Abstract
Autonomous underwater vehicles (AUVs) with bearing target tracking capability are fundamental and essential. However, they face the problems of high nonlinearity, difficult target trajectory initialization, and poor multi-target tracking (MTT) performance. Consequently, we adopt a novel MTT method for multi-AUV based on the fast Labeled Multi-Bernoulli (LMB) filter. In this method, the LMB filter uses belief propagation (BP) to solve the data association problem quickly and effectively approximate the LMB during the update step. And a Gaussian mixture approximation is used to determine the new potential target trajectory based on individual AUV-bearing measurements. Furthermore, we employ the iterator-corrector strategy to perform the fast LMB filter for multi-AUV. The simulation results show that the method performs well in MTT for multi-AUV using bearing-only measurements.
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