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通过启用人工智能的声学浮标增强海上领域感知，以实时检测和跟踪快速移动的船只。

Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels.

作者信息

Karst Jeremy, McGurrin Robert, Gavin Kimberly, Luttrell Joseph, Rippy William, Coniglione Robert, McKenna Jason, Riedel Ralf

机构信息

Roger F. Wicker Center for Ocean Enterprise, The University of Southern Mississippi, Gulfport, MS 39501, USA.

BLUEiQ, 10 Fan Pier Boulevard, Boston, MA 02210, USA.

出版信息

Sensors (Basel). 2025 Mar 20;25(6):1930. doi: 10.3390/s25061930.

DOI:10.3390/s25061930
PMID:40293108
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11945802/
Abstract

Acoustic target recognition has always played a central role in marine sensing. Traditional signal processing techniques that have been used for target recognition have shown limitations in accuracy, particularly with commodity hardware. To address such limitations, we present the results of our experiments to assess the capabilities of AI-enabled acoustic buoys using OpenEar™, a commercial, off-the-shelf, software-defined hydrophone sensor, for detecting and tracking fast-moving vessels. We used a triangular sparse sensor network to investigate techniques necessary to estimate the detection, classification, localization, and tracking of boats transiting through the network. Emphasis was placed on evaluating the sensor's operational detection range and feasibility of onboard AI for cloud-based data fusion. Results indicated effectiveness for enhancing maritime domain awareness and gaining insight into illegal, unreported, and unregulated activities. Additionally, this study provides a framework for scaling autonomous sensor networks to support persistent maritime surveillance.

摘要

声学目标识别在海洋传感中一直发挥着核心作用。用于目标识别的传统信号处理技术在准确性方面存在局限性，尤其是在使用商用硬件时。为了解决这些局限性，我们展示了我们的实验结果，以评估使用OpenEar™（一种商用现货软件定义水听器传感器）的人工智能声学浮标检测和跟踪快速移动船只的能力。我们使用三角形稀疏传感器网络来研究估计通过该网络的船只的检测、分类、定位和跟踪所需的技术。重点是评估传感器的操作检测范围以及机载人工智能用于基于云的数据融合的可行性。结果表明，该技术在增强海上领域意识和洞察非法、未报告和无管制活动方面具有有效性。此外，本研究提供了一个扩展自主传感器网络以支持持续海上监视的框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c3a/11945802/a5ce1bc23c08/sensors-25-01930-g011.jpg
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本文引用的文献

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A Path Toward Explainable AI and Autonomous Adaptive Intelligence: Deep Learning, Adaptive Resonance, and Models of Perception, Emotion, and Action.通往可解释人工智能和自主自适应智能之路：深度学习、自适应共振以及感知、情感和行动模型
Front Neurorobot. 2020 Jun 25;14:36. doi: 10.3389/fnbot.2020.00036. eCollection 2020.
2
Tracking of multiple surface vessels based on passive acoustic underwater arrays.基于被动声呐水下阵列的多水面舰艇跟踪
J Acoust Soc Am. 2020 Feb;147(2):EL87. doi: 10.1121/10.0000598.
3
Arbitrary Microphone Array Optimization Method Based on TDOA for Specific Localization Scenarios.
基于 TDOA 的特定定位场景下任意麦克风阵列优化方法。
Sensors (Basel). 2019 Oct 7;19(19):4326. doi: 10.3390/s19194326.