Joint multistatic THz imaging radars for standoff personnel screening

Xu Yang; Jin Li; Yiming Pi; Tong Liu; Haijiang Wang

doi:10.1117/1.JRS.12.034002

18 July 2018 Joint multistatic THz imaging radars for standoff personnel screening

Xu Yang, Jin Li, Yiming Pi, Tong Liu, Haijiang Wang

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 3, 034002 (July 2018). https://doi.org/10.1117/1.JRS.12.034002

Abstract

In response to the increasing threat of terrorism, standoff security screening of person-borne concealed weapons or contraband in public areas, such as airports and railway stations, is an urgent requirement; however, current solutions suffer from the limited field of view and the problem of security screening with interfering with the passenger flow. This paper proposes an imaging method that exploits the angular diversity of distributed multistatic terahertz (THz) radar network in combination with inverse synthetic aperture radar (ISAR) technique to realize high-resolution penetration imaging at a standoff range. The radar network is based on multistatic ISAR systems, and the multistatic ISAR system’s equivalent monostatic model is derived. According to the equivalent monostatic model, we develop the image formation algorithm and give the analytical expression of the cross-range resolution. Compared with conventional monostatic ISAR configuration, the analytical expression shows that the multistatic ISAR configuration can enhance the image’s cross-range resolution and the maximum enhanced factor is approximately equal to the number of radars in the multistatic system. Numerical simulations and experimental results agree well with the theoretical derivation. The proposed imaging approach offers a low-cost and flexible alternative to the present systems not only for security screening but also for noncooperative target imaging.

Citation Download Citation

Xu Yang, Jin Li, Yiming Pi, Tong Liu, and Haijiang Wang "Joint multistatic THz imaging radars for standoff personnel screening," Journal of Applied Remote Sensing 12(3), 034002 (18 July 2018). https://doi.org/10.1117/1.JRS.12.034002

Received: 13 February 2018; Accepted: 26 June 2018; Published: 18 July 2018

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