Remote Tracking to Monitor Ship Tracks at or near the Water Surface

Nosov, V. N.; Kaledin, S. B.; Иванов, С. Г.; Timonin, Vadim

doi:10.1134/s0030400x19100187

Cited by 4 publications

(1 citation statement)

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“…In the process of measuring the trajectory traces and predicting the tracks, radar scanning technology, and ship-borne AIS technology are the two main technical means for locating ship information [4,37]. Radar scanning technology can capture the real-time tracks of the ship, but it is susceptible to the surrounding air humidity, density, and actual installation conditions of the radar.…”

Section: Ais Tracks Formationmentioning

confidence: 99%

A Track Initiation Algorithm Using Residual Threshold for Shore-Based Radar in Heavy Clutter Environments

Zhang

Liu

et al. 2020

JMSE

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There is a large error in the actual radar trajectory tracking process. Track initiation is the primary problem in trajectory tracking and the first step in target tracking. The current track initiation algorithms are greatly affected by heavy clutter environments, so it is necessary to propose an algorithm to solve the problem of low track initiation efficiency. This paper presents a track initiation algorithm using a residual threshold in heavy clutter environments. The falling probability of measured value and decision threshold are used to determine the correlation window. The angle limiting condition is added to establish the track association, and the residual threshold is used to further eliminate the false tracks. The initial track experiment with the trajectory data in the sea near Rizhao Port shows that the algorithm is superior to the traditional logic method and Kalman filter method in track quality. The experiment uses the AIS buffer zone to calculate track initiation probability and uses the multi-region AIS trajectory data for verification. The experimental result shows that track initiation probability with the proposed algorithm in this paper can reach 92.31%.

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Section: Ais Tracks Formationmentioning

confidence: 99%