Combination of physics-based and image-based features for landmine identification in ground penetrating radar data

Date

2019-4-23

Author

Genc, Alper
Akar, Gözde

Metadata

Show full item record

Item Usage Stats

199
views

0
downloads

Ground penetrating radar (GPR) is a powerful technology for detection and identification of buried explosives, especially with little or no metal content. However, subsurface clutter and soil distortions increase false alarm rates of current GPR-based landmine detection and identification methods. Most existing algorithms use shape-based, image-based, and physics-based techniques. Analysis of these techniques indicates that each type of algorithm has a different perspective to solve the landmine detection and identification problem. Therefore, one type of method has stronger and weaker points with respect to the other types of algorithms. To reduce false alarm rates of the current GPR-based landmine detection and identification methods, we propose a combined feature utilizing both physics-based and image-based techniques. Combined features are classified with a support vector machine classifier. The proposed algorithm is tested on a simulated data set that contained more than 500 innocuous object signatures and 400 landmine signatures, over half of which are completely nonmetal. The results presented indicate that the proposed method has significant performance benefits for landmine detection and identification in GPR data.

Subject Keywords

Ground penetrating radar, Landmine identification, Feature extraction, Physics-based approach, Cumulative energy curve, Intrinsic impedance

URI

https://hdl.handle.net/11511/28613

Journal

Journal of Applied Remote Sensing

DOI

https://doi.org/10.1117/1.jrs.13.026503

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

Multi-feature fusion for GPR-based landmine detection and classification Genç, Alper; Akar, Gözde; Department of Electrical and Electronics Engineering (2019) Ground penetrating radar (GPR) is a powerful technology for detection and identification of buried explosives especially with little or no metal content. However, subsurface clutter and soil distortions increase false alarm rates of current GPR-based landmine detection and identification methods. Most existing algorithms use shape- based, image-based and physics-based techniques. Analysis of these techniques indicates that each type of algorithms has a different perspective to solve landmine detection and i...
Through-The-Wall Target Detection using GPR A-Scan Data: Effects of Different Wall Structures on Detection Performance DOĞAN, MESUT; Sayan, Gönül (2017-09-27) Ground penetrating radar (GPR) is an electromagnetic sensor based on the ultra-wideband radar technology that can also be used for through-the-wall (TTW) target recognition. Search for the presence of designated targets hidden behind the walls, such as stationary or moving human bodies or certain types of weapons, is addressed in various critical applications; in rescue missions after earthquakes or in military operations, etc. In such inverse problems, type of the wall is as important as the properties and...
Fusion of forward-looking infrared camera and down-looking ground penetrating radar for buried target detection Yuksel, Seniha Esen; Akar, Gözde; Ozturk, Serhat (2015-04-23) In this paper, we propose a system to detect buried disk-shaped landmines from ground penetrating radar (GPR) and forward-looking long wave infrared (FL-LWIR) data. The data is collected from a test area of 500m(2), which was prepared at the IPA Defence, Ankara, Turkey. This test area was divided into four lanes, each of size 25m length by 4m width and 1m depth. Each lane was first carefully cleaned of stones and clutter and then filled with different soil types, namely fine-medium sand, course sand, sandy ...
Detection of Conducting and Dielectric Objects Buried under a Layer of Asphalt or Concrete Using Simulated Ground Penetrating Radar Signals DOĞAN, MESUT; GÜMÜŞ, SİNEM; Sayan, Gönül (2017-09-15) Ground-penetrating radars (GPRs) are ultra-wideband microwave sensors mainly used for detection and identification of mines and other explosive objects buried in soil or hidden under road construction layers. In this study, we investigated effects of having different construction layers over the soil surface in buried object detection problem using A-scan GPR data. A novel preprocessing technique that makes use of cumulative energy curves of A-scan signals is used for preprocessing and target detection in ...
Investigation of Simulated Ground Penetrating Radar Data for Buried Objects Using Quadratic Time-Frequency Transformations DOĞAN, MESUT; Sayan, Gönül (2017-07-14) Sub-surface sensing is a challenging area of research that highly benefits from the use of ultra-wideband ground penetrating radar (GPR) technology. Detection and classification of buried objects with reduced false alarm rates is still open to improvements. Use of joint temporal and spectral target features obtained from electromagnetic GPR signals using time-frequency representation (TFR) methods is highly promising because TFRs provide detailed information about the energy distribution of GPR signals over...

Citation Formats

A. Genc and G. Akar, “Combination of physics-based and image-based features for landmine identification in ground penetrating radar data,” Journal of Applied Remote Sensing, 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/28613.