The use of artificial intelligence (AI) technology to enhance the concealment and breakthrough defense capabilities of drones can be carried out from the perspective of the following multi-dimensional technological integration： --- ###**First, improve concealment** 1. **Intelligent dynamic path planning** -**Enhanced learning (RL) adaptive obstacle avoidance**: Real-time analysis of threat heat maps from radar, infrared, and optical sensors through the RL model, combined with the terrain database to generate a three-dimensional low-altitude breakthrough path (such as close to mountains and buildings), and dynamically adjust the flight altitude and speed. For example, the **Deep deterministic strategy gradient (DDPG)** algorithm is used to pre-train the UAV's strategy to deal with sudden radar exposure in a simulation environment. -**Game theory optimization path**: Construct a game model of drones and defense systems, predict the law of enemy radar activation and scan blind spots, and use **Monte Carlo tree search (MCTS)**To select the path with the lowest probability of being detected. 2. **Multi-spectrum stealth enhancement** -**AI-driven material and shape optimization**: Use **To generate an adversarial network (GAN)** To simulate the radar scattering cross-section (RCS) of different shapes and material combinations to generate a stealth shape with a fractal structure or radar wave-absorbing material coating. For example, the surface texture of a metamaterial is generated to scatter radar waves in a specific frequency band. -**Dynamic electromagnetic feature control**: Through **Real-time reinforcement learning**Adjust the impedance distribution of the intelligent skin on the surface of the UAV to actively offset the reflection of electromagnetic waves in a specific direction, or imitate the environmental background (such as the RCS characteristics of birds). 3. **Active electronic confrontation** -**Cognitive electronic warfare system**: Deploy **Deep neural network (DNN)**Real-time analysis of enemy radar signal characteristics (such as pulse repetition frequency and modulation method), and use **confrontation sample generation technology**To transmit customized interference waveforms (such as coherent drag interference or false target injection)). For example, a spoofed signal that is highly similar to the real echo is generated by **Variational autoencoderator (VAE)**. -**Multi-DRONE collaborative interference**: Multiple aircraft share interference strategies through **Federal learning** to form a distributed network of interference nodes, covering different frequency bands and azimuths, making it impossible for enemy radars to filter effectively. --- ###**2. Break through the defense system** 1. **Threat perception and intelligent avoidance** -**Multi-modal sensor fusion**: The Transformer model is used to integrate visible light, infrared, SAR radar, and electronic support measures (ESM) data to build a real-time threat map. For example, identify the thermal characteristics of an air defense missile launcher and the direction of the radar beam, and combine **YOLOv7**target detection to achieve rapid positioning of millimeter wave radar. -**Predictive avoidance strategy**: Use the **Short- and long-term memory network (LSTM)**to predict the trajectory of the missile (such as the active radar guidance stage of the 48N6E3 missile of the S-400), and calculate the optimal avoidance maneuver (such as high-speed dive combined with foil interference). 2. **Adversarial machine learning attacks** -**Sensor spoofing**: For enemy image recognition systems, specific textures are sprayed on the surface of the drone through **adversarial patches**, causing the optical/infrared imaging system to misclassify it as birds or clouds. For example, use **Projection attack** to project a dynamic confrontation pattern on the body. -**Radar recognition system attack**: Generate **Adversarial RCS modulated signal** to enable the CNN classifier in the enemy radar signal processing chain to identify the DRONE as a false target (such as a civil aviation airliner). **FGSM (fast gradient notation)** can be used to optimize the interference waveform. 3. **Group intelligent collaborative breakthrough** -**Heterogeneous drone cluster operations**: Coordinate reconnaissance, interference, and attack drones through the framework of Centralized training-Distributed Execution (CTDE). For example, **In the "Loyal Wingman" mode**, small drones are used as bait to trigger enemy radars, and large drones then carry out saturation attacks. -**Self-organizing bee colony algorithm**: Particle swarm optimization (PSO)** is used to achieve dynamic formation adjustment. For example, some UAVs carried out “suicide” electromagnetic pulse attacks to destroy radar nodes, while the rest of the UAVS took advantage of the gap between the system restarts to break in. 4. **Autonomous decision-making and task reconstruction** -**Real-time task planning engine**: Dynamically adjust the task priority based on the Deep Q Network (DQN)**. For example, when the Thaad system's AN/TPY-2 radar activation is detected, it automatically switches to ultra-low altitude flight and releases the active bait. -**Cross-domain collaborative learning**: Through Meta-Learning**, UAVs can quickly adapt to new defense systems. For example, the mirror deflection strategy to deal with laser weapons is pre-trained in a simulated environment, and fine-tuned online in actual combat. --- ###**3. Supporting technical challenges** 1. **Edge computing and lightweight model**: Deploy **Knowledge distillation**technology to compress neural network models (such as ResNet-50 compressed into MobileNet architecture), and combine **Neural architecture search (NAS)**to optimize computing efficiency to meet the computing power limitations of airborne embedded devices. 2. **Anti-jamming communication**: Adopts the frequency hopping sequence optimized by enhanced learning** and the error correction coding based on LDPC code**, combined with BLOCKCHAIN technology to realize the decentralized anti-jamming of cluster communication. 3. **Confrontation and defense technology