Abstract
In this study, to detect person-borne concealed threats in range profiles under the circumstance of unknown clutter, we propose a binary integration nonparametric detection method based on the generalized sign (GS) detector for range-spread targets in a distributed terahertz radar network (DTRN). In the detection, the length of range-spread targets and the number of dominant scatterers on range-spread targets are considered and adaptively estimated. Furthermore, the GS detection method is applied to maintain a constant false alarm rate (CFAR) under the circumstance of unknown clutter. The detection performance of the proposed method for single terahertz radar and DTRN are both examined with the data synthesized by real range-spread targets data and real clutter data. Experimental results show that the proposed method is effective, and for a given false alarm probability, the DTRN exhibits better detection performance than the single terahertz radar.
Highlights
Given its short detection range and penetrativity, terahertz radar is mainly applied in the fields of security checks and anti-terrorism with high-resolution screening imaging at a stand-off distance [1–3]
The detection performance of single terahertz radar and distributed terahertz radar network (DTRN) is analyzed under the circumstance of unknown clutter by using the data synthesized by real range-spread targets data and real clutter data
5 Conclusions In this study, a binary integration nonparametric detection method based on the generalized sign (GS) detector for range-spread targets in DTRN is proposed to detect person-borne concealed threats in range profiles
Summary
Given its short detection range and penetrativity, terahertz radar is mainly applied in the fields of security checks and anti-terrorism with high-resolution screening imaging at a stand-off distance [1–3]. Given that the length of range cell samples is larger than that of range-spread targets, the sliding window detection method is applied to the local detectors. The length of the sliding window which is the possible length of range-spread targets is estimated via the maximal signal to clutter ratio (SCR) rule [15]. The number of dominant scatterers within the sliding window is selected as the threshold for binary integration detection, which is estimated via Otsu’s method [16]. The detection performance of single terahertz radar and DTRN is analyzed under the circumstance of unknown clutter by using the data synthesized by real range-spread targets data and real clutter data. Experimental results show that the proposed method is effective, and for a given false alarm probability, the DTRN exhibits better detection performance than the single terahertz radar. The overall decision is obtained following the m-out-of-n fusion rule
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