Songtao Lu

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Since closely moving targets exist extensively in the ground moving target tracking, the uncertainty of data association greatly increases making the measurement-to-track association more difficult. Especially, traditional multiple hypothesis tracking (MHT) has high false tracking rate and track swap. This paper first investigates the measurement based(More)
In this communication, we introduce the concept of three dimensional (3D) battery electrodes to enhance the capacity per footprint area for lithium-sulfur battery. In such a battery, 3D electrode of sulfur embedded into porous graphene sponges (S-GS) was directly used as the cathode with large areal mass loading of sulfur (12 mg cm(-2)), approximately 6-12(More)
—Heterogeneous network is a new paradigm in next generation cellular systems, which is promised to significantly improve the spatial spectrum efficiency through overlapped coverage. This however calls for efficient interference management techniques. In this paper, we propose an amplitude-space sharing strategy among the macro-cell user and pico-cell users,(More)
To date, Wald sequential probability ratio test (WSPRT) has been widely applied to track management of multiple hypothesis tracking (MHT). But in a real situation, if the false alarm spatial density is much larger than the new target spatial density, the original track score will be very close to the deletion threshold of the WSPRT. Consequently, all(More)
Lithium-sulfur (Li-S) batteries are a promising candidate of next generation energy storage systems owing to its high theoretical capacity and energy density. However, to date, its commercial application was hindered by the inherent problems of sulfur cathode. Additionally, with the rapid decline of non-renewable resources and active appeal of green(More)
Symmetric nonnegative matrix factorization (SNMF) is equivalent to computing a symmetric nonneg-ative low rank approximation of a data similarity matrix. It inherits the good data interpretability of the well-known nonnegative matrix factorization technique and have better ability of clustering nonlinearly separable data. In this paper, we focus on the(More)