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New Chinese System Identifies Real Targets And Surpasses Decoys In Controlled Tests With High Precision
The China announced significant advancements in its submarine military technology. According to researchers, the new artificial intelligence system applied to torpedoes achieved 92.2% accuracy in distinguishing between real submarines and decoys.
This information was disclosed in April in the Chinese scientific journal Command Control & Simulation, peer-reviewed.
Underwater Disguise Technology In Focus
Underwater decoys are now one of the main defenses against torpedo attacks. They create trails of false bubbles, simulating evasive maneuvers or generating images of multiple targets on sonar.
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Moreover, some operate in coordinated swarms, projecting phantom targets to confuse detection systems.
These tactics are especially effective against supercavitating torpedoes. These devices create a vapor bubble around them, reducing friction with the water and achieving high speeds.
However, supercavitation generates noises that mask true acoustic signals, making it even more challenging to identify real targets.
Researchers Point Out Limitations Of Current Methods
Senior engineers Wu Yajun and Liu Liwen, who lead the project, highlighted the challenges faced by current systems.
“The current target recognition methods for China’s high-speed underwater vehicles prove inadequate in environments saturated with advanced countermeasures, necessitating the urgent development of new approaches for feature extraction and target identification“, they said.
The team also emphasized that only systems equipped with long-range detection and high target recognition rates can ensure sufficient operational effectiveness.
After the application of the new artificial intelligence system, detection rates rose from 61.3% to over 80% when facing sophisticated decoys.
Global Race For Smart Torpedoes
Several countries are seeking to develop increasingly accurate autonomous torpedoes.
The Russian model VA-111 Shkval and current American projects also utilize supercavitation, but all still face difficulties hitting targets at high speeds.
With advancements in underwater acoustics, electronics, and artificial intelligence, the underwater warfare landscape has become even more complex.
Operations now include decoys, electroacoustic countermeasure systems, electronic jammers, and multiple types of weapons operating in the same area.
According to the study, this environment requires systems to accurately identify real targets, even amid various simultaneous threats.
Challenges For Underwater AI
In addition to accuracy, the Chinese team highlighted the complexity of autonomous systems.
As the vehicles operate independently, all decisions must be made without external assistance in real time. This raises the demands on algorithms and embedded computational capabilities.
“The deep learning recognition model proposed in this study, combined with the solution for identifying small samples from generative adversarial networks, allows for effective discrimination of underwater targets. This establishes the technical foundation for field deployment“, the researchers stated.
Rumors About New Submarine Projects
In recent months, reports have emerged that China may be developing a secret submarine.
Experts suggest that the project could become the largest underwater combat drone in the world. However, Chinese authorities have not officially confirmed this information.
Despite the promising results, researchers acknowledge that the reliability of the system still needs to be validated in real combat situations, where unpredictable variables can influence performance.
Furthermore, the intensive use of deep learning raises concerns about the transparency and explanation of decisions made by the systems in high-risk scenarios.
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