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基于边界约束粒子滤波的多UUV纯方位协同目标跟踪

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面向海上跨域协同中多无人水下航行器(UUV)协同探测水面目标需求,针对现有纯方位目标跟踪算法所面临的滤波器初始化困难和水声数据传输丢包问题,提出了一种基于边界约束粒子滤波的多UUV协同纯方位目标跟踪算法.首先提出了主从式协同探测模型,利用跟随者向领航者上报状态估计结果进行数据融合.其次,基于UUV传感器和目标的先验信息设计了初始阶段可靠粒子生成方法和更新阶段的指标函数粒子权重优化方法.最后提出了基于灰色预测的分布式融合算法,得到目标预测结果.仿真实验将所提算法和其他常见算法进行对比,在通信丢包以及噪声干扰情况下验证了算法的有效性和可行性.
Multi-UUV Collaborative Bearing-only Target Tracking Based on Boundary Constrained Particle Filter
Due to the difficulties of filter initialization and packet loss in underwater acoustic data transmission faced by existing bearing-only target tracking algorithms,a multi-unmanned undersea vehicle(UUV)collaborative bearing-only target tracking algorithm based on boundary constrained particle filter was proposed,so as to meet the demand for multi-UUV collaborative detection of water surface targets in cross-domain collaboration at sea.Firstly,a master-slave collaborative detection model was proposed,which utilized the follower to report the state estimation results to the navigator for data fusion.Secondly,based on the prior information of UUV sensors and targets,a reliable particle generation method for the initial stage and a particle weight optimization method for the indicator function in the update stage were designed.Finally,a distributed fusion algorithm based on gray prediction was proposed to obtain the target prediction results.The simulation experiment compared this algorithm with other common algorithms and verified its effectiveness and feasibility under communication packet loss and noise interference.

unmanned undersea vehiclebearing-only target trackingparticle filtercollaboration detectiondata fusion

韩博、徐红丽、邱少雄、张文睿、茹敬雨

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东北大学信息科学与工程学院,辽宁沈阳,110004

无人水下航行器 纯方位目标跟踪 粒子滤波 协同探测 数据融合

装备预研共用技术项目国家自然科学基金青年科学基金

5091102060462303099

2024

水下无人系统学报
中国船舶重工集团公司第七〇五研究所

水下无人系统学报

CSTPCD
影响因子:0.251
ISSN:2096-3920
年,卷(期):2024.32(2)
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