Practical Moving Target Detection in Maritime Environments Using Fuzzy Multi-sensor Data Fusion
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Practical Moving Target Detection in Maritime Environments Using Fuzzy Multi-sensor Data Fusion Wenwen Liu1 • Yuanchang Liu1 • Bryan Adam Gunawan1 • Richard Bucknall1
Received: 25 February 2020 / Revised: 23 July 2020 / Accepted: 10 September 2020 The Author(s) 2020
Abstract As autonomous ships become the future trend for maritime transportation, it is of importance to develop intelligent autonomous navigation systems to ensure the navigation safety of ships. Among the three core components (sensing, planning and control modules) of the system, an accurate detection of target ships’ navigation information is critical. Within a typical maritime environment, the existence of sensor noises as well as the influences generated by varying environment conditions largely limit the reliability of using a single sensor for environment awareness. It is therefore vital to use multiple sensors together with a multi-sensor data fusion technology to improve the detection performance. In this paper, a fuzzy logic-based multi-sensor data fusion algorithm for moving target ships detection has been proposed and designed using both AIS and radar information. A two-stage fuzzy logic association method has been particularly developed and integrated with Kalman filtering to achieve a computationally efficient performance. The effectiveness of the proposed algorithm has been tested and validated in simulations where multiple target ships are transiting with complex movements. Keywords Fuzzy multi-sensor data fusion Unmanned surface vehicles (USVs) Maritime navigation Automatic Identification System (AIS)
& Yuanchang Liu [email protected] 1
Department of Mechanical Engineering, University College London, Torrington Place, London WC1E 7JE, UK
1 Introduction In order to increase the degree of autonomy and better ensure navigation safety, unmanned surface vehicle (USVs) should not only be able to acquire their own accurate and reliable navigational data, but to also perceive the surrounding environment to avoid collision risks. Normally, static obstacles, such as small islands and coastlines, can be determined from commercial nautical charts with sufficient accuracy. Detecting dynamic obstacles, such as moving target ships (TS), is a more dynamic challenge. Automatic Identification System (AIS) can provide reasonably accurate navigational data of TSs, and a simple AIS receiver can be powered at similar low-voltage levels that are also adequate for the navigation sensor system of an autonomous USV. However, the application of AIS may become compromised while the USV is operating at sea encountering with multiple targets. Tracking all the surrounding targets to analyse the collision risks is essential to ensure its safety. Although, an increasing number of vessels are installing AIS devices, only large ships over 300 gross tonnage are required to instal transponders. Small vessels are normally equipped with AIS receivers, so that they would only be aware of other target ship’s information instead of sending their own informat
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