Factor graph weight particles aided distributed underwater cooperative positioning algorithm

The growing scale of marine exploration requires high-resolution underwater localization, which necessitates cooperation among underwater network nodes and consideration of the channel complexity and power efficiency. In this paper, we proposed a factor graph weight particle-aided distributed underwater node cooperative positioning algorithm (WP-DUCP). The algorithm capitalizes on the factor graph and sum-product algorithm to decompose the global optimization to the product of several local optimization functions. Combined with Gaussian parameters used to construct weighted particles and to realize belief transfer, the algorithm shows low complexity and high efficiency and is suitable for energy-restricted and communication distance-limited underwater networks. In terms of convergence, localization resolution, and computational complexity, we conducted simulations and real tests with comparisons to the existing colocalization methods. The results verified the higher resolution of the proposed method with no extra computational burden.