Optimization UUV Self-localization Method Based on Distributed Network

With the proposal of carbon capture and storage technology, seabed carbon storage technology has become an effective way to change climate change. This paper proposes an optimization UUV self-localization method to solve the problem of less accurate feedback leakage location of seabed carbon sequestration. The method employs a hyperbolic intersection model and uses an improved generalized cross correlation algorithm based on PATH weighting for time delay estimation. The localization model is also solved using the joint Chan&Taylor algorithm. The method enables accurate feedback on the leak location, ensuring timely and efficient repair. Simulation results show that the improved delay detection algorithm is more accurate than the traditional PATH-weighted generalized correlation algorithm in a low signal-to-noise environment; the selection of suitable initial values for Taylor expansion also improves the accuracy and efficiency of the joint Chan&Taylor algorithm. The experimental test results show that the maximum error in a 1.5km*1.5km localization area is less 20m, indicating that the method has superior localization accuracy and is more valuable to be utilized.