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Automatic identification of ARPA radar tracking vessels by CCTV camera system

CCTV 카메라 시스템에 의한 ARPA 레이더 추적선박의 자동식별

  • Published : 2009.08.31

Abstract

This paper describes a automatic video surveillance system(AVSS) with long range and 360$^{\circ}$ coverage that is automatically rotated in an elevation over azimuth mode in response to the TTM(tracked target message) signal of vessels tracked by ARPA(automatic radar plotting aids) radar. This AVSS that is a video security and tracking system supported by ARPA radar, CCTV(closed-circuit television) camera system and other sensors to automatically identify and track, detect the potential dangerous situations such as collision accidents at sea and berthing/deberthing accidents in harbor, can be used in monitoring the illegal fishing vessels in inshore and offshore fishing ground, and in more improving the security and safety of domestic fishing vessels in EEZ(exclusive economic zone) area. The movement of the target vessel chosen by the ARPA radar operator in the AVSS can be automatically tracked by a CCTV camera system interfaced to the ECDIS(electronic chart display and information system) with the special functions such as graphic presentation of CCTV image, camera position, camera azimuth and angle of view on the ENC, automatic and manual controls of pan and tilt angles for CCTV system, and the capability that can replay and record continuously all information of a selected target. The test results showed that the AVSS developed experimentally in this study can be used as an extra navigation aid for the operator on the bridge under the confusing traffic situations, to improve the detection efficiency of small targets in sea clutter, to enhance greatly an operator s ability to identify visually vessels tracked by ARPA radar and to provide a recorded history for reference or evidentiary purposes in EEZ area.

Keywords

Automatic video surveillance system(AVSS);ARPA radar;TTM signal;CCTV camera system;Vessel identification

References

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Cited by

  1. Acoustic Tracking of Fish Movements in an Artificial Reef Area Using a Split-beam Echo Sounder, Side-scan and Imaging Sonars at Suyeong Man, Busan, Korea vol.46, pp.3, 2013, https://doi.org/10.5657/KFAS.2013.0273
  2. Image Analysis Module for AR-based Navigation Information Display vol.27, pp.3, 2013, https://doi.org/10.5574/KSOE.2013.27.3.022
  3. Target recognition for coastal surveillance based on radar images and generalised Bayesian inference vol.12, pp.2, 2018, https://doi.org/10.1049/iet-its.2017.0042