Magnetic anomaly detection technology for underwater vehicle

Magnetic anomaly detection technology holds significant application value in target detection for underwater vehicles. To address the challenge of effectively extracting magnetic anomaly signals in sea wave noise interference, a joint detection method combining improved Kalman filtering and orthogonal basis decomposition is proposed. Firstly, a composite magnetic model of an underwater vehicle in arbitrary navigation is constructed through numerical simulation to generate simulated magnetic anomaly signals. Secondly, a magnetic anomaly detection dataset superimposed with sea wave noise is developed by integrating a finite-depth multilayer seawater magnetic field noise model, seawater conductivity data, and sea wave spectrum characteristics. Subsequently, an improved Kalman filtering algorithm is employed to effectively suppress sea wave noise and enhance signal quality. Finally, the orthogonal basis decomposition method is utilized to achieve efficient detection of magnetic anomaly signals. The results demonstrate that in conditions with a signal-to-noise ratio of approximately -15dB and a detection platform speed below 60 m/s, the proposed method maintains a high detection probability, verifying its robustness in complex sea wave noise environments.