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: 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.

Sweep coverage with mobile sensors

Abstract: Many efforts have been made for addressing coverage problems in sensor networks. They fall into two categories, full coverage and barrier coverage, featured as static coverage. In this work, we study a new coverage scenario, sweep coverage, which differs with the previous static coverage. In sweep coverage, we only need to monitor certain points of interest (POIs) periodically so the coverage at each POI is time-variant, and thus we are able to utilize a small number of mobile sensors to achieve sweep coverage among a much larger number of POIs. We investigate the definitions and model for sweep coverage. Given a set of POIs and their sweep period requirements, we prove that determining the minimum number of required sensors (min-sensor sweep-coverage problem) is NP-hard, and it cannot be approximated within a factor of 2. We propose a centralized algorithm with constant approximation ratio 2 + epsi for the simplified problem where all sweep periods are identical. We further characterize the non-locality of the problem and design a distributed sweep algorithm, DSWEEP, cooperating sensors to provide required sweep requirements with the best effort. We conduct extensive simulations to study the performance of the proposed algorithms. Our simulations show that DSWEEP outperforms the randomized scheme in both effectiveness and efficiency.

Hierarchical Clustering With Hard-Batch Triplet Loss for Person Re-Identification

Abstract: For clustering-guided fully unsupervised person reidentification (re-ID) methods, the quality of pseudo labels generated by clustering directly decides the model performance. In order to improve the quality of pseudo labels in existing methods, we propose the HCT method which combines hierarchical clustering with hard-batch triplet loss. The key idea of HCT is to make full use of the similarity among samples in the target dataset through hierarchical clustering, reduce the influence of hard examples through hard-batch triplet loss, so as to generate high quality pseudo labels and improve model performance. Specifically, (1) we use hierarchical clustering to generate pseudo labels, (2) we use PK sampling in each iteration to generate a new dataset for training, (3) we conduct training with hard-batch triplet loss and evaluate model performance in each iteration. We evaluate our model on Market-1501 and DukeMTMC-reID. Results show that HCT achieves 56.4% mAP on Market-1501 and 50.7% mAP on DukeMTMC-reID which surpasses state-of-the-arts a lot in fully unsupervised re-ID and even better than most unsupervised domain adaptation (UDA) methods which use the labeled source dataset. Code will be released soon on https://github.com/zengkaiwei/HCT

Progress and trends in nondestructive testing and evaluation for wind turbine composite blade

Abstract: Wind energy is one of the fastest growing renewable energy resources. It is distinctly important to increase reliability and availability of wind turbines and further to reduce the wind energy cost. Blades are considered to be one of the most critical components in wind turbine system because they convert Kinetic energy of wind into useable power. Blades are fabricated by carbon fiber reinforced polymer (CFRP) or glass fiber reinforced polymer (GFRP). Flaws and damages are inevitable during either fabrication or lifetime of a composite blade. Thus, non-destructive testing (NDT) and structural health monitoring (SHM) for wind turbine blade (WTB) are required to prevent failures and increase reliability in both manufacturing quality control and in-service inspection. In this work, a fully, in-depth and comprehensive review of NDT techniques for WTB inspection was reported based on an orderly and concise literature survey. Firstly, typical flaw and damage occurring in manufacturing progress and in service of WTB were introduced. Next, the developments of visual, sonic and ultrasonic, optical, electromagnetic, thermal and radiographic NDT for composite WTB inspection were reviewed. Thereafter, strengths and limitations of NDT techniques were concluded through comparison studies. In the end, some research trends in WTB NDT have been predicted, for example in combination with SHM. This work will provide a guide for NDT and SHM of WTB, which plays an important role in wind turbine safety control and wind energy cost savings. In addition, this work can benefit the NDT development in the field of renewable energy, such as solar energy, and energy conservation field, such as building diagnosis.

Effective Infrared Small Target Detection Utilizing a Novel Local Contrast Method

Abstract: Effective detection of small targets plays a pivotal role in infrared (IR) search and track applications for modern military defense or attack Consequently, an effective small IR target detection algorithm based on a novel local contrast measure (NLCM) is proposed in this letter Initially, difference of Gaussian band-pass filter is employed to enhance target and suppress background clutter Then, a segmentation operation is implemented to obtain IR local regions of fixed size larger than general IR small target size Finally, the salient map is obtained using the NLCM, and an adaptive threshold is applied to extract the target region Experimental results on two real sequences show that the proposed method has better detection performance compared with conventional baseline methods

Spectrally Constrained MIMO Radar Waveform Design Based on Mutual Information

Abstract: We address the waveform design problem for multiple-input multiple-output (MIMO) radar in spectrally crowded environments. We exploit the mutual information between the target reflections and the target responses as the design metric. To tackle the associated nonconvex optimization problem, we propose an algorithm based on first-order Taylor series approximation as well as minorization–maximization (MM) based algorithms to design the spectrally constrained waveforms. Interestingly, for some scenarios, we can synthesize the globally optimal (spectrally constrained) waveforms with the maximum mutual information. We also show that, through intelligent waveform design, MIMO radar can coexist more efficiently with other communication systems occupying the same spectrum, while suffering from insignificant mutual information losses.