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Environmental-data Collection System for Satellite-to-Ground Optical Communications

Kenji Suzuki, Dimitar Kolev, Alberto Carrasco-Casado, and Morio Toyoshima

National Institute of Information and Communications Technology (NICT), Japan

In satellite-to-ground optical communications, it can be assumed that the link will be established if site diversity is performed among two or more ground stations connected with the terrestrial network. To be able to show effectively which of the separated ground stations has a clear line of sight it is necessary to store a historic registry of weather data and statistically analyze it to make predictions. Therefore, the data from ten environmental-data collection sta-tions throughout Japan has been collected and analyzed for a statistically-long time. This paper shows the overview of this system.

Key Words: Satellite Communications, Optical Communications, Site Diversity

Nomenclature

To : Sky temperature Ta : Ground surface temperature

Tm : Ground surface average temperature (few-days average value)

Ts Average sea level temperature h Height above sea level

Cr Cloudage Ct Cloud height

1. Introduction As the resolution of Earth-observation satellite sensors increases, the quantity of data they produce also increases. In an optical-communication system of an Earth-observation satellite, even though communicating with a geostationary data relay satellite at 1.5-2.5 Gbps, the slower feeder downlink from the geostationary data relay satellite to the OGS (Optical Ground Station) implies that not all the acquired data can be downloaded in real time. Further study is needed for a broadband satellite commu-nication system that uses light or millimeter waves for the feeder link from the geostationary data relay satellite to the ground station or for a direct downlink from the Earth-observation satellite to a ground station. However, light and millimeter waves are both susceptible to attenua-tion by rain or clouds, which can interfere with communi-cations. Research on weather relevant to optical satellite communication, such as the extent of regions of clear skies, includes analysis of digital weather instrument data from the weather satellite “Himawari”, AMeDAS, and other sources of the Japan Meteorological Agency1) 2). However, there has been no verification of the site diversity effect taking actual satellite orbits into account by in-site long-term acquisition, storage, and analysis of data such as the statistical distribution of clear-sky regions, cloudage, and cloud height. We therefore took as our objective the

verification of the effectiveness of the site diversity tech-nique by the analysis of environmental data accumulated over a statistically-long period of time. For the collection of the environmental data, which is also necessary for practical free-space optical communication, we used the facilities of the National Institute of Information and Communications Technology (NICT) at ten geographically widespread locations at different longitudes and latitudes across the Japanese archipelago3)4).

Fig. 1 Configuration of an environmental-data collection system

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2. Environmental Data Collection System 2.1. Overview

Fig. 1 shows the configuration diagram of the environ-mental-data collection system OBSOC (Observation sys-tem of the patch of Blue Sky for Optical Communication) installed at ten observation stations located across Japan and an environmental-data collection, analysis and display server installed at a center station. The collected data is transmitted to the center station via a terrestrial network at specified time intervals. The observation stations are con-trolled entirely from the center station, allowing a ful-ly-automated operation. Fig. 2 shows the ten locations at NICT facilities throughout Japan where the observation stations were installed.

The locations have a line-of-sight elevation angle of 5 degrees or more to ensure a field of view as wide as possi-ble for the whole-sky camera. When the station is installed on a rooftop, it is placed as far as possible from outdoor units of air conditioning systems to prevent effects on the cloudage and ceilometer sensors.

Fig. 2 Location of the environmental-data collection stations

2.2. Environmental-data collection stations The environmental-data collection stations are equipped

with the sensors listed in Table 1. The data from the whole-sky camera for identifying clear-sky regions (about 200 Kbytes per image), the cloudage and ceilometer in-struments, and the various weather instruments is collected at a rate of 263 bytes per measurement. The weather in-struments installed in the stations (3 to 5 in Table 1) were of the same grade as certified by the Meteorological Agency to ensure data reliability.

A block diagram of the environmental data collection system is shown in Fig. 3. To protect the equipment, which is exposed to the weather outdoors, and to prevent effects from upstream equipment, a discharge-and-insulated-type SPD (Surge Protective Device) is used to protect the net-work system against lightning strikes, and a discharge-type SPD, breaker and UPS (Uninterruptible Power Supply) are used to protect the power supply. An example of a field installation of an environmental-data collection system is shown in Fig. 4. It is designed to withstand wind speeds of 50 m/s at the installation location with no part of the equipment blown away (maximum instantaneous wind speed; the design for the Okinawa installation is 90 m/s).

Table 1. Specification of the measurement sensors

Sensor Specification

1) Whole-sky camera VGA image with the color CCD

fisheye lens (170deg of viewing

angle)

2) Cloudage/Ceilometer Angle of field 60 degrees infrared

radiometer. 5 directions of the zenith

and the north, south, east and west

direction

Amount of Cloud: 0～100%±6%,

Ceilometer: 0m～8000m±200m

3) Temperature -60℃～60℃ (±0.2℃@20℃)

4) Humidity 0%～100%RH,±1%RH(0～90%),

±1.7%RH(90～100%)

5) Pressure 500～1100hPa±0.15hPa (Resolution:

0.01hPa)

6) Illumination/insolation 0～2000W/m2

7) Anemoscope/

Anemometer

50m/sec Max (Survival wind speed

100m/sec)

8) Rain gauge Tipping bucket type with heater:

±0.5mm (～20mm), ±3% (20mm～)

Fig. 3 Block diagram of the environmental-data collection system

Fig. 4 Environmental-data collection station (Taiki-cho Hokkaido)

2.2.1. Whole-sky camera A highly-sensitive color CCD with a fish-eye lens cap-

tures VGA images of the entire sky. The images are output in JPEG compression format. The inside of the dome can-not be fogged by a heater and air-circulation fan that oper-ate according to the outdoor air temperature and dome temperature. Other sensors include proprietary atmospheric pressure sensors and an infra-red thermometer oriented toward the azimuth. The day and night whole-sky camera

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images acquired at NICT Koganei (Fig. 5 and Fig. 6) show that regions of clear-sky and clouds are clearly distin-guished.

Fig. 5 Whole-sky camera image (daytime)

Fig. 6 Whole-sky camera image (night time) 2.2.2. Cloudage and ceilometer instruments

A photograph of the cloudage and ceilometer instru-ments is shown in Fig. 7. Five infra-red temperature sen-sors that have a 60-degree field of view are arranged with one oriented to the zenith and the other four oriented to the north, south, east and west at elevation angles of 55 de-grees. The sensors have the same specifications for power supply and control communication based on RS485.

The cloudage (Cr) is obtained by calculating the rela-tion of the ground surface temperature (Ta) and infra-red temperature (Sky temperature: To) to the cloudage ob-tained from the ground surface temperature and infra-red temperature and the whole-sky camera image data that has been accumulated on the basis of the coefficients of the statistically calculated correlation function (Fig. 8). Tm is the ground surface average temperature. Ts is the average sea level temperature.

The cloudage Cr estimation is calculated as follows:

(1)

a = a1×Ts+b1 (2)

b = a2×Ts+b2 (3)

Ts = Tm+0.0065×h (4)

(5)

Cloud height (Ct) is obtained from the ground-surface temperature and infra-red radiation temperature, with the reference value being -45°C at 8,000 m above sea level5).

Fig. 7 Cloudage and ceilometer instruments

Fig. 8 Cloudage and cloud height estimation image

2.2.3. Estimated Cloudage and height The environmental trends indicated by the changes in

data from the whole-sky camera, zenith-oriented infra-red thermometer, outdoor air temperature, and atmospheric pressure are presented in Fig. 9. The cloudage and cloud height can be estimated from changes in the ground tem-perature and upper air temperature, within the 60-degree field of view. When the temperature is low and clouds ap-pear in a clear-sky region, the temperature rises and it is judged that clouds are present. Fig. 10 shows an example of the whole-sky camera image, the estimated cloudage and the cloud height.

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Fig. 9 Environmental-data trends (Kashima)

Fig. 10 Whole-sky camera image, cloudage and cloud height (StarBED)

2.3. Environmental-data collection, analysis and dis-play server

The environmental data collected by the system at each observation station is stored on a environmental-data col-lection, analysis and display server of the center station located at NICT Headquarters, in Koganei (Tokyo). The data is analyzed to determine the degree to which windows for free-space optical communication between satellites and ground stations can be ensured. The environmen-tal-data collection, analysis and display server has the functions described below. 2.3.1. Monitoring and control

The environmental-data collection, analysis and display server monitors the situation at the observation stations and sets the data acquisition intervals, etc. 2.3.2. Estimation of the proportion of time in which space-to-ground optical communication is possible

The periodically-transmitted environmental data is used to estimate the total cloud cover and clear-sky region ratio (determination of clear-sky regions), visibility, etc. at each observation station, and statistical data processing to de-termine daily averages, etc. is performed. The resulting data is registered in a database. 2.3.3. Data display function

Fig. 10 shows the real-time environmental-data display. Trend graphs that include the most recent environmental data for all the observation stations are displayed by an Internet browser (Fig. 11).

The IEEE 1888 FETCH protocol is also supported. Fur-thermore, a past-data search and display function retrieves search results for the specified search conditions, which include the observation station, the time and day of the observation, and a range of instrument data such as

cloudage and cloud height, and displays the results as a list or a graph, or the whole-sky camera images that corre-spond to the search results.

Fig. 11 Real-time environmental data display

(http://sstg.nict.go.jp/OBSOC/ ?lang=e)

Fig. 12 Trend graphs of environmental data

2.3.4. Estimation of laser communication windows for optical communication considering the satellite orbit

This function takes the TLE (Two-Line Element) orbit elements of the assumed Earth-observation satellite as the input and estimates the visibility at each observation station (clear-sky regions). In addition to searching and displaying environmental data from the observation stations that are in the range of visibility of the satellite and the observation time, statistical processing of the proportion of times at which optical satellite communication is possible is per-formed (Fig. 13).

Fig. 13 Estimation of laser communication windows

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3. Site-diversity technique

Fig. 14 shows annual clear-sky rate (1st June 2014-31st May 2015) of ten observation stations. In 2016, the rainy season in Kanto region happened from 5th to 18th of June. Fig. 15 shows the strong impact this season has on light propaga-tion, e.g. the annual clear-sky rate in the Koganei OGS is usually 56.4%, but during the 2016 rainy season was only 11%.

Fig. 14 Annual clear-sky rate (1st June 2014-31st May 2015)

Using OBSOC environmental-data to measure the at-mospheric transmittance and the cloud coverage applied to the NICT SOTA mission, it is possible to estimate the link probability in each pass over the ground stations (fig. 16). When using 2 OGSs, the probability increases from around 50% up to 77%. If three OGSs can be selected in every pass, the probability increases up to 100%. This means that three OGSs could be enough to mitigate the effects of the clouds completely, even in the rainy season6).

Fig. 15 Clear-sky rate average and rainy season

Fig. 16 Link probability per SOTA link during 2016 rainy season

4. Conclusion

Satellite optical communications will likely change the way we transmit information from space. However, the atmos-pheric-related issues are not yet fully solved. Site diversity is the most important technique to guarantee continuous opera-tion. For site-diversity techniques to work properly, a thor-ough characterization of the local weather of each site is nec-essary to monitor the conditions in real time and predict the handovers from one ground station to another. In this paper, the on-site weather-data collection system developed in NICT was described.

We plan to verify the correlations between the laser wave-lengths used in free-space optical communication and envi-ronmental data, collect, store and analyze environmental data that cover a period of at least three years, predict site-diversity line of sight at the time the satellite is passing for establishing free-space optical communication between satellites and ground stations, and investigate algorithms for optimum ground station selection.

References

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3) Suzuki, K., Kubooka, T., Fuse, T., Yamamoto, S., Tsuji, H., Mori-kawa, E., Takayama, Y., Kunimori, H., and Toyoshima, M.: Ex-perimental System for Site Diversity through Statistical Processing of Environmental Data for Optical Communication between Satel-lites and Ground Stations, IEICE 2013 Society Conference, B-3-21, p229, 2013-09(in Japanese).

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6) Carrasco-Casado, A., Kolev, D., Suzuki, K., and Toyoshima, M.: Improvement of Link Availability with Site-Diversity Techniques and efforts on Standardization of Weather Characterization, IEICE 2017 General Conference, B-3-32, p263, 2017-03.