Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A GPR-based landmine identification method using energy and dielectric features
Date
2018-04-14
Author
Akar, Gözde
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
177
views
0
downloads
Cite This
This study presents a novel landmine identification method that estimates intrinsic parameters of buried objects from their primary and secondary GPR reflections to reduce false alarm rates of GPR-based landmine detection algorithms. To achieve this, two different features are extracted from A-scan GPR data of buried objects. The time length of the reflected GPR signal from the underground object indicates the first feature. The second feature estimates the intrinsic impedance of the buried object. These two features are classified with the support vector machine (SVM) classifier. The experimental results show that the proposed features have very high discrimination power which reduces false alarm rates to a great extent.
Subject Keywords
Landmine identification
,
Ground penetrating radar (GPR)
,
Feature extraction
,
Cumulative energy curve
,
Total energy value
,
Intrinsic impedance
URI
https://hdl.handle.net/11511/48153
DOI
https://doi.org/10.1117/12.2301009
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
A Radar Target Recognition Method with MUSIC Algorithm: Application to Aircraft Targets with Measured Scattered Data
Secmen, M.; Turhan-Sayan, G.; Sayan, Gönül (2008-05-30)
This paper demonstrates the usefulness of an ultra wideband target recognition method in the case of realistic and complicated target geometries at resonance region. The method utilizes the MUSIC algorithm to extract the natural resonance-related scattering features of targets. The resulting features give the power distribution maps of targets. These maps are called as fused MUSIC spectrum matrices and used as the main target recognition feature in the method. The fusion process is needed to reduce the aspe...
A Novel Adaptive Pre Screener For Ground Penetrating Radar
Baydar, Bora; Akar, Gözde (2016-05-19)
This paper describes a novel pre-screener algorithm for landmine detection with a ground penetrating radar (GPR). The pre-screener algorithms are used for finding anomalies that are potential locations of interest. Thus, their processing time is as important as their true detection rate and false alarm rate. The proposed approach is based on Kernel Least Mean Square algorithm. Although Least Mean Square (LMS) based approach has already been used in the literature, KLMS based approach is a novel application ...
A novel method for electromagnetic target classification using the music algorithm: Applied to small-scale aircraft targets
Secmen, Mustafa; Sayan, Gönül (2006-01-01)
This paper introduces a novel target classification method based on the extraction of target features by using natural response related late-time electromagnetic scattered field data. In the feature extraction stage, the use of multiple signal classification (MUSIC) algorithm together with a simple but effective feature fusion approach leads to a significant reduction in the sensitivity of classification accuracy to both aspect angle variations and the signal-to-noise ratio (SNR) levels of the data. Another...
A Multi-Dimensional Hough Transform Algorithm Based on Unscented Transform as a Track-Before-Detect Method
Sahin, Gozde; Demirekler, Mübeccel (2014-07-10)
In this study, a new Multi-Dimensional Hough Transform technique is proposed for the detection of dim targets in radar data. Multi-Dimensional Hough Transform is a Track-Before-Detect method that fuses Hough Transform results obtained on (x-t), (y-t) and (x-y) domains. The proposed study models Hough Transform results in (x-t) and (y-t) domains by Gaussians and transforms these Gaussians to (x-y) domain using Unscented Transform. This improves the computational efficiency significantly without degrading per...
A window-based time series feature extraction method
Katircioglu-Ozturk, Deniz; GÜVENİR, H. ALTAY; Ravens, Ursula; Baykal, Nazife (2017-10-01)
This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publi...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
G. Akar, “A GPR-based landmine identification method using energy and dielectric features,” 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48153.