多假设跟踪和多静态主动声纳系统融合技术

Kathrin Seget, A. Schulz, U. Heute
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引用次数: 7

摘要

在多静态声纳系统中,来自多个传感器的数据经过融合后,其跟踪效果要优于仅有一对信号源-接收器的系统。虽然集中式融合在理论上可获得最佳融合结果,但分布式融合仍具有相当大的优势。由于传送到融合节点的数据较少,因此与集中式融合相比,分布式融合所需的数据传输带宽更少,处理数据的计算负荷也更小。本文提出的分布式融合方法无需执行轨迹到轨迹关联。融合是通过应用额外的多假设跟踪器来跟踪在单传感器阶段过滤的状态。本文提出的融合技术适用于两个不同的多静态声纳数据集,并与集中式融合方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Hypothesis Tracking and fusion techniques for multistatic active sonar systems
In multistatic sonar systems data from several sensors are fused to obtain an improved tracking result compared to systems with a single source-receiver pair. Although centralised fusion leads to a theoretical optimal fusion result, distributed fusion features considerable advantages. As less data have to be passed to a fusion node, distributed fusion requires less bandwidth to transmit data as well as less computational load to process the data compared to centralised fusion. In this paper a distributed fusion approach is presented without performing a track-to-track association. Fusion is done by applying an additional Multi-Hypothesis Tracker to track states filtered at the single sensor stages. The presented fusion technique is applied to two distinct multistatic sonar datasets and compared to a centralised fusion approach.
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