GPR Image Enhancement Based on Frequency Shifting and Histogram Dissimilarity

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 114
  • Download : 0
In the ground-penetrating radar (GPR) B-scan images, various noise sources are superimposed due to the ruggedness of the surface, sensor vibration, and multiple reflections. Additionally, the intensity of the received signals from small-size or low-metal-content landmines is low. Thus, it is difficult to accurately detect buried mines. In this letter, we propose an effective method to improve the B-scan image so that accurate landmine detection is possible even in such conditions. The proposed B-scan image enhancement method is comprised of two main techniques: an A-scan transformation based on frequency shifting and a background-landmine dissimilarity measurement using cumulative intensity distribution (CID). Based on frequency shifting, an A-scan transformation is devised to attenuate the strong ac component contained by the received A-scan signal. The CID-based dissimilarity is introduced to measure how an A-scan differs from a background model in the presence of a landmine. The proposed dissimilarity measure provides a robust response to a rugged ground surface and sensor vibration. For performance analysis, we compared our method with some conventional methods using the GPR data set acquired by an ultra wide band GPR sensor manufactured by Hanwha Systems Co., Ltd. We carried out various experiments and verified that the proposed method has a better performance than the conventional methods.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2018-05
Language
English
Article Type
Article
Keywords

GROUND-PENETRATING RADAR

Citation

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, v.15, no.5, pp.684 - 688

ISSN
1545-598X
DOI
10.1109/LGRS.2018.2809720
URI
http://hdl.handle.net/10203/242349
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0