基于鱼眼镜头相机和平移/倾斜相机的无人机多阶段贝叶斯目标估计

T. Furukawa, Changkoo Kang, Boren Li, G. Dissanayake
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引用次数: 2

摘要

提出了一种用于无人机机动目标位置估计的广义多阶段贝叶斯方法。所提出的方法的主要硬件组件是一个带有鱼眼镜头的相机和另一个带有普通镜头和平移/倾斜单元的相机。在广角视角(AOV)下,鱼眼镜头相机首先检测目标的方位,然后PT相机在其广角视角内捕获目标。递归贝叶斯估计在全局定义的空间中稳定地定位目标。本文还提出了一种针对鱼眼镜头相机的多级检测方法。置信水平是根据每种检测技术的检测概率(POD)来定义的,鱼眼镜头通过逐渐增加POD来实现连续检测。最后由POD广义地推导出观测似然。将该方法应用于多旋翼直升机对移动目标的检测,结果验证了多级贝叶斯方法和多级鱼眼镜头检测方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-stage Bayesian target estimation by UAV using fisheye lens camera and pan/tilt camera
This paper presents a generalized multi-stage Bayesian approach for an unmanned aerial vehicle to estimate the location of a mobile target. The major hardware components of the proposed approach are a camera with a fisheye lens and another camera with a normal lens and a pan/tilt unit. With wide angle of view (AOV), the fisheye lens camera first detects the bearing of the target, and the PT camera next captures the target in its AOV. The recursive Bayesian estimation steadily locates the target in a globally defined space. The paper also proposes a multi-stage detection method for the fisheye lens camera. The level of confidence is defined in association with the probability of detection (POD) for each detection technique, and the fisheye lens enables continuous detection by gradually increasing the POD. The observation likelihood is finally derived from the POD in a generalized manner. The proposed approach was applied to the detection of a mobile target by a multi-rotor helicopter, and results have demonstrated the effectiveness of both the proposed multi-stage Bayesian approach and multi-stage fisheye lens detection method.
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