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Improved particle swarm optimization algorithm for submarine cable localization based on magnetic detection
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AI
DOI：10.1016/j.oceaneng.2025.123769.png)
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Abstract
En 中文
Due to the complex structure and irregular magnetic field distribution of three-core alternating submarine cables, traditional positioning methods relying on precise parameters are easily affected by interference such as current fluctuations and complex underwater environments, making it difficult to achieve high-precision positioning. To solve the above problems, an approximate distribution model of a three-core submarine cable is derived by introducing magnetic flux density, in which the effect of armor and lead sheath is taken into account. On the basis of this model, a new localization method based on improved Beetle Particle Swarm Optimization (BPSO) algorithm is proposed by combining a dual three-axis magnetic sensor array and an underwater robot. The algorithm is heuristic which reduces the dependence on parameter accuracy and is proven to be convergent. The simulation results show that the proposed method has almost no error in the absence of interference, and can still maintain good positioning accuracy under current fluctuations and various interferences, which illustrate the effectiveness and robustness of the proposed method.
Keywords:
Submarine cable
Electromagnetic localization
Underwater robot
Electromagnetic detection