molecular state, to investigate the possibility that the newly observed ${Z}_{c}(3900)$ is a $S$-wave $\overline{D}{D}^{*}$ molecular state. To ensure the quality of QCD sum rule analysis, contributions of up to dimension nine are calculated to test the convergence of operator product expansion (OPE). We find that the two-quark condensate $⟨\overline{q}q⟩$ is very large and makes the standard OPE convergence (i.e. the perturbative at least larger than each condensate contribution) happen at very large values of Borel parameters. By releasing the rigid OPE convergence criterion, one could find that the OPE convergence is still under control. We arrive at the numerical result $3.86\ifmmode\pm\else\textpm\fi{}0.27\text{ }\text{ }\mathrm{GeV}$ for $\overline{D}{D}^{*}$, which agrees with the mass of ${Z}_{c}(3900)$ and could support the explanation of ${Z}_{c}(3900)$ in terms of a $S$-wave $\overline{D}{D}^{*}$ molecular state.

78 citations

Journal ArticleDOI
TL;DR: In this paper, a bifunctional oxygen electrocatalyst based on FeCo nanoparticles/N-doped carbon core-shell spheres was prepared via one-step pyrolysis of graphitic carbon nitride and acetylacetonates.
Abstract: Electrocatalytic conversion of oxygen holds great potential for clean energy technologies, including water electrolysis, regenerative fuel cells, and rechargeable metal-air batteries. The development of highly efficient and inexpensive oxygen electrocatalysts as replacements for precious metal-based catalysts is vitally important for large-scale practical application in the future. A bifunctional oxygen electrocatalyst based on FeCo nanoparticles/N-doped carbon core–shell spheres supported on N-doped graphene sheets was prepared via one-step pyrolysis of graphitic carbon nitride and acetylacetonates. The optimized product exhibited an oxygen electrode activity of 0.87 V and excellent durability. The remarkable performance is mainly attributed to the synergetic effect arising from the FeCo nanoparticles and N-doped carbon shell. This study introduces an inexpensive and simple way to develop highly active bifunctional oxygen electrocatalysts.

78 citations


Authors

Showing all 39659 results

NameH-indexPapersCitations
Rui Zhang1512625107917
Jian Li133286387131
Chi Lin1251313102710
Wei Xu103149249624
Lei Liu98204151163
Xiang Li97147242301
Chang Liu97109939573
Jian Huang97118940362
Tao Wang97272055280
Wei Liu96153842459
Jian Chen96171852917
Wei Wang95354459660
Peng Li95154845198
Jianhong Wu9372636427
Jianhua Zhang9241528085
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
202397
2022468
20212,986
20203,468
20193,695