Conical Differential Range Based Back-Projection Algorithm for Concealed Object Detection with Three-Dimensional mmW Imaging


Duysak H., YİĞİT E., Seyfi L.

TRAITEMENT DU SIGNAL, cilt.39, sa.6, ss.1981-1989, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 39 Sayı: 6
  • Basım Tarihi: 2022
  • Doi Numarası: 10.18280/ts.390610
  • Dergi Adı: TRAITEMENT DU SIGNAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Business Source Elite, Business Source Premier, Compendex, zbMATH
  • Sayfa Sayıları: ss.1981-1989
  • Anahtar Kelimeler: millimeter-wave imaging, radar imaging, back-projection algorithm, FAST BACKPROJECTION ALGORITHM
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

Millimeter wave(mmW) imaging has spread to a wide range of applications in the last quarter. One of the most important research areas of mmW is three-dimensional (3D) imaging systems. In this study, conical differential range-based back-projection (BP) algorithm is proposed for three-dimensional mmW imaging. In the algorithm, the differential range is created using points inside a conical volume, thus the number of interpolation points is considerably reduced. The performance of the algorithm is demonstrated by simulation and experimental studies. Cylindrical scanning is carried out by means of the experimental setup. Experiments are carried out at frequencies of 26.5-40 GHz. The traditional BP algorithm (BPA) and the proposed algorithm are used to reconstruct the images. With the proposed method, it is observed that ISLR for the point target increased by about 5 dB compared to the traditional method. Moreover, the computational complexity is reduced by up to 10 times, depending on the imaging area. Thanks to the proposed method, the image of the concealed weapon under the cloth in an experimental study is more clearly focused compared to the traditional method. Therefore, it can provide images that give more accurate results for applications such as automatic target detection methods.