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首页> 外文期刊>IEEE sensors journal >Beam Slice-Based Recognition Method for Acoustic Landmark With Multi-Beam Forward Looking Sonar
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Beam Slice-Based Recognition Method for Acoustic Landmark With Multi-Beam Forward Looking Sonar

机译：基于波束切片的多波束前视声纳声地标识别方法

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摘要

Autonomous underwater vehicles (AUVs) have been widely used for many risky underwater tasks. For these tasks, AUVs require navigational aids, such as active beacon-type underwater acoustic landmarks, which are the most widely used. It requires heavy installation loads and regular maintenance with high price sensors. In this paper, we propose a novel localization method in shallow water with a multi-beam forward looking sonar (MFLS), where positioning is based on passive-type acoustic landmarks. The proposed landmark comprises a combination of concrete pillars with a highly reliable and efficient recognition method for the real-time use of AUVs. The proposed landmark system has many advantages in the practical use, such as no maintenance, being strong on the marine bio-fouling, and light installation load with low price concrete pillars. The proposed recognition method is divided into two processes to verify the landmark. First, a pillarlike object is separated from the background, and the height of the pillar is calculated by the length of the shadow, which has a very high recognition rate and accuracy. Through modeling, the distance from the landmark to the MFLS can be calculated. The proposed method stochastically updates the navigation data based on the positional relationship with the landmark. The performance of the proposed landmark and its recognition method is verified through a water tank and field experiments using the AUV (Cyclops). The recognition rate and accuracy are also discussed.
机译：自主水下航行器（AUV）已被广泛用于许多危险的水下任务。对于这些任务，AUV需要导航辅助工具，例如使用最广泛的主动信标型水下声学地标。它需要高昂的价格，需要高昂的安装负担和定期维护。在本文中，我们提出了一种新的浅水定位方法，该方法采用多波束前视声纳（MFLS），其定位基于无源型声学地标。拟议中的地标包括混凝土支柱与用于AUV实时使用的高度可靠和高效的识别方法的组合。所提出的地标系统在实际使用中具有许多优点，例如无需维护，在海洋生物污垢上很坚固，安装成本低且混凝土柱价格低。所提出的识别方法分为两个过程以验证界标。首先，将柱状对象与背景分离，并通过阴影的长度来计算柱状的高度，这具有很高的识别率和准确性。通过建模，可以计算出界标到MFLS的距离。所提出的方法基于与地标的位置关系随机地更新导航数据。通过AUV（Cyclops）的水箱和野外实验验证了拟议地标的性能及其识别方法。还讨论了识别率和准确性。

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