BAB V HASIL PENELITIAN DAN ANALISIS
V.2. Proses Pengolahan Data
V.2.2. Meningkatkan Gain pada Data
42
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Gambar 25. Profil citra data GPR setelah dikuatkan dengan metode time power gain pada line 0
Gambar 26. 1D plot untuk signal trace setelah dikuatkan dengan metode time power gain pada line 0
Line 0
two way travel time (ns)
position (meter)
0 2 4 6 8 10
0
50
100
150
200
250
300
350
-2 -1.5 -1 -0.5 0 0.5 1 1.5 2 x 107
0 100 200 300 400 500 600 700 800 900 1000
-2 -1.5 -1 -0.5 0 0.5 1 1.5
2x 107 1D Plot Line 0
two way travel time (ns)
signal amplitude (mV)
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Gambar 27. Profil citra data GPR setelah dikuatkan dengan metode time power gain pada line 1
two way travel time (ns)
position (meter) Line 1
0 2 4 6 8 10
0 50 100 150 200 250 300
350 -4
-3 -2 -1 0 1 2 3 x 107
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Gambar 28. 1D plot untuk signal trace setelah dikuatkan dengan metode time power gain pada line 0
Gambar 28 memperlihatkan gambar yang mirip dengan gambar setelah proses dewow. Perbedaannya terletak pada permukaan yang lebih dalam. Pada gambar dengan metode time power, data profil pada permukaan bagian atas tidak terlalu banyak perubahan, namun kondisi sinyal hanya melemah, sedangkan pada bagian bawah, terlihat perbedaan karena sinyal pada profil bagian bawah lebih kuat.
Penguatan amplitude sinyal pada bagian bawah profil dan pelemahan amplituda sinyal pada bagian atas profil ditujukkan pada Gambar 28. Terlihat pada Gambar 28, semakin berada pada bawah profil, maka penguatan sinyal semakin besar.
V.2.2.2. Automated gain control (AGC)
Profil hasil pengolahan data GPR dengan meningkatkan gain data dengan metode automated gain control dapat dilihat pada Gambar 29, Gambar 30, Gambar 31 dan Gambar 32. Caranya adalah dengan menetapkan sebuah time (depth) window dan mengatur agar daya pada setiap window adalah sama. Oleh karenanya
0 100 200 300 400 500 600 700 800 900 1000
-4 -3 -2 -1 0 1 2
3x 107 1D Plot Line 1
two way travel time (ns)
signal amplitude (mV)
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kita harus menentukan lebar window atau window width. Pada setiap window, diberikan penguatan yang sama. Figure 12 memperlihatkan penguatan yang sama untuk setiap window.
Gambar 29. Profil citra data GPR setelah dikuatkan dengan metode automated gain control pada line 0
two way travel time (ns)
position (meter) Line 0
0 2 4 6 8 10
0
50
100
150
200
250
300
350
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8
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Gambar 30. 1D plot untuk signal trace setelah dikuatkan dengan metode automated gain control pada line 0
Gambar 31. Profil citra data GPR setelah dikuatkan dengan metode automated gain control pada line 1
0 100 200 300 400 500 600 700 800 900 1000
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1
1D Plot Line 0
two way travel time (ns)
signal amlitude (mV)
two way travel time (ns)
position (meter) Line 1
0 2 4 6 8 10
-50 0 50 100 150 200 250 300 350
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8
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Gambar 32. 1D plot untuk signal trace setelah dikuatkan dengan metode automated gain control pada line 0
Gambar-gambar profil yang telah dijelaskan sebelumnya, semua gambar dinyatakan dalam two way travel time. Waktu propagasi dua arah ini dapat dikonversi menjadi kedalaman. Untuk dapat mengkonversi waktu propagasi dua arah ke depth, kecepatan sinyal radar dalam tanah perlu diketahui. Untuk kecepatan gelombang elektromagnetik dalam media dapat dilihat pada Table I. Kecepatan rambat yang digunakan pada data GPR adalah 0.6 m/s. Gambar 33 menunjukkan profil data GPR dimana two-way travel time dikonversi ke depth.
0 100 200 300 400 500 600 700 800 900 1000
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1
1D Plot Line 1
two way travel time (ns)
signal amplitude (mV)
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Gambar 33. Profil citra data GPR dengan two-way travel time dikonversi ke depth dengan velocity = 0.06 m/ns
Depth (meter)
position (meter) Line 0
0 2 4 6 8 10
0 1 2 3 4 5 6 7 8 9 10
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BAB VI
KESIMPULAN DAN SARAN
VI.1. Kesimpulan
Hasil penelitian ini berhasil mengembangkan sebuah program untuk membaca data GPR kemudian memvisualisasikan kondisi bawah permukaan dari data GPR yang diolah. Tahap pertama adalah tahap editing dan rubber banding yang merupakan tahap persiapan pengolahan data. Informasi yang dibutuhkan adalah frekuensi yang digunakan, jarak antar lines, jumlah lines, jumlah trace dan jenis file. Tahap berikutnya adalah tahap time zero correction dan tahap dewow.
Time zero correction adalah metoda untuk menyinkronkan/mengoreksi waktu tepat saat sinyal menyentuh permukaan untuk masuk menembus permukaan. Penelitian ini sudah berhasil mengoreksi waktu nol sinyal. Proses dewow bertujuan untuk menghilangkan komponen frekuensi rendah dan DC bias. Program yang dibuat pada penelitian ini sudah melakukan proses dewow walaupun tidak begitu terlihat perbedaannya antara sebelum dan setelah dewow. Namun terlihat ketika citra 1D plot trace dianalisis. Tahap berikutnya adalah proses filtering yang bertujuan untuk meningkatkan SNR. Program juga sudah berhasil melakukan filter terhadap data GPR. Setelah filtering, tahap berikutnya adalah meningkatkan gain pada data.
Tahap ini merupakan tahap yang sedikit kompleks karena bukan menggunakan data langsung. Proses gaining data berjalan bagus, namun nilai parameter penguatan belum optimal. Secara umum, program pengolahan data GPR (GPR Digital Signal Processing) yang dibuat pada penelitian ini sudah berjalan sempurna.
VI.2. Saran
Pengembangan program pengolahan data GPR adalah suatu hal yang tidak sederhana karena pengolahan data GPR sangat bergantung dari kualitas data GPR, karakteristik permukaan dan bawah permukaan serta pengalaman peneliti dalam penentuan beberapa nilai parameter permukaan maupun benda di bawah permukaan. Pada penelitian ini menggunakan data GPR dari penelitian lain di luar
51
negeri. Oleh karenanya peneliti mengembangkan program pengolahan data GPR berdasarkan data GPR peneliti lain yang kemudian diverifikasi dengan program pengolahan data GPR yang telah ada sebelumnya.
Saran untuk penelitian selanjutnya adalah sebaiknya data yang digunakan untuk verifikasi program pembacaan data GPR adalah data GPR yang disurvey oleh peneliti sendiri, baik survey lapangan atau survey dengan skenario lapangan tertentu sehingga karakteristik permukaan dan bawah permukaan bias diatur untuk memverifikasi hasil pengolahan data GPR.
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DAFTAR PUSTAKA
Ali, J., Abdullah, N., Yusof, M., Mohd, E., & Mohd, S. (2017). Ultra- Wideband Antenna Design for GPR Applications: A Review.
International Journal of Advanced Computer Science and Applications, 8(7). https://doi.org/10.14569/IJACSA.2017.080753
Annan, P. (2002). The history of ground penetrating radar. Subsurface Sensing Technologies and Applications (Vol. 3).
DAVIS, J. L., & ANNAN, A. P. (1989). GROUND-PENETRATING RADAR FOR HIGH-RESOLUTION MAPPING OF SOIL AND ROCK STRATIGRAPHY1. Geophysical Prospecting, 37(5), 531–551.
https://doi.org/10.1111/j.1365-2478.1989.tb02221.x
Hariyadi, T. (2009). Perancangan Dan Realisasi Transceiver Stepped Frequency Continuous Wave Ground Penetrating Radar (Sfcw-Gpr) 700-1400 Mhz.
Huber, E., & Hans, G. (2018). RGPR — An open-source package to process and visualize GPR data. In 2018 17th International Conference on Ground Penetrating Radar (GPR) (pp. 1–4). IEEE.
https://doi.org/10.1109/ICGPR.2018.8441658
Jol, H. M. (2008). Ground Penetrating Radar Theory and Applications.
Oxford: Elsevier Science.
Mohamed, H. A., Elsadek, H., & Abdallah, E. A. F. (2012). Design of compact DRH antenna For GPR transmitter application. In The 2nd Middle East Conference on Antennas and Propagation (pp. 1–4). IEEE.
https://doi.org/10.1109/MECAP.2012.6618186
Pérez-Gracia, V., González-Drigo, R., Di Capua, D., & Pujades, L. G.
(2007). Characteristics of the GPR field pattern antennas. In M. Ehlers
& U. Michel (Eds.) (p. 67492L). https://doi.org/10.1117/12.737753 Rubin, Y., & Hubbard, S. S. (Eds.). (2005). Hydrogeophysics (Vol. 50).
Dordrecht: Springer Netherlands. https://doi.org/10.1007/1-4020-3102-
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Severns, R. (2005). Skin Depth and Wavelength in Soil.
Shao, J., Fang, G., Ji, Y., Tan, K., & Yin, H. (2013). A Novel Compact Tapered-Slot Antenna for GPR Applications. IEEE Antennas and Wireless Propagation Letters, 12, 972–975.
https://doi.org/10.1109/LAWP.2013.2276403
Yildiz, S., Uysal, A., & Ozen, M. (2016). Shorted TEM horn antenna for GPR applications. In 2016 16th Mediterranean Microwave Symposium (MMS) (pp. 1–3). IEEE. https://doi.org/10.1109/MMS.2016.7803876
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LAMPIRAN
Lampiran 1. Publikasi (1)
Design and Implementation of Low-Cost Wideband Antenna for Ground Penetrating Radar
Baso Maruddani
1,2*, Efri Sandi
1, Muhammad Fadhil Naufal Salam
11Electronics Vocational Education Program, Engineering Faculty, Universitas Negeri Jakarta, Indonesia
2DJA Institute, Jakarta, Indonesia
*Corresponding author: Baso Maruddani; Email: [email protected]
Abstract
Vivaldi antenna is one of many types of antenna implemented on ground penetrating radar. Its characteristics are pointed radiation and wide bandwidth. This study aims to design an antenna used for non-destructive test on a transportation to check the roadway material. This Vivaldi antenna has a wide bandwidth, 1 GHz approximately, with the frequency range between 1 GHz to 2 GHz. This Vivaldi antenna design is obtained by changing few parameters of common Vivaldi antenna to fulfill its design characteristics:
low cost and wide bandwidth. The antenna size is 350mm x 300mm. The simulation result shows that there is return loss below -10 dB for 1-2 GHz frequency range and the lowest return loss at that frequency range is around -35 dB on 1.4 GHz. This paper also explains about the effect of tapered slot size changes to return loss value and frequency. When the antenna width is enlarged, the value of return loss is getting smaller in the lower frequency.
Therefore, antenna bandwidth is getting wider. The same situation happened when tapered slot size gets bigger value, the antenna working frequency switches into the lower frequency. We can conclude that antenna bandwidth widening can be done by enlarging tapered length value and reducing tapered rate value.
Keywords: Vivaldi antenna, Ground Penetrating Radar, optimization, low cost antenna, wide bandwidth
1. Introduction
Ground Penetrating Radar (GPR) is a technology that has been developed within 15- 20 years ago. The advancement involves theories, techniques, technology and also applications range. GPR is an imaging tool that uses electromagnetic waves to observe underground material. At the beginning of its emergence, GPR technology is used to detect natural materials, but as the theory and technique progress, GPR also is also used to detect unnatural materials such as asphalt, concrete, and even bridge structures. Each material that we want to detect has different GPR specifications due to different permittivity value.
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Simply talk, the GPR works by counting the amount of reflection and electromagnetic waves that fired on the surface.
There are two important parts in GPR: the antenna and the processing system to process a received / reflected signal. This paper focuses on the antenna used by GPR: Vivaldi antenna. Vivaldi antenna was first used by Gibson in 1979 with very wide bandwidth characteristics and directional radiation patterns [1]. Theoretically, Vivaldi antennas have infinite bandwidth, high gain, and linear polarization [2]. Figure 1 shows the concept of a Vivaldi antenna in the front view.
Figure 1:VivaldiAntenna
Dimension parameters of Vivaldi Antenna are antenna length (PA), antenna width (LA), tapered length (TL), tapered rate (r), slot-line length (sL), back-wall offset (bwo) and opening mouth (MO).The Vivaldi antenna included in the Exponential Tapered Slot Antenna (TSA) type.
2. Methods and Equipment 2.1. Methods
The development of the Vivaldi antenna on this paper begins by determining some antenna parameters to specify the initial antenna. The next step is making antenna modeling by using antenna simulation software based on parameters specified in the antenna dimension parameters. Antenna simulation is used to find out whether the antenna model meets antenna specifications for the Ground Penetrating Radar (GPR). After all antenna parameters are specified and simulated, the parameters are compared to the desired specification (frequency, return loss, VSWR). If simulation result shows that antenna does not meet the specification yet, optimization is carried out. Optimization is done to achieve the specifications needed by learning various things, other literacy and also trial and error.
Optimization is done by changing the values of the antenna dimension parameters. Each antenna dimension parameter has an effect for bandwidth antenna performance during this research period. Thus connecting between antenna width parameter and bandwidth of the Vivaldi antenna becomes one of the data results in this research.
The length (PA) and width (LA) of the antenna is determined by equation (1).
𝑃𝐴 ≈ 𝑐
𝑓 √𝜀𝑟 𝐿𝐴 ≈1
2× 𝑐
𝑓 √𝜀𝑟 (2)
where 𝑃𝐴 is an antenna length, 𝐿𝐴 is an antenna width, 𝑐 is a speed of light, 𝑓 is the frequency, and 𝜀𝑟 is a relative permittivity. In the design of Vivaldi's taper slot antenna, the dimensions of Tapered length and Tapered rate determines through the calculation using formula (3). The slope level of the taper slot of Vivaldi antenna greatly affects the gain, beamwidth and bandwidth of the TSA [3]. Tapered slot antennas have a curvilinear level
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based on exponential functions as in equation (3) where long tapered values was predetermined and the mouth opening value can be found by using formula (4).
𝑢 = ± 𝑠 × 𝑒𝑥𝑝(𝑟×𝑡) (3) ±𝑀𝑂
2 = ±𝑠
2× 𝑒𝑥𝑝(𝑟×𝑇𝐿) (4)
Air-coupled on GPR systems is used to evaluate and obtain information from the topside of the infrastructure (such as sidewalks or asphalt roads). Air-coupled antenna system operates on the frequency range 500 to 2500 MHz and the middle frequency is on 1.0 GHz where this frequency has an ability to penetrate ground 0.5 to 0.9 meters [4]. One of the advantages of an air-coupled antenna is that as the process is installed, data processing can be carried out at vehicle speeds of up to 100km/h which does not disturb the traffic around it.
Microstrip to the slotline transition is simply a feed technique by crossing the slotline with the microstrip [5]. This casting technique includes all types of electromagnetic couplings because the slotline and microstrip are separated by substrate elements. Stub is the distance between the midpoint of the microstrip and slotline meeting. Equation (5) is used to determine the wavelength by using a Microstrip pilot for slotline transitions. Table 2 shows Vivaldi antenna dimension parameter values after calculation and Figure 2 shows an initial design of Vivaldi antenna.
𝑠𝑡𝑢𝑏𝐿 = 0.25 × 𝑐
𝑓𝑐√𝜀𝑟 (5)
Table 1: Parameters of Vivaldi antenna
Parameters Symbols Value
Tapered Length TL 75 mm
Tapered Rate R 0.0555
Mouth Opening MO 73.22 mm
Stub Length stubL 24.1 mm
Slotline Length sL 74 mm
Slotline Width S 1.14 mm
Antenna Length PA 150 mm
Antenna Width LA 75 mm
CooperThickness - 0.035 mm
Substrate Thickness H 1.6 mm
Backwall offset bwo 1 mm
Microstrip Width W 3.1 mm
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(a) (b)
Figure 2: Initial design of Vivaldi antenna, front view(a), back view (b).
3. Results
The Vivaldi antenna design with dimension parameters results from the distribution calculation to determine the return loss and VSWR values in the working frequency range as shown in Figure 3.
(a) (b)
Figure 3: Simulation result of Vivaldi antenna at first, return loss (a), VSWR (b).
Both graphs show that Vivaldi antenna does not have return loss and VSWR values according to specifications. Therefore optimization is done by changing the parameter values of the dimensions of the antenna width, antenna length and tapered slot. The following Vivaldi antenna parameters after optimization are shown in Table 2 and simulation results with optimized parameters are shown in Figure 4. In Figure 4, return loss value is less than -10 dB and VSWR value is between 1 and 2.
Table 2: Parameters of Vivaldi antenna after optimization
Parameters Symbols Value
Tapered Length TL 250 mm
Tapered Rate R 0,022
Mouth Opening MO 278, 95 mm
Stub Length stubL 24,1 mm
Slotline Length sL 99 mm
Slotline Width S 1,14 mm
Antenna Length PA 350 mm
Antenna Width LA 300 mm
Cooper Thickness - 0,035 mm
Substrate Thickness H 1,6 mm
Backwall offset Bwo 1 mm
Microstrip Width W 3 mm
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(a) (b)
Figure 4: Vivaldi antenna simulation result after optimization, return loss (a) and VSWR (b)
Optimization Process
The optimization process is done by changing the antenna length value, antenna width and tapered rate value. For antenna widths, changes are made by making the antenna width larger. Figure 5(a) shows the change in the shape of the return loss graph for some antenna width values which are 75 mm (red), 100 mm (green), 125 mm (blue), 200 mm (orange) and 250 mm (pink). For antenna lengths, changes are made by increasing the antenna width value. Figure 5(b) shows a graph of return loss against several values of the antenna length which are 200 mm (red), 250 mm (green), 300 mm (blue) and 350 mm (orange). For tapered rate values, tapered length values are made even greater, so the tapered rate becomes smaller. Tapered rate simulation is shown in Figure 6.
(a) (b)
Figure 5: Return loss, antenna width shifting graph (a) and antenna length shifting graph (b)
Table 3: Tapered length and tapered rate optimization value.
Tapered length (mm) Tapered rate Color
75 0.0555 Red
100 0.04165 Green
150 0.0277 Blue
250 0.022 Orange
300 0.018 Pink
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Figure 6: Return loss toward tapered slot value shifting
4. Discussion
Figure 5(a) shows when the antenna width value is enlarged, the graph gradually moves towards low frequency (return loss and VSWR). This causes greater bandwidth. Next, optimization is performed on the antenna length dimension parameters. Figure 5(b) shows return loss against several values of the antenna length: 200mm (red), 250mm (green), 300mm (blue) and 350mm (orange). When the antenna length is enlarged, there is no significant change in the return loss and VSWR graphs to the working frequency range of the Vivaldi antenna. Antenna length value greater than the antenna width aims to make the Vivaldi antenna still have a radiation pattern which is consistent with its characteristics.
Tapered slot optimization is done by changing two dimensional parameters, which are tapered length and tapered rate. Table 3 shows tapered length and tapered rate optimization values. In Figure 6, it can be seen that when the tapered slot, includes the tapered rate and tapered length values, is increased, the working frequency range of the Vivaldi antenna shifts towards the low frequency (return loss and VSWR). The result when tapered length value is enlarged and tapered rate value is reduced, the working frequency range widens.
However, tapered slot optimization is limited by antenna width and antenna length because their dimension depend on the dimensions of the length and width of the Vivaldi antenna.
(a) (b) (c) Figure 7: Fabricated antenna, the antenna (a), return loss measurement (b), VSWR measurement
Furthermore, the antenna design is fabricated to determine its bandwidth by measuring it using a network analyzer. Figure 7(a) shows the fabricated Vivaldi antenna.
The fabricated Vivaldi antenna bandwidth is measured using a network analyzer.
Figures 7(b) and 7(c) show the return loss graph and the VSWR of the fabricated Vivaldi
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antenna. Fabricated Vivaldi antenna shows a decrease in bandwidth and the working frequency whereas the fabricated Vivaldi antenna has a working frequency range from 1 GHz to 1.7 GHz. The bandwidth decrease is caused by differences in the dimensions of the Vivaldi antenna simulation and fabrication parameters. Table 4 shows the comparison of the parameters of the Vivaldi antenna dimensions with the fabrication simulation. There are differences in the parameters of the mouth opening dimension, the width of the feed channel and the backwall offset. This causes differences in the results of fabricated and simulated antenna performance.
Tabel 4: Comparation between optimization and fabrication antenna parameters
Parameters Simulation
(optimization)
Fabrication
Antenna Length 350 mm 350 mm
Antenna Width 300 mm 300 mm
Mouth Opening 278,95 mm 280 mm
Feeder Width 3 mm 2 mm
Backwall Offset 1 mm 1,5 mm
5. Conclusion
The design of the Vivaldi antenna for the Ground Penetration Radar is carried out starting from the literature study, determining antenna specifications, designing and optimizing the shape of Vivaldi antenna on the antenna simulator application and antenna fabrication so that the bandwidth can be measured.
This Vivaldi antenna with dimension 350 × 300 mm has a working frequency range from 1 GHz to 1.7 GHz with return loss values is less than -10dB and VSWR value is between 1 and 2. The fabricated Vivaldi antenna has decreased bandwidth from the simulation results which has bandwidth 1 GHz with a working frequency range from 1 GHz to 2 GHz. However, the fabricated Vivaldi antenna can be used for Non-Destructive Testing Highway antennas.
Acknowledgement
The authors would like to express our gratitude to Dean of Engineering Faculty, Universitas Negeri Jakarta for the contribution and support to the research.
Conflict of Interest
The authors have no conflict of interest to declare.
References
Elsevier Science. (2009). Ground Penetrating Radar Theory and Applications.
Edited by Harry M. Jol. Slovenia: Elsevier Science.
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Erdogan, Yakup. (2009). Parametric Study and Design of Vivaldi Antennas and Arrays. PhD dissertation/master’s thesis, Middle East Technical University.
Gibson, P.J. (1979). Vivaldi Aerial. 101-105.
Mukhidin, T.H. (2015). Studi Parametrik Antena Vivaldi Slot dengan Pencatuan Mikrostrip in Proceeding of SENATEK 2015, 397-403.
Rajaraman, Raviprakash. (2004). Design Of a Wideband Vivaldi Antenna Array for the Snow Radar. PhD dissertation/master’s thesis, University of Kansas.
62 Lampiran 2. Publikasi (2)
Developing of Ground Penetrating Radar (GPR) Data Processing
Baso Maruddani1,2 and Efri Sandi1
1 Universitas Negeri Jakarta, DKI Jakarta 13220 Indonesia
2 DJA Institute, DKI Jakarta 13220 Indonesia Email: [email protected]; [email protected]
Abstract—Ground Penetrating Radar (GPR) is one of radar type that is often used to determine conditions inside or below some surface. GPR is also commonly used as a material evaluation tool by its trait as a non-destructive testing (NDT). One of the most important sections of GPR is signal processing system or GPR data processing that will filter all of the GPR survey results. Reflection signals gained by the radar antenna are then filtered to discover any objects located below the surface of the ground. The better of process in filtering data, the more accurate for GPR to interpret the gained signal. This study aims to design a GPR data processing system that is sufficiently be able to interpret the gained signal so that can accurately discover any objects located on the ground. This GPR data processing system is expected to working on a variety of frequencies and the application can develop in various types. The aim of this study are designing and modifying the GPR data processing system.
Index Terms—GPR, processing, dewow, filtering, gain
I. INTRODUCTION
Applications for wireless communication systems are vary greatly. Radar is one of the applications where the transmitter and receiver are in the same place. Ground Penetrating Radar (GPR) is a wireless communication system that is used to view any objects located under the surface of the ground or behind the walls. GPR can "view" through the ground by sending the electromagnetic signals to a certain object and then gaining a reflection signal from the signal sent earlier and reconstructing that reflected signal. How to reconstruct reflected signals is
by processing the reflected signals to be an image. GPR design is highly depend on the application to be used. Therefore, GPR to
"view" the inner surface is basically different from GPR to see the shallow surface [1].
GPR has very wide applications, including for geology, archeology, civil engineering, non- destructive testing (NDT) and in the field of defense and security. Several studies have been conducted on GPR. Both from the hardware side, namely the antenna, and from the software side [2]. On the hardware side, research that has been conducted was about the selection of the GPR working frequency. The choice of antenna working frequency used in GPR devices depends on the application used, because each antenna has a radiation pattern and some characteristics will affect the final interpretation of the GPR readings results [3]. Several studies have been conducted in [4], [5], [6] to improve the accuracy of the GPR reading results system and the development of the antenna model used.
The antenna design has also been compared comprehensively in [7]. Explained in [7] that the antenna working frequency, antenna gain and antenna impedance were tested to determine the compatibility with the GPR application that was implemented.
The research on GPR data processing has been conducted in [2], [8], [9], [10], [11], [12], [13]. In [2], software for GPR data processing from R – language was created, called RGPR.
RGPR is built based on two classes to filter and visualize GPR data by paying attention to step by step data filtering process. There are many