Dergiler / Sigma Mühendislik ve Fen Bilimleri Dergisi / 2019 / Cilt: 37 - Sayı: 3

AN EXPERIMENTAL STUDY ON DETECTING AND IMAGING CAVITY REGIONS INSIDE TREE TRUNK USING CIRCULAR BACK PROJECTION FOCUSING ALGORITHM

Sayfa
737–746
Yayın Tarihi
2020-09-01
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The resultant focused TIIR radar images of measured data have demonstrated that CBPA can be a strong candidate and successfully utilized for migrating the raw backscattered data for TIIR applications.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In this work, we have presented experimental study for detecting cavity regions inside a tree trunk using circular back projection focusing algorithm (CBPA).
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Temel Bulgular & Veri:First, the validity of CBPA was questioned and then checked by the help of a simulation scenario that were generated using perfect point-scatterers in Matlab programming environment.
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Sonuç & Katkı:The resultant focused TIIR radar images of measured data have demonstrated that CBPA can be a strong candidate and successfully utilized for migrating the raw backscattered data for TIIR applications.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Remote sensing · radar imaging · tree-penetrating radar

Abstract

In this work, we have presented experimental study for detecting cavity regions inside a tree trunk using circular back projection focusing algorithm (CBPA). First, the validity of CBPA was questioned and then checked by the help of a simulation scenario that were generated using perfect point-scatterers in Matlab programming environment. After achieving perfect reconstruction of the simulated cavity structure together with the tree-body in the simulated scenario, the implementation of CBPA was applied to a real tree-interior imaging radar (TIIR) experiments that were conducted in the laboratory. The resultant focused TIIR radar images of measured data have demonstrated that CBPA can be a strong candidate and successfully utilized for migrating the raw backscattered data for TIIR applications.

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Bu Makaleye Atıf Yap

GÖKKAN, S., YILMAZ, B., ÖZDEMİR, C. (2020). AN EXPERIMENTAL STUDY ON DETECTING AND IMAGING CAVITY REGIONS INSIDE TREE TRUNK USING CIRCULAR BACK PROJECTION FOCUSING ALGORITHM. Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt: 37 - Sayı: 3, 737–746. https://ajindex.com/articles/419145

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Kaynakça (15)

  1. A. Brookes. (2007) Preventing death and serious injury from falling trees and branches, Australian Journal of Outdoor Education, 11(2), 50-59
  2. J. Watt and D. J. Ball. (2009) Trees and the Risk of Harm, Report for the National Tree Safety Group
  3. V. Bucur. (1995) Acoustics of Wood. CRC Press, Boca Raton, FL
  4. S.A. Al Hagrey. (2006) Electrical resistivity imaging of wooden tree trunks,” Near Surface Geophysics, vol. 4, 177-185
  5. G. Catena, M. Catalano, and L. Palla. (1990) Thermal infrared detection of cavities in trees,” European Journal of Forest Pathology, 20, 201–210
  6. H. Berndt, A.P. Schniewind, G.C. Johnson. (2000) Ultrasonic energy propagation trough wood: where, when, how much, Proc. Of 12th Int. Symposium on NDT of Wood, Sopron 13-15, 57-66
  7. M. Hasegawa, M. Takata, J. Matsumara and K. Oda. (2011) Effect of wood properties on within-tree variation in ultrasonic wave velocity in softwood, Ultrasonics 51, 296-302
  8. J. R. Butnor, J. A. Doolittle, L. Kress, S. Cohen and K. H. Johnsen. (2001) Use of ground-penetrating radar to study tree roots in the southeastern United States, Tree Physiology 21, 1269–1278
  9. C. Özdemir, Ş. Demirci, E. Yiğit and B. Yılmaz. (2014) A Review on Migration Methods in B-scan Ground Penetrating Radar Imaging, Mathematical Problems in Engineering, Volume,1-16
  10. B. Yılmaz, Ş. Demirci, E. Yiğit and C. Özdemir. (2013) An Experimental Study of Through-the-Wall Radar for Life sign Detection, Proceedings of Progress in Electromagn, Research Symposium (PIERS 2013),1602-1604
  11. M. G. Amin, Through-the-Wall Radar Imaging. (2010) Taylor and Francis, Bocaraton, FL, 2010
  12. N.J. Redding and G.N. Newsam. (2001) Inverting the Circular Radon Transform,” DTSO Research Report DTSO-RR-0211
  13. L.Zhou, C.Huang and Y.Su. (2012) A Fast back projection algorithm based on cross correlation for GPR imaging,” IEEE Geoscience and Remote Sensing Letters, vol.9, no.2, pp.228-232
  14. H.Zhang, S.Ouyang, G.Wang, J.Li, S.Wu and F.Zhang. (2015) Back projection algorithm based on self correlation for ground penetrating radar imaging, Journal of Applied Remote Sensing, vol.9, 095059
  15. S.Sardar and A.K.Mishra. (2011) “A UBW based Improved Imaging of Breast Tumors,” IEEE Applied Electromagnetics Conference (AEMC). DOI: 10.1109/AEMC.2011.6256909 [16] D.Oloumi, P. Boulanger, A.Kordzadeh and K. Rambabu.(2015) Breast Tumor Detection Using UWB Circular-SAR Tomograptic Microwave Imaging, IEEE 37th Annual International Confer