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LIANG Xiao, YE Shengbo, SONG Chenyang, et al. Automatic multitarget detection method based on distributed through-wall radar[J]. Journal of Radars, in press. doi: 10.12000/JR24127
Citation: LIANG Xiao, YE Shengbo, SONG Chenyang, et al. Automatic multitarget detection method based on distributed through-wall radar[J]. Journal of Radars, in press. doi: 10.12000/JR24127

Automatic Multitarget Detection Method Based on Distributed Through-wall Radar

DOI: 10.12000/JR24127
Funds:  The National Key Research and Development Program of China (2023YFC3011503), Science and Technology on Near-surface Detection Laboratory (6142414220710)
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  • Corresponding author: LIU Xiaojun, lxjdr@mail.ie.ac.cn; JIANG Hejun, jhj68@126.com
  • Received Date: 2024-06-20
  • Rev Recd Date: 2024-09-03
  • Available Online: 2024-09-09
  • Ultra-WideBand (UWB) radar exhibits strong antijamming capabilities and high penetrability, making it widely used for through-wall human-target detection. Although single-transmitter, single-receiver radar offers the advantages of a compact size and lightweight design, it cannot achieve Two-Dimensional (2D) target localization. Multiple-Input Multiple-Output (MIMO) array radar can localize targets but faces a trade-off between size and resolution and involves longer computation durations. This paper proposes an automatic multitarget detection method based on distributed through-wall radar. First, the echo signal is preprocessed in the time domain and then transformed into the time-frequency domain. Target candidate distance cells are identified using a constant false alarm rate detection method, and candidate signals are enhanced using a filtering matrix. The enhanced signals are then correlated based on vital information, such as breathing, to achieve target matching. Finally, a positioning module is employed to determine the radar’s location, enabling rapid and automatic detection of the target’s location. To mitigate the effect of occasional errors on the final positioning results, a scene segmentation method is used to achieve 2D localization of human targets in through-wall scenarios. Experimental results demonstrate that the proposed method can successfully detect and localize multiple targets in through-wall scenarios, with a computation duration of 0.95 s based on the measured data. In particular, the method is over four times faster than other methods.

     

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