Binary integration nonparametric detection for range-spread targets in distributed terahertz radar network under unknown clutter

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.