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Automatic Identification System Data Fusion80Marine Research of the National Academy of Marine ResearchDOI: 10.29677/MR.202406_4(1).0006 Surrounded by the sea, Taiwan is located in the eastern part of Asia, where East Asia and South Asia converge, and occupies a central position in the East Asian archipelago. Therefore, the maritime transportation in its surrounding areas is highly developed. To the west, across the Taiwan Strait, lies China. To the south, through the Bashi Strait, one can reach countries such as the Philippines, Vietnam, Singapore, and Malaysia.To the north, through the East China Sea and the South China Sea, one can reach countries like Japan and South Korea. Taiwan's exceptional geographical location has made it a crucial transportation hub in Asia and the Western Pacific. It plays a significant role in various aspects, including the economy and transportation within the Asian region. The waters near Taiwan are characterized by a high number of vessels, bustling maritime tradeactivities, and frequent fishing operations. With limited navigational space in the surrounding seas of Taiwan, the increasing variety of vessels poses a significant risk of accidents during navigation. As maritime safety concerns have gained significant attention from countries worldwide, the International Maritime Organization (IMO) has issued the \OLAS)\(RECOMMENDATION ITU-R M.2092-1, 2022), which mandates the installation of the AutomaticIdentification System (AIS) on all passenger and cargo ships with a gross tonnage of 300 tons or above for international voyages, as well as cargo ships not engaged in international voyages with a gross tonnage of 500 tons or above. While navigational instruments and equipment such as radar charts and Automatic Radar PlottingAids (ARPA) have the capability to identify vessels at sea, their primary purpose is to provide relevantnavigational information during ship operations. However, they are unable to acquire and relay other dynamic vessel information such as longitude, latitude, heading, and speed of neighboring vessels. This limitation hinderseffective measures to avoid and mitigate potential maritime accidents, including collisions that can lead to capsizing and grounding. In response to the increasing volume of various types of vessels entering and leaving ports (Nieh, et al., 2019) and to ensure safe navigation in the waters surrounding Taiwan, the Maritime and Port Bureau, Ministry of Transportation and Communications (MOTC) revised the \ (Huang et al., 2019) in 2008 based on the International Convention for the Safety of Life at Sea. According to these regulations, all types of vessels with a gross tonnage of 20 tons or above are required to be equipped with the AIS, and nationwide AIS-related hardware facilities have been established. These measures aim to ensure the safety of vessel navigation and acquire precise dynamic data such as ship speed and heading. In the research project titled \ Suand Xu from the Harbor and Marine Technology Center in 2021, the authors discussed how to utilize historical dynamic data from ships' AIS to analyze vessel trajectories in the waters surrounding Taiwan and compile statistics on various types of vessels entering and leaving major commercial ports. The purpose of this study is to provide a basis for maritime traffic management by the competent authorities and reduce the probability of ship collisions at sea. Therefore, the accuracy and correctness of AIS data significantly impact the accuracy of the analysis. In the 2020 paper \g Taiwan\by Huang and Chen et al., several issues regarding the current operation of the AIS were identified. Specifically, the paper highlights instances of missing or incorrect parameters in the AIS data fields of terrestrial AIS base stations receiving data from ships. To address this concern, we utilize AIS receiving stations to collect ship AIS data and verify whether the received data exhibits issues such as missing or incorrect parameters in theaforementioned AIS data fields. Examination of the system database interface for AIS data decoding, depicted in Figure 1, reveals that certain parameters in the AIS data indeed exhibit abnormal conditions.1 INTRODUCTION