Passive Electromagnetic Field Positioning Method Based on BP Neural Network in Underwater 3-D Space

An Underwater Passive Electric Field Positioning Method Based on Scalar Potential

“…Given that scalar potential functions can effectively describe static field distributions, potential measurements offer a convenient and computationally simplified approach to data processing, thereby favoring practical applications [13]. Regarding the choice of location algorithms, two primary approaches emerge: field source parameter fitting based on numerical calculations [14][15][16][17][18], and field source parameter inversion leveraging intelligent optimization algorithms [12,19,20]. The former typically requires fewer measurement points, less computational intensity, and faster operation speeds; however, it also exhibits a strong dependence on initial values and limited noise resilience and is primarily suitable for near-field applications.…”

“…After introducing the parameter-adaptive strategy, in order to consider the anti-noise ability and convergence of the algorithm, it is necessary to add a boundary mutation processing mechanism [34] as an improved supplement to the boundary absorption processing and random reproduction processing-that is, to judge the individuals in the solution space to cross the boundary and to provide two mutation opportunities to the individuals v j that exceed the search boundary. The first mutation strategy is shown in Formula (19), and the second mutation strategy is shown in Formula (28). If the individual still crosses the boundary after two mutations, an individual is randomly generated in the solution space to replace the crossover individual.…”