Identification of Cumulonimbus Cloud using Sensor Data of NOAA

Satellite Captured by Low Cost Flower Cross Dipole

Yenniwarti Rafsyam

, Lingga Ghufira Oktariza

, Jonifan

, Indra Z.

, and Eri Ester Khairas

Department of Electrical Engineering, Jakarta State Polytechnic

Physics Laboratory Gunadarma University

Keywords: kernel-erison method, omnidirectional radiation pattern, right hand circular polarization

Abstract: The implementation of a flower cross dipole could be a promising candidate to receive any information from

NOAA satellite in certain frequency. Flower cross dipole was designed to work in 137 MHz frequency. This

work urgently discusses about identification of cumulonimbus cloud based on NOAA satellite sensor data

which was received by flower cross dipole. The detection system has been developed by real-time monitoring

based on NOAA satellite sensor data, then convert to cloud image. The further study would be focus on

cumulonimbus cloud which causes bad weather in a region. The identification result was validated by

Meteorological, Climatological, and Physical Agency of Indonesia and analyzed by kernel-erison method.

The overall results indicate the flower cross dipole has 1.58 VSWR value with -12.85 dB return loss. In other

hand, the flower cross dipole produced omnidirectional radiation pattern with 11.8 MHz bandwidth and 2.307

dB gain. The low-cost flower cross dipole only has 52.59 cm length with unique and simple design to be

produced.

1 INTRODUCTION

Weather conditions are meteorological elements that

have a high variation in scale of space and time, so it

is difficult to predict. However, weather information

is very important and needed by almost all fields such

as agriculture, transportation, plantations, to early

warning of natural disasters, floods, landslides, and

drought (Sun, 2016). Information on weather

conditions is still limited, one of which is due to

difficult data access. Therefore, we need a technology

system that can determine the exact state of the

national weather. Satellite technology is a necessity

that cannot be avoided anymore at this time because

satellite data is able to quickly display data with wide

coverage.

The National Oceanic and Atmospheric

Administration (NOAA) is a USA scientific agency

that has 19 satellites. The main activity of these

satellites is to observe the ocean and atmosphere on a

global scale (Bosquez, 2016). Hence, it is able to

monitor the territorial waters of Indonesia with a

broad scope for the benefit of weather monitoring.

NOAA satellites are at an orbit altitude of 833-870

km with inclination around 98.7 ° - 98.9 °. NOAA

took aerial photography at around 16:00 to 17:00

WIB. From the images taken by NOAA satellites, it

can be processed so that cloud types and weather

predictions are classified (Rafsyam, 2017) (Rafsyam,

2017). Cumulonimbus clouds are a type of

condensation cloud formed from water vapor and

carried by the wind. The danger of these clouds is it

can produce thunder and bad weather which is usually

found in the tropics area (Sun, 2016) (Dian, 2014)

(Rafsyam, 2017) (Rafsyam, 2071). In addition to bad

weather and lightning, these clouds are also

accompanied by ice and have very cold temperatures.

To detect and predict cumulonimbus clouds, sensor

data is needed from NOAA satellites that cross

Indonesia 2-4 times in 1 day. Hence, NOAA satellite

sensor data can observe the detection of

cumulonimbus clouds in real time (Rafsyam, 2017)

(Rafsyam, 2017).

Earth stations, the satellite signal receiver system

from NOAA satellites with a specified frequency,

have been developed in this work. The earth station

system consists of an omnidirectional antenna to

capture NOAA signals that are connected to a

processing system software. Cross Dipole Antenna is

an omnidirectional system that produces singular

radiation patterns that can receive signals from all

directions. On the other hand, transmissions from

138

Rafsyam, Y., Oktariza, L., Jonifan, ., Z, I. and Khairas, E.

Identiﬁcation of Cumulonimbus Cloud using Sensor Data of NOAA Satellite Captured by Low Cost Flower Cross Dipole.

DOI: 10.5220/0009968100002905

In Proceedings of the 8th Annual Southeast Asian International Seminar (ASAIS 2019), pages 138-143

ISBN: 978-989-758-468-8

NOAA satellites using right hand circular

polarization (RHCP) (Geeta, 2015). Cross dipole

antenna has high gain with circular polarization.

Therefore, antenna design must have a working

frequency of 136 - 138 MHz, impedance of 50 ohms,

and a minimum gain of 12 dBi (Dian, 2014) (Shi,

2016) (Rafsyam, 2017). Sensor data captured by the

dipole antenna should be delivered to a single rectifier

(Vignesh, 2016). The signal is processed by the

software and analyzed using the kernel erison method

to show the comparison of cloud validation from

BMKG with the cloud image analysis results from the

receiver.

2 SYSTEM DESIGN

The system design of the earth station is shown in

Figure 1, consisting of a satellite signal receiver and

processing of the 137.9 MHz NOAA satellite signal

which is real-time and can be accessed anytime and

anywhere. In other hands, the flower cross dipole is

designed in several stages before it can be used as a

NOAA satellite signal receiver. In overall, the

calculation of the length of the antenna element that

can work at frequencies 137-138 MHz and simulates

the antenna design based on the calculation results.

Finally, if it matches the simulation results, the

antenna design is fabricated to be tested and

validated.

Figure 1, the design of a receiver system which

is a system flow diagram for receiving data signal

information received from satellites. Data acquisition

systems can automatically detect and receive

information signals from satellites when passing

through the system. The information signal is

captured by the flower cross dipole and then

separated from the carrier by the receiving radio.

Figure 1: System design of Flower Cross Dipole as sensor

data receiver from NOAA satellite

After the information signal is obtained, the

sound card will work to convert analog data into

digital data. Then the digital signal is processed and

recorded in the form of wav files. This file will then

be used at a later stage, namely image processing. The

signal that is obtained is the sound signal and then

converted to an image.

Then this image can be reprocessed so that it can

detect cumulonimbus clouds (clouds that have the

potential to rain). In satellite signal processing,

WxtoImg, python programming and library opencCV

software is used. The data that is already in the form

of a WAV file is processed further using WxtoImg to

produce an image that has information on the state of

the cloud which will later be reprocessed by openCV

python so it can automatically detect that area has a

cumulonimbus cloud.

3 RESULT AND DISCUSSION

The flower cross dipole as shown in Figure 2, is an

omnidirectional and right circular polarized antenna

that can be proven in the analysis of the antenna test

results shown on the Figure 3. This exactly matches

the antenna pattern from the satellite. The radiation of

cross dipole antenna basically generated from two

orthogonal half-wavelength dipoles fed by two

sources with magnitude 90

phase difference (Xu,

2016) (Bhaskar 2018). The basic cross dipole is

modified in each side of the cross dipole. In figure 3,

shows the radiation pattern with the parameters of

power received by the flower cross dipole and plotted

from an angle of 10

to 360

. If observed in the

horizontal plane and vertical plane, the flower cross

dipole can receive energy distributions that tend to be

the same from all angles. So, the antenna radiation

diagram pattern can be illustrated like a spherical.

This indicates that for the capture of signals from

satellites, the signal's incoming direction can be

received by the flower cross dipole from all

directions.

Identiﬁcation of Cumulonimbus Cloud using Sensor Data of NOAA Satellite Captured by Low Cost Flower Cross Dipole

139

Figure 2. Flower Cross Dipole from above.

Figure 3. Test result of radiation pattern

In antenna testing, the measured parameter is the

amount of energy reflected to the antenna by

measuring the value of S11 or return loss and VSWR

flower cross dipole at a frequency of 137 MHz to 138

MHz. By knowing the amount of return loss, the

amount of energy that can be received by the antenna

can be determined. Antenna test results for the return

loss parameter is shown in Figure 4, resulting in a

return loss value of -12.85 dB. From Figure 4, the x

axis shows frequency and y axis shows return loss,

with detected frequency range 100-300 MHz. Return

loss is known as the ratio of reflected power from a

load to the power on that load and expresses in dB

(Cui, 2014). Return loss provides is helpful, as it

provides a real valued measure of load match.

Another parameter of the load match traditional real

valued measure is voltage standing wave ratio

(VSWR).

Figure 4: Simulation test result of Flower Cross Dipole in

return loss

Figure 5: Simulation test result of Flower Cross Dipole

VSWR parameters

Figure 5 shows the antenna test results for the

VSWR parameter which produces a value of 1.58.

The VSWR value is a conversion of the S11 value

which shows the ratio of the maximum stationery

wave voltage to the maximum travelling wave

voltage that occurs on the flower cross dipole when

capturing satellite signals. With a VSWR value of

around 1.5, the antenna is good enough to be used as

a cross dipole antenna. The antenna test results for the

S11 and VSWR parameters are validated and shown

in Figure 6 which shows the flower cross dipole can

capture satellite signals at 137.9 MHz with the same

value of S11 and VSWR as the test results in Figure

4. Gain which obtained from the simulation results

was 2.307 dB with frequency 137.9 as shown in

Figure 5.

ASAIS 2019 - Annual Southeast Asian International Seminar

140

Figure 6: Radiation pattern of Flower Cross Dipole as

receiver

Basically, NOAA satellites record an area by

receiving Advanced Very High Resolution (AVHRR)

data from satellites in the form of 2-4 raw data in one

day. In this study, the flower cross dipole received

NOAA satellite sensor data and was carried out by

following the NOAA satellite schedule that passed in

the territory of Indonesia (Rafsyam, 2017)

. NOAA

satellites that are currently active are NOAA 15,

NOAA 18 and NOAA 19 (Uengtrakul, 2014). Test

that have been carried out by connecting the flower

cross dipole with the RTL-SDR dongle is used to

receive signals sent by NOAA satellites (Uengtrakul,

2014).

Figure 7 show us the validation of result of the

flower cross dipole after fabricated. The result of the

parameters are -17, 692 dB of return loss and 1,357

of VSWR. This result performs better than simulation

value which the return loss is below -10 dB while the

VSWR is below 1.92 (Kaur, 2016). The reference

values realize polarization conversion of the reflected

wave, the reflected and directed wave emitted from

flower cross dipole will generate polarization wave,

like circular polarization (Chen, 2015).

Figure 7: Validation result of Flower Cross Dipole

The cumulonimbus cloud detection test aims to

detect cloud from the cloud color gradation

parameters formed. The cumulonimbus clouds with a

wide range of dense clouds with white light color

indicates bad weather conditions in an area. Results

from Signal catched from NOAA satellites 18 in the

form of sound are recorded with the help of SDR

Sharp software (Bosquez, 2016). The software reads

the signal level received at different times and days.

After that the recorded sound signal is converted into

image form with WXtoImg (Mahmood, 2016). The

results of this image will be analyzed and validated

with BMKG data. Image analysis is shown in Figure

8 using the OpenCV Python kernel 2x2.

Cumulonimbus clouds detection can be determined

from the color and gradient of clouds formed in

Figure 8 and most colors of cumulonimbus clouds are

white light. Based on the validation with BMKG data

in Figure 7, the results of the detection of

cumulonimbus clouds by using a flower cross dipole

Identiﬁcation of Cumulonimbus Cloud using Sensor Data of NOAA Satellite Captured by Low Cost Flower Cross Dipole

141

as a NOAA satellite signal receiver have 9% error of

Figure 9.

Figure 8: Meteorological, Climatological, and Physical

Agency of Indonesia validation

Figure 9: Image processing result using openCV Python

kernel (2x2)

4 CONCLUSION

In this study, fabrication of flower cross dipole with a

working frequency of 137.9 MHz was successfully

tested and validated with several parameters such as

VSWR, S11, and gain. The radiation pattern formed

is omnidirectional, so that it can receive signals and

waves from all directions. Signal processing that has

been received by the antenna is validated with the

BMKG image results and the percentage of error

resulting from image processing is 9%. Hence, the

flower cross dipole can be used as a candidate for

satellite receiver signals at a working frequency of

137.9 to detect bad weather due to the presence of

cumulonimbus clouds in an area. Moreover, the

flower cross dipole is a low-cost antenna with

aesthetically unique design and shape.

ACKNOWLEDGEMENT

This research is supported by research grand from

Simlitabmas RISTEKDIKTI and P3M Politeknik

Negeri Jakarta (PNJ) with research program No

023/SP2H/LT/DPRM/2019.

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