基于快速LMB滤波的多auv单方位多目标跟踪方法

Yuexing Zhang, Yiping Li, Shuo Li, J. Zeng, Liang Li, Gaopeng Xu, Peiyan Gao
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摘要

具有方位目标跟踪能力的自主水下航行器是水下航行器发展的基础和必要条件。然而,它们面临着高非线性、目标轨迹初始化困难和多目标跟踪性能差的问题。因此,我们采用了一种基于快速标记多伯努利(LMB)滤波器的多auv MTT方法。在该方法中,LMB滤波器使用信念传播(BP)来快速解决数据关联问题,并在更新步骤中有效地逼近LMB。基于单个auv方位测量,采用高斯混合近似确定新的潜在目标轨迹。此外,我们采用迭代校正策略对多水下机器人进行快速LMB滤波。仿真结果表明,该方法在多水下机器人的单方位MTT测试中具有良好的性能。
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A Multi-AUV Bearings-Only Multi-target Tracking Method Based on the Fast LMB Filter
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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