Enhancing the autonomous navigation and countermeasures capabilities of unmanned ships through artificial intelligence is a key technological innovation to enhance the effectiveness of maritime operations. The following analysis is carried out from the dimensions of technical realization, combat scenario adaptation, and ethical safety.： ###1. Intelligent upgrade of autonomous navigation system 1. **Multi-modal perception fusion** -Heterogeneous sensor arrays of optical/infrared/synthetic aperture radar are used to align cross-modal features through the Transformer architecture to eliminate the perceptual blind spots caused by maritime fog/electromagnetic interference. -Dynamic Bayesian network evaluates sensor confidence in real time, such as millimeter-wave radar, which automatically increases its weight in heavy rain. 2. **Strengthen learning and navigation algorithms** -Build a high-precision digital twin environment at sea, using PPO algorithm for million-order virtual voyage training -Design composite reward functions: balance route efficiency (DTW dynamic time regularization), concealment (radar scattering cross-section optimization), energy consumption (path curvature constraints) 3. **Distributed co-positioning** -SLAM point cloud data is shared between ships through a laser communication chain, and the federation learns to update the shared feature library. -The tightly coupled design of quantum inertial navigation and GPS spoofing detection module, the positioning error is controlled at CEP≤3 meters ### 2. Construction of intelligent confrontation system 1. **Adversarial game decision-making** -Build a GAN network for soldier push of the red and blue programs, the generator simulates the enemy's electronic warfare strategy, and the discriminator optimizes the counter-control plan -Online intensive learning realizes the dynamic evolution of confrontation strategies and delays response<200ms 2. **Intelligent management of electromagnetic spectrum** -Cognitive radio combined with Deep Q Network (DQN) to realize autonomous optimization of frequency hopping mode -Fingerprint recognition of radiation sources based on small sample learning, which can identify more than 90% of unknown radar models 3. **Multi-domain deception tactics** -Generate an adversarial network (GAN) to synthesize the infrared characteristics of a three-dimensional ship to achieve 1:N virtual target projection -Adaptive modulation of sonar bait (Wasserstein GAN generates personalized voiceprint) ###3. System toughness enhancement design 1. **Anti-destructive self-healing network** -The digital twin mirrors the operating state in real time, and quickly reconstructs the control model through migration learning when it is damaged. -TEE-based trusted execution environment, defense model against poisoning attacks 2. **Game theory-driven resource scheduling** -Steinkolberg game model optimizes the energy distribution of the bait/main system -Federal learning guarantee that the damage to a single ship will not affect the group knowledge base ###4. Test and verification system 1. **Meta Universe Proving Ground** -Construct a virtual marine environment containing Coriolis force/ocean current disturbances - Inject 200+ confrontation scenarios such as GPS spoofing/AIS forgery 2. **Bayesian optimization acceleration** -Converge the curve through the Gaussian process regression prediction algorithm to reduce the number of actual installation tests by 30% ###5. Ethical Safety framework 1. **Interpretable AI module** -Visual decision-making path of SHAP value to meet the requirements of the weapon system review of the Geneva Convention -Set up a Moral restraint layer (Moral Layer) to disable the interference behavior of civilian ships 2. **Human-in-loop hierarchical control** -Manual veto power is reserved in the OODA ring, and key decisions need to be confirmed at level 3 -Set up a remote abort channel with asymmetric encryption The current technological bottleneck lies in the collaborative stability of multiple agents in a complex electromagnetic environment. It is recommended to give priority to the development of a migration learning framework to enhance cross-scenario adaptability. The U.S. Navy has verified part of the technology path in the "Ghost Fleet" program, and care needs to be taken to avoid the systemic risks caused by algorithm homogenization. In the next 12-18 months, the integration of attention mechanisms and physical models will likely break through the threshold of the minimum target recognition rate.