Evidence map›Paper›PMID 36433308›Full record

ArticleSensors (Basel, Switzerland)2022

Implementation of and Experimentation with Ground-Penetrating Radar for Real-Time Automatic Detection of Buried Improvised Explosive Devices.

Pachara Srimuk, Akkarat Boonpoonga, Kamol Kaemarungsi, Krit Athikulwongse, Sitthichai Dentri

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Pachara SrimukResearch Center of Innovation Digital and Electromagnetic Technology, Electrical Engineering, Department of Electrical and Computer Engineering, Faculty of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok 10800, Thailand.
Akkarat BoonpoongaResearch Center of Innovation Digital and Electromagnetic Technology, Electrical Engineering, Department of Electrical and Computer Engineering, Faculty of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok 10800, Thailand.ORCID 0000-0001-9197-7674
Kamol KaemarungsiNational Electronics and Computer Technology Center, National Science and Technology Development Agency, Pathumthani 12120, Thailand.
Krit AthikulwongseNational Electronics and Computer Technology Center, National Science and Technology Development Agency, Pathumthani 12120, Thailand.ORCID 0000-0002-4092-8634
Sitthichai DentriDepartment of Electronics Engineering Technology, Collage of Industrial Technology, King Mongkut's University of Technology North Bangkok, Bangkok 10800, Thailand.ORCID 0000-0003-4015-543X
King Mongkut's University of Technology North Bangkok · THNational Science and Technology Development Agency · TH

Funding

King Mongkut's University of Technology North Bangkok KMUTNB-64-KNOW-45Thailand Graduate Institute of Science and Technology SCA-CO-2559-2297-TH
6 · The paper itself

Abstract

This paper proposes the implementation of and experimentation with GPR for real-time automatic detection of buried IEDs. GPR, consisting of hardware and software, was implemented. A UWB antenna was designed and implemented, particularly for the operation of the GPR. The experiments were conducted in order to demonstrate the real-time automatic detection of buried IEDs using GPR with an R-CNN algorithm. In the experiments, the GPR was mounted on a pickup truck and a maintenance train in order to find the IEDs buried under a road and a railway, respectively. B-scan images were collected using the implemented GPR. R-CNN-based detection for the hyperbolic pattern, which indicates the buried IED, was performed along with pre-processing, for example, using zero offset removal, and background removal and filtering. Experimental results in terms of detecting the hyperbolic pattern in B-scan images were shown and verified that the proposed GPR system is superior to the conventional one using region analysis processing-based detection. Results also showed that pre-processing is required in order to improve and/or clean the hyperbolic pattern before detection. The GPR can automatically detect IEDs buried under roads and railways in real time by detecting the hyperbolic pattern appearing in the collected B-scan image.

Indexed as

RadarWeaponsAlgorithmsEmpirical ResearchResearch Designautomatic detectionGPRground-penetrating radarIEDimprovised explosive devicesR-CNNregion-based convolutional neural networkultra-wideband antennaUWB antenna

Identifiers

PMID36433308
PMCPMC9693345
OpenAlexW4308970681

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.