Self-Selective Correlation Ship Tracking Method for Smart Ocean System

In recent years, with the development of the marine industry, navigation environment becomes more complicated. Some artificial intelligence technologies, such as computer vision, can recognize, track and count the sailing ships to ensure the maritime security and facilitates the management for Smart Ocean System. Aiming at the scaling problem and boundary effect problem of traditional correlation filtering methods, we propose a self-selective correlation filtering method based on box regression (BRCF). The proposed method mainly include: 1) A self-selective model with negative samples mining method which effectively reduces the boundary effect in strengthening the classification ability of classifier at the same time; 2) A bounding box regression method combined with a key points matching method for the scale prediction, leading to a fast and efficient calculation. The experimental results show that the proposed method can effectively deal with the problem of ship size changes and background interference. The success rates and precisions were higher than Discriminative Scale Space Tracking (DSST) by over 8 percentage points on the marine traffic dataset of our laboratory. In terms of processing speed, the proposed method is higher than DSST by nearly 22 Frames Per Second (FPS)

Dual-polarized spatial-temporal propagation measurement and modeling in uma o2i scenario at 3.5 GHz

Outdoor-to-indoor (O2I) coverage in urban areas by using the sub-6 GHz (sub-6G) band is important in the fifth generation (5G) mobile communication system. The spatial-temporal propagation characteristics in different polarizations in the 5G spectrum are crucial for the network coverage. In this paper, we measured the urban macrocell (UMa) O2I channels at 3.5 GHz in the space, time, and polarization domains simultaneously. The channel sounder utilized two ±45° polarized antenna arrays. The transmitter (TX) was placed on the rooftop of a five-storey building to emulate a base station and the receiver (RX) was moved in the corridors on different floors in another building to emulate user equipments (UEs). We obtained the small-scale parameters of excess delay, power, and azimuth/elevation of arrival (AoA/EoA) of individual multipath components (MPCs), the propagation profiles of azimuth/elevation power spectrum (APS/EPS) and power delay profile (PDP), and the large-scale parameters including azimuth/elevation spread of arrival (ASA/ESA) and delay spread (DS). Based on the measurement results, we propose the lifted-superposed Laplace distribution (LS-Laplace) function and lifted-superposed normal distribution (LS-Normal) function to model the APS and EPS, respectively, and a three-phase model for the PDP. We find that the ASA and ESA follow the lognormal distribution and the DS has a Rayleigh distribution. We also reveal the impact of surrounding environments and polarization on the channel propagation profiles and statistical characteristics. The measurement results and channel models in this paper provide reference for the design and deployment of the 5G system to exploit the spatial and polarization diversities in the UMa O2I scenario.This work was supported in part by the National Natural Science Foundation of China under Grant 61571370, Grant 61601365, and Grant 61801388, in part by the Key Research Program and Industrial Innovation Chain Project of Shaanxi Province under Grant 2019ZDLGY07-10, Grant 2019JQ-253, and Grant 2019JM-345, and in part by the China Postdoctoral Science Foundation under Grant BX20180262, Grant BX20190287, Grant 2018M641020, and Grant 2018M641019.Scopu