Practical Moving Target Detection in Maritime Environments Using Fuzzy Multi-sensor Data Fusion
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 14, 2020
- Source ID
- 10.1007/s40815-020-00963-1
Entities
People
- Bryan Adam Gunawan
- Richard Bucknall
- Wenwen Liu
- Yuanchang Liu
Organizations
- Office of Naval Research
- Royal Society
- University College London