A Miss-Detection Probability Based Thresholding Algorithm for an IR-UWB Radar Sensor

Xuanjun Quan, J. Choi, S. Cho
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引用次数: 1

Abstract

In this paper, we propose a miss-detection probability based thresholding algorithm for an impulse radio ultra-wideband (IR-UWB) radar sensor. The conventional thresholding algorithm like constant false alarm rate (CFAR) is noise oriented algorithm which is focused on false alarm. Unlike this algorithm, the proposed algorithm is focused on miss-detection. For some applications miss-detection is more critical than false alarm, especially for short range application like IR-UWB radar sensor, such as anticollision system, intrusion detection. Moreover, the target signal oriented thresholding algorithm may better aware of the environment. As we know the amplitude of the signal varies depending on the installation height and angle of the radar. Conventional noise oriented thresholding algorithm is lack of considering these parameters. However, since the proposed algorithm is a target signal oriented thresholding algorithm, it is automatically optimized for these parameters. We analyzed the thresholds generated by the CFAR based thresholding algorithm and miss-detection probability based thresholding algorithm in the experiment result.
一种基于超宽带红外雷达传感器漏检概率的阈值算法
本文针对脉冲无线电超宽带(IR-UWB)雷达传感器,提出了一种基于脱靶概率的阈值算法。恒虚警率(CFAR)等传统阈值算法是一种针对虚警的面向噪声的算法。与该算法不同的是,该算法侧重于遗漏检测。在某些应用中,漏检比虚警更重要,特别是在红外-超宽带雷达传感器等短距离应用中,如防碰撞系统、入侵检测等。此外,面向目标信号的阈值算法可以更好地感知环境。我们知道,信号的振幅取决于雷达的安装高度和角度。传统的基于噪声的阈值分割算法缺乏对这些参数的考虑。然而,由于所提出的算法是一种面向目标信号的阈值算法,因此它会自动针对这些参数进行优化。我们在实验结果中对基于CFAR的阈值算法和基于漏检概率的阈值算法产生的阈值进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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