• Journal of Space Technology and Applications
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• v.2 no.2
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• pp.121-136
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• 2022

Automatic Identification System used in ship communication is required for marine control way, including monitoring of vessel operation in coastal and exchanging of information for safety navigation between them. But, it uses a very high frequency band of approximately 160 MHz, and at the same time, due to the curvature of Earth, there is a limit to the communication distance. Several demonstrations were made successfully over satellite, but not much work has been done yet through cube-satellite which has low-orbit at 500 km altitude. Here, we demonstrate a reception test of AIS (automatic identification system) receiver for a cube-satellites using software-defined radio (SDR). We collected AIS data from ship at port of Busan, Korea, using R8202T2 SDR and established to transmit them using Adam-Pluto and Matlab Simulink. The process of weakening the signal strength to a satellite was constructed using attenuator. Through above process, we demonstrated whether AIS data was successfully received from the AIS payload.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.219-228
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• 2024

Vessels can operate with their Automatic Identification System (AIS) turned off, prompting the development of strategies to identify them. Among these, utilizing satellites to collect radio frequency (RF) data in the absence of AIS has emerged as the most effective and practical approach. The purpose of this study is to develop a matching algorithm for RF with AIS data and find the RF's applicability to classify a suspected ship. Thus, a matching procedure utilizing three RF datasets and AIS data was employed to identify ships in the Yellow Sea and the Korea Strait. The matching procedure was conducted based on the proximity to AIS points, ensuring accuracy through various distance-based sections, including 2 km, 3 km, and 6 km from the AIS-based estimated points. Within the RF coverage, the matching results from the first RF dataset and AIS data identified a total of 798 ships, with an overall matching rate of 78%. In the cases of the second and third RF datasets, 803 and 825 ships were matched, resulting in an overall matching rate of 84.3% and 74.5%, respectively. The observed results were partially influenced by differences in RF and AIS coverage. Within the overlapped region of RF and AIS data, the matching rate ranged from 80.2% to 98.7%, with an average of 89.3%, with no duplicate matches to the same ship.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.297-303
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• 2009

Automatic Identification System (AIS) is a VHF radio broadcasting system where transmits packets of data via VHF data link. It enables vessels and coastal-based station that equipped with AIS equipment to send and receive useful information. This information can be help in situational awareness and provide a means to assist in collision avoidance. In addition, AIS can be use as Aid-To-Navigation, by providing the location and additional information on buoys and lights. Besides, it can also contain details information in meteorological status of a particular ship location. This paper presents the standalone AIS system that able to receive and report own ship location, meteorological data collection and broadcast safety related information if necessary. With the unique ship's MMSI number, all the information of that particular ship can be monitor by using AIS program written in C++ programming language.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.92-99
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• 2016

AIS(Automatic Identification System) is an vessel traffic management system which exchanges vessel data with other nearby ships, AIS base stations using VHF band. A domestic AIS base station is located along coast lines or island. So it is difficult to collect vessel data from the ocean. To solve this problem, we adopted AIS payload on the low earth orbit satellite. The AIS payload on the satellite is interfaced with OBC(On-Board Computer) via UART and the FSW(Satellite Flight Software) manages it. The FSW have to receive AIS command from ground station and forward to AIS payload. Similarly FSW have to receive response, OBP, OGP data from AIS payload and it is downlink to the ground station. So in this paper we describe the FSW design & implementation for AIS payload.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.430-432
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• 2013

AIS(Automatic Identification System) is a radionavigation equipment for exchanging safety related information between ships as well as ship and shore station, introduced by SOLAS convention and widely used especially in vessel traffic service. However, in an area of broad communication coverage of coast station, various problems may appear in receiving AIS data from ships. In this paper, AIS problems that may happen in broad communication coverage of coast station are analyzed using received data.

• The Journal of the Acoustical Society of Korea
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• v.37 no.3
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• pp.129-138
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• 2018

In port and coastal areas where ship traffic is frequent, ship noise dominantly influences underwater noise in low frequency band below 1 kHz. In this paper, we propose a modeling method to estimate the underwater shipping noise using the voyage information of ship observed in AIS (Automatic Identification System). For the purpose of ship noise modeling, the navigation information of the vessels operating in the southern part of Jeju was observed using AIS and underwater noise was measured by installing a hydrophone in the experimental area to verify the modeled ship noise. AIS data were used to model the noise level of ship and compared with measured underwater noise. The variation of noise level with time was found to be similar, and the cause of the error was discussed. Through this study, it was confirmed that the noise level of ship can be estimated within 5 dB error range using AIS data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.305-308
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• 2014

AIS(Automatic Identification System) is a radionavigation equipment for exchanging safety related information between ships as well as ship and shore station, introduced by SOLAS convention and widely used especially in vessel traffic service. The dynamic data of AIS is transmitted at intervals of 2 second to 3 minutes depending on ship's navigational status and speed. However, so often times it happens that some AIS data can not be received due to increasing AIS traffic and it's time slot confliction. In this paper, a revised reporting intervals of AIS dynamic data is proposed in order to decrease AIS data link load.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.103-112
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• 2012

We demonstrate the preliminary results of ship detection application using synthetic aperture radar (SAR) and automatic identification system (AIS) together. Multi-frequency and multi-temporal SAR images such as TerraSAR-X and Cosmo-SkyMed (X-band), and Radarsat-2 (C-band) are acquired over the West Sea in South Korea. In order to compare with SAR data, we also collected an AIS data. The SAR data are pre-processed considering by the characteristics of scattering mechanism as for sea surface. We proposed the "Adaptive Threshold Algorithm" for classification ship efficiently. The analyses using the combination of the SAR and AIS data with time series will be very useful to ship detection or tracing of the ship.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.257-269
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• 2023

This paper presents a method for detecting faults in data obtained from the Automatic Identification System (AIS) of surface vessels. The data include latitude, longitude, Speed Over Ground (SOG), and Course Over Ground (COG). We derive two methods that utilize two models: a constant state model and a derivative augmented model. The constant state model incorporates noise variables to account for state changes, while the derivative augmented model employs explicit variables such as first or second derivatives, to model dynamic changes in state. Generally, the derivative augmented model detects faults more promptly than the constant state model, although it is vulnerable to potentially overlooking faults. The effectiveness of this method is validated using AIS data collected at a harbor. The results demonstrate that the proposed approach can automatically detect faults in AIS data, thus offering partial assistance for enhancing navigation safety.