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 Novel Adaptive Pre Screener For Ground Penetrating Radar
Date
2016-05-19
Author
Baydar, Bora
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
194
views
0
downloads
Cite This
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 for landmine detection with GPR. In this study, KLMS approach is compared with LMS approach in terms of processing time, false alarm rate, and true detection rate.
Subject Keywords
Landmine
,
GPR
,
Signal processing
,
Adaptive signal processing
URI
https://hdl.handle.net/11511/53040
Conference Name
24th Signal Processing and Communication Application Conference (SIU)
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
A tracker-aware detector threshold optimization formulation for tracking maneuvering targets in clutter
Aslan, Murat Samil; Saranlı, Afşar (Elsevier BV, 2011-09-01)
In this paper, we consider a tracker-aware radar detector threshold optimization formulation for tracking maneuvering targets in clutter. The formulation results in an online method with improved transient performance. In our earlier works, the problem was considered in the context of the probabilistic data association filter (PDAF) for non-maneuvering targets. In the present study, we extend the ideas in the PDAF formulation to the multiple model (MM) filtering structures which use PDAFs as modules. Althou...
A new electromagnetic target classification method with MUSIC algorithm
Secmen, Mustafa; Sayan, Gönül (2006-01-01)
This paper introduces a novel method for aspect invariant electromagnetic target recognition based on the use of multiple signal classification (MUSIC) algorithm to extract late-time resonant target features from the ultra-wideband scattered data. This method is mainly based on the usage of MUSIC spectra obtained from electromagnetic scattered data as the target features. This approach achieves very high accuracy rates even at very low signal-to-noise ratio (SNR) values although it needs scattered data for ...
A novel electromagnetic target recognition method by MUSIC algorithm
Secmen, Mustafa; Sayan, Gönül (2006-12-01)
This paper introduces a novel method for aspect invariant electromagnetic target recognition based on the use of multiple signal classification (MUSIC) algorithm to extract late-time resonant target features from the ultra-wideband scattered data. This approach achieves very high accuracy rates even at very low signal-to-noise ratio (SNR) values although it needs scattered data for classifier design at only a few different aspects and makes use of the MUSIC algorithm in a simple and computationally efficien...
A GPR-based landmine identification method using energy and dielectric features
Akar, Gözde (2018-04-14)
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 tw...
A high performance Sigma-Delta readout circuitry for mu g resolution microaccelerometers
Ocak, Ilker E.; Kepenek, Reha; Külah, Haluk; Akın, Tayfun (Springer Science and Business Media LLC, 2010-08-01)
This paper reports a second order electromechanical sigma-delta readout for micro-g resolution accelerometers in addition to other high-sensitivity capacitive microsensors with large base capacitance. The chip implements a switched-capacitor readout front-end and an oversampled sigma-delta modulator, and hence can be used for both open-loop analog readout and closed-loop control and readout with direct digital output. The readout circuit has more than 115 dB dynamic range and can resolve less than 3 aF/root...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Baydar and G. Akar, “A Novel Adaptive Pre Screener For Ground Penetrating Radar,” presented at the 24th Signal Processing and Communication Application Conference (SIU), Zonguldak, TURKEY, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53040.