National University of Defense Technology

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

A Fast Back-Projection Algorithm Based on Cross Correlation for GPR Imaging

Abstract: In ground-penetrating radar imaging, the classic back-projection (BP) algorithm has an excellent reputation for imaging in layered mediums with convenience and robustness. However, the classic BP algorithm is time consuming and with a lot of artifacts, which have adverse effects on the following work like detection and recognition. A novel BP algorithm, which is both fast and with good effect of suppressing artifacts, is proposed in this letter. At first, an approved approximation method is used to calculate the position of refraction point with remarkable speed and satisfactory accuracy. Then, a lookup table is used to reduce the redundancy in classic BP algorithm. In order to achieve effective artifact suppression, a cross-correlation-based method is introduced. Experimental results of field data present the superiority of the proposed BP algorithm over its classic counterpart both in operation speed and artifact suppression.

Hybrid Satellite Terrestrial Relay Networks With Cooperative Non-Orthogonal Multiple Access

Abstract: In this letter, we investigate the outage probability (OP) and ergodic capacity of the downlink hybrid satellite terrestrial relay networks (HSTRNs) with a cooperative non-orthogonal multiple access (C–NOMA) scheme, in which a user with better channel condition acts as a relay node and forwards information to other users, thus alleviating the masking effect of users with poor channel conditions in heavy shadowing. Specifically, the exact analytical expression for the OP of the considered system is derived. Furthermore, the ergodic capacity expression is also developed to facilitate performance evaluation of the proposed framework. Finally, the simulations are provided to show the impact of key parameters on the considered system and the superiority of introducing the C–NOMA scheme to the HSTRNs.

Security Enhanced Authentication and Key Agreement Protocol for LTE/SAE Network

Abstract: The 3rd Generation Partnership (3GPP) standard is developing System Architecture Evolution(SAE)/Long Term Evolution(LTE) architecture for the next generation mobile communication system. In the LTE/SAE architecture, EPS AKA(Evolved Packet System Authentication and Key Agreement) procedure is used to provide mutual authentication between the user and the network. However the EPS AKA has several vulnerabilities such as disclosure of user identity, man-in-middle attack, etc. Therefore, this paper analyzes the deficiencies of the EPS AKA, and proposes a Security Enhanced Authentication and Key agreement (SE-EPS AKA) based on Wireless Public Key Infrastructure (WPKI). Then, the new SE-EPS AKA has been proved with the formal verification method, and the proof result shows that the SE-EPS AKA can satisfy the security and efficiency propoerties in the LTE/SAE architecture.

Predicting Scene Parsing and Motion Dynamics in the Future

Abstract: It is important for intelligent systems, e.g. autonomous vehicles and robotics to anticipate the future in order to plan early and make decisions accordingly. Predicting the future scene parsing and motion dynamics helps the agents better understand the visual environment better as the former provides dense semantic segmentations, i.e. what objects will be present and where they will appear, while the latter provides dense motion information, i.e. how the objects move in the future. In this paper, we propose a novel model to predict the scene parsing and motion dynamics in unobserved future video frames simultaneously. Using history information (preceding frames and corresponding scene parsing results) as input, our model is able to predict the scene parsing and motion for arbitrary time steps ahead. More importantly, our model is superior compared to other methods that predict parsing and motion separately, as the complementary relationship between the two tasks are fully utilized in our model through joint learning. To our best knowledge, this is the first attempt in jointly predicting scene parsing and motion dynamics in the future frames. On the large-scale Cityscapes dataset, it is demonstrated that our model produces significantly better parsing and motion prediction results compared to well established baselines. In addition, we also show our model can be used to predict the steering angle of the vehicles, which further verifies the ability of our model to learn underlying latent parameters.

Review on recent progress on mid-infrared fiber lasers

Abstract: We present review on recent progress on mid-infrared fiber lasers. The relevant glass fiber host materials and different kinds of doped rare-earth ions are introduced. Lasers operating from 1.9 to 3 μm in the rare-earth ions Tm3+, Ho3+, Er3+, and Dy3+ in the recent two years are discussed. Three interesting research issues, i.e., supercontinuum generation based on mid-infrared fiber laser, mid-infrared Raman fiber laser, and coherent beam combining in the mid-infrared wavelength band are classified and analyzed. Some discussions and prospective predictions are proposed at the end of this paper.