Radar Modeling Experiment Using Vector Network Analyzer

Pramudita, Aloysius Adya; Praktika, Tyas Oksi; Jannah, Solihatul

doi:10.23919/isap47053.2021.9391495

Cited by 6 publications

(6 citation statements)

References 5 publications

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“…In this research, the SFCW radar system was realized to operate with a frequency range between 500 MHz to 3 GHz. Respecting the capability of the Vector Network Analyzer (VNA) for radar modeling reported in [48], the Mini VNA was employed as the transceiver part of the radar. The first port is operated as the transmitter, and the second port is operated as the receiver.…”

Section: A Radar-drone For Soil Water Content Estimation On Tea Plant...mentioning

confidence: 99%

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Soil Water Content Estimation With the Presence of Vegetation Using Ultra Wideband Radar-Drone

Pramudita

Wahyu²,

Rizal

et al. 2022

IEEE Access

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Radar-drone system is potentially implemented as a method for collecting the soil water content of a large area. Vegetation that may covers the soil surface affects the detection results of soil water content using radar system in plantation areas. Vegetation will influence the propagation mechanism of radar waves, therefore, a method to overcome this effect is needed. The method to compensate the effect of vegetation based on a transmission line model is then proposed in this paper. The transmission line model is used as the concept for transforming the measured reflection coefficient under the vegetation effect to the ground reflection coefficient value. Experiments were carried out by taking a case studies on tea plantations. The tea plant becomes a vegetation layer which its effect needs to be considered on the detection of soil water content. An ultra-wideband radar system with a frequency range of 500 MHz -3 GHz is proposed in this study. The radar is integrated to hexacopter drone for scanning the tea plantation areas. The radar-drone system flight with a constant elevation from ground level. The experimental results show that the proposed method is able to improve the detection results of soil water content using radar with an accuracy of 96%. The radar-drone performance in detecting soil water content is suitable for precision farming purposes.

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Section: A Radar-drone For Soil Water Content Estimation On Tea Plant...mentioning

confidence: 99%

“…Furthermore, the received signal can be reconstructed by calculating the inverse Fast Fourier Transform that is written in (5). The steps of reconstructing the received signal from the measured S 21 data have been explained in [48].…”

Section: A Radar-drone For Soil Water Content Estimation On Tea Plant...mentioning

confidence: 99%

Soil Water Content Estimation With the Presence of Vegetation Using Ultra Wideband Radar-Drone

Pramudita

Wahyu²,

Rizal

et al. 2022

IEEE Access

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“…The VNA is set to take S21 measurements with a frequency range that matches the radar system. The S21 data represents the transfer function between the send signal and the received signal [10,19,20]. This data is subsequently sent to the computer to carry out the reconstruction process from the received signal.…”

Section: Radar Modeling Using a Vector Network Analyzer (Vna)mentioning

confidence: 99%

“…The steps for modeling the radar were discussed in Ref. [10]. First, the required equipment is prepared as shown in Fig 2 . Several functions are set in VNA including frequency range, measured data sample, complex data format, and S21 measurement.…”

Section: Radar Modeling Using a Vector Network Analyzer (Vna)mentioning

confidence: 99%

Modeling of Cavities Detection in The Tree Stemsection Using Radar Vector Network Analyzer (VNA) Elaborating Radon Transform

Dwinanda

Nugroho

Pramudita

2022

JMECS

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Trees are one of the most useful plants for life on earth. However, trees can be harmful due to cavities in the stem sections. Rapid detection is needed to prevent several losses that may arise due to fallen trees. This research identified a hollow and non-hollow tree stem section of flamboyant tree with a sub-surface detection radar system. The sub surface detection radar system was modeled using a Vector Network Analyzer (VNA) connected to a Vivaldi antenna. VNA emitted electromagnetic waves to the tree stem section and subsequently propagated and penetrated hollow tree stem section. The propagation wave met the boundary plane between the wood and the cavity which reflected the electromagnetic waves. The reflected wave was caught by antenna and was display by the VNA as S-Parameter. This research used a Vivaldi antenna with a working frequency of 1 GHz – 10 GHz and a VNA with working frequency 300KHz - 8GHz. The difference in the amplitude of the signal could be seen from the results of cavity measurements made at one point. By implementing circular scanning method with inverse radon transformation, this research could identify a 19 cm diameter wood with a hole of 6 cm and 9.5 cm diameter filled with water, respectively. It was observed that the optimal detection was obtained by placing object between the antennas. This research has signified the application of radar modeled with VNA for detecting the cavities in tree stem section.

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“…VNA is a measuring instrument used to measure scattering parameters, namely S 11 , S 21 , S 12 , and S 22 of a system [18]. The parameters measured by the VNA are far-field and near-field parameters on the antenna.…”

Section: F Radar System Modelling On Vector Network Analyzer (Vna)mentioning

confidence: 99%

Pengaruh Dinding Penghalang pada Deteksi Tanda Vital Pernapasan dengan Through Wall Radar

Ridhia

Pramudita²,

Wahyu³

et al. 2022

JNTETI

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Through-Wall Radar (TWR) telah banyak diaplikasikan dalam berbagai bidang, salah satunya dalam pencarian atau evakuasi korban bencana yang tertimpa reruntuhan. TWR merupakan pengaplikasian sistem radar yang bekerja pada rentang frekuensi yang lebar atau ultra-wideband (UWB) sehingga memiliki tingkat akurasi yang tinggi dalam mendeteksi objek di balik dinding. Pada penelitian ini, antena Vivaldi digunakan untuk mendapatkan tingkat resolusi yang tinggi karena mampu bekerja pada UWB. Untuk menghasilkan tingkat akurasi yang tinggi, dibutuhkan parameter seperti karakteristik dielektrik untuk setiap jenis penghalang yang digunakan. Eksperimen pada penelitian ini dilakukan untuk mengetahui pengaruh dinding penghalang pada deteksi tanda vital pernapasan menggunakan sistem radar. Sistem radar dimodelkan menggunakan dua metode, yaitu dengan vector network analyzer (VNA) dan bladeRF. Eksperimen dilakukan dalam beberapa tahap, yaitu pembuatan desain sistem eksperimen, pengambilan data eksperimen, pengolahan hasil data eksperimen, dan analisis hasil eksperimen. Jenis dinding yang digunakan pada penelitian ini adalah dinding bata Hebel dan dinding kayu. Hasil data eksperimen pada penelitian ini digunakan untuk menganalisis pengaruh penghalang pada deteksi tanda vital pernapasan menggunakan sistem radar. Eksperimen menggunakan VNA sebagai sistem radar dilakukan untuk menganalisis pengaruh dinding penghalang pada deteksi target di balik dinding penghalang. Eksperimen menggunakan bladeRF sebagai sistem radar dilakukan untuk membuktikan ada atau tidaknya pengaruh penghalang pada deteksi tanda vital pernapasan menggunakan sistem radar. Hasil pengukuran menunjukkan bahwa penurunan amplitudo sinyal peak-to-peak terbesar terjadi pada deteksi target dengan jarak 125 cm, yaitu sebesar 11,51 dB, dan delay sebesar 0,084 ns, saat menggunakan penghalang bata Hebel. Sementara itu, saat menggunakan penghalang kayu, penurunan rata-rata amplitudo sinyal peak-to-peak sebesar 2,968 dB dan delay sebesar 0,006 ns.

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Radar Modeling Experiment Using Vector Network Analyzer

Cited by 6 publications

References 5 publications

Soil Water Content Estimation With the Presence of Vegetation Using Ultra Wideband Radar-Drone

Soil Water Content Estimation With the Presence of Vegetation Using Ultra Wideband Radar-Drone

Modeling of Cavities Detection in The Tree Stemsection Using Radar Vector Network Analyzer (VNA) Elaborating Radon Transform

Pengaruh Dinding Penghalang pada Deteksi Tanda Vital Pernapasan dengan Through Wall Radar

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