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An Algorithm for Power Line Detection and Warning Based on a Millimeter-Wave Radar Video

机译:基于毫米波雷达视频的电力线检测与预警算法

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Power-line-strike accident is a major safety threat for low-flying aircrafts such as helicopters, thus an automatic warning system to power lines is highly desirable. In this paper we propose an algorithm for detecting power lines from radar videos from an active millimeter-wave sensor. Hough Transform is employed to detect candidate lines. The major challenge is that the radar videos are very noisy due to ground return. The noise points could fall on the same line which results in signal peaks after Hough Transform similar to the actual cable lines. To differentiate the cable lines from the noise lines, we train a Support Vector Machine to perform the classification. We exploit the Bragg pattern, which is due to the diffraction of electromagnetic wave on the periodic surface of power lines. We propose a set of features to represent the Bragg pattern for the classifier. We also propose a slice-processing algorithm which supports parallel processing, and improves the detection of cables in a cluttered background. Lastly, an adaptive algorithm is proposed to integrate the detection results from individual frames into a reliable video detection decision, in which temporal correlation of the cable pattern across frames is used to make the detection more robust. Extensive experiments with real-world data validated the effectiveness of our cable detection algorithm.
机译:电力线撞击事故是诸如直升机等低空飞行的飞机的主要安全威胁,因此,对电力线的自动警告系统是非常需要的。在本文中,我们提出了一种从有源毫米波传感器的雷达视频中检测电力线的算法。霍夫变换用于检测候选行。主要挑战在于,由于地面返回,雷达视频非常嘈杂。噪声点可能落在同一条线上,这导致霍夫变换后的信号峰值类似于实际的电缆线。为了区分电缆线和噪声线,我们训练了支持向量机进行分类。我们利用布拉格图案,这是由于电磁波在电源线的周期性表面上的衍射所致。我们提出了一组功能来代表分类器的布拉格模式。我们还提出了一种切片处理算法,该算法支持并行处理,并改善了杂乱背景中电缆的检测。最后,提出了一种自适应算法,将来自单个帧的检测结果集成到一个可靠的视频检测决策中,其中跨帧使用电缆模式的时间相关性,以使检测更加可靠。使用实际数据进行的大量实验验证了我们的电缆检测算法的有效性。

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