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基于视频观测的鸟类跟踪系统的雷达解决方案应用。

Application of Radar Solutions for the Purpose of Bird Tracking Systems Based on Video Observation.

机构信息

Bioseco S.A., Budowlanych 68, 80-298 Gdansk, Poland.

Faculty of Mechatronics, Armament and Aerospace, Military University of Technology, Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland.

出版信息

Sensors (Basel). 2022 May 11;22(10):3660. doi: 10.3390/s22103660.

DOI:10.3390/s22103660
PMID:35632076
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9146798/
Abstract

Wildlife Hazard Management is nowadays a very serious problem, mostly at airports and wind farms. If ignored, it may lead to repercussions in human safety, ecology, and economics. One of the approaches that is widely implemented in small and medium-size airports, as well as on wind turbines is based on a stereo-vision. However, to provide long-term observations allowing the determination of the hot spots of birds' activity and forecast future events, a robust tracking algorithm is required. The aim of this paper is to review tracking algorithms widely used in Radar Science and assess the possibilities of application of these algorithms for the purpose of tracking birds with a stereo-vision system. We performed a survey-of-related works and simulations determined five state-of-the art algorithms: Kalman Filter, Nearest-Neighbour, Joint-Probabilistic Data Association, and Interacting Multiple Model with the potential for implementation in a stereo-vision system. These algorithms have been implemented and simulated in the proposed case study.

摘要

野生动物危害管理是当今一个非常严重的问题，主要在机场和风力发电场。如果被忽视，可能会对人类安全、生态和经济产生影响。在小型和中型机场以及风力涡轮机中广泛实施的一种方法基于立体视觉。然而，为了提供长期观察，以确定鸟类活动的热点并预测未来事件，需要一个稳健的跟踪算法。本文的目的是综述广泛应用于雷达科学中的跟踪算法，并评估这些算法应用于使用立体视觉系统跟踪鸟类的可能性。我们进行了相关工作的调查和模拟，确定了五种最先进的算法：卡尔曼滤波器、最近邻、联合概率数据关联和交互多模型，这些算法具有在立体视觉系统中实现的潜力。这些算法已在提出的案例研究中进行了实现和模拟。

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