In this paper, we proposed a new thresholding method for impulse radio ultra-wideband (IR-UWB) radar-based detection applications by taking both the false alarm and miss-detection rates into consideration. The thresholding algorithm is the key point of the detection application, and there have been numerous studies on these developments. Most of these studies were related to the occurrence of false alarms, such as the constant false alarm rate algorithm (CFAR). However, very few studies have considered miss-detection, which is another crucial issue in detection applications. To mitigate this issue, our proposed algorithm considered miss-detection as well as the false alarms occurring during thresholding. In the proposed algorithm, a threshold is determined by combining a noise signal-based threshold, in which the focus point is the false alarm, with a target signal-based threshold, in which the focus point is a miss-detection, at a designed ratio. Therefore, a threshold can be determined based on the focus point by adjusting the designed ratio. In addition, the proposed algorithm can estimate the false alarm and miss-detection rates for the determined threshold, and thus, the threshold can be objectively set. Moreover, the proposed algorithm is better in terms of understanding the target signal for a given environment. A target signal can be affected by the clutter, installation height, and the angle of the radar, which are factors that noise-oriented algorithms do not consider. As the proposed algorithm analyzed the target signal, these factors were all considered. We analyzed the false alarm and miss-detection rates for the thresholds, which were determined by different combination ratios at various distances, and we experimentally verified the validity of the proposed algorithm.
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