In the vast expanse of the open sea, keeping tabs on every vessel is no easy feat. Small boats, in particular, can be a challenge to detect due to their low radar reflection intensity. This is where the work of Yongfeng Suo, a researcher from the Navigation College at Jimei University in Xiamen, China, comes into play. Suo and his team have developed a novel approach to enhance the detection of small vessels, a breakthrough published in the Journal of Marine Science and Engineering.
The team’s solution revolves around the Constant False Alarm Rate (CFAR) algorithm, a standard tool in radar systems. The problem? Traditional CFAR algorithms struggle to pick up small vessels, leading to missed detections and potential maritime safety issues. Suo’s team tackled this by integrating Automatic Identification System (AIS) data, a system used by vessels to broadcast their identity, position, course, and speed.
Here’s where it gets interesting. The team used an iTransformer model, a type of artificial intelligence, to analyze the AIS data and adjust the CFAR thresholds. “We compared traditional CFAR processing results of radar data with AIS data to identify some special targets,” Suo explained. “These special targets, which possessed AIS information but remained undetected by radar, enabled the iTransformer model to generate more reasonable CFAR threshold adjustments.” In simpler terms, the AI learned to lower the radar’s sensitivity in areas where small vessels were likely to be, making them easier to spot.
The results speak for themselves. In simulated scenarios, the team’s method reduced the missed detection rate of small vessels by a whopping 73.4% and the false-alarm rate by 60.7%. This is a significant leap forward in maritime safety and supervision.
So, what does this mean for the maritime industry? For starters, it could greatly enhance maritime safety by making it easier to detect small vessels, including those engaged in illegal activities like smuggling or unauthorized fishing. It could also improve traffic monitoring in busy ports and waterways, reducing the risk of collisions.
Moreover, this technology could have commercial applications. Shipping companies could use it to better track their smaller vessels, improving fleet management and reducing the risk of losses. It could also be a boon for maritime law enforcement, making it easier to detect and intercept vessels engaged in illegal activities.
In the words of Suo, “Our study provides a new solution for ensuring maritime navigation safety and strengthening illegal supervision, while also offering new technical references for the field of radar detection.” With such promising results, it’s clear that this technology has the potential to make a significant impact on the maritime industry.