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Updated: Jan 17, 2026

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一种基于学生的t噪声的新型变异贝叶斯方法,用于水下定位.

Haoqian Huang1, Yutong Zhang1, Chenhui Dong1

  • 1College of Artificial Intelligence and Automation, Hohai University, Changzhou 213200, China.

Sensors (Basel, Switzerland)
|September 19, 2025
PubMed
概括

这项研究引入了一种使用学生t分布 (SWVKF-ST) 的新型滑窗变异卡尔曼波器,以提高水下导航的准确性. 该SWVKF-ST方法有效地处理测量异常值,并在具有挑战性的声学环境中改进状态估计.

关键词:
多传感器融合融合技术多种色因素导致的色.滑动窗户是一个滑动窗户.学生的 t 分布.变量贝叶斯式贝叶斯式

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