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Progress In Electromagnetics Research Letters, Vol. 9, 49–57, 2009 ANALYSIS EFFECT ANTENNA J. S. Mandeep OF WATER ON A KA-BAND Jabatan Kejuruteraan Elektrik, Elektronik, and Sistem Fakuliti Kejuruteraan dan Alam Bina Universiti Kebangsaan Malaysia 43600 UKM Bangi, Malaysia Abstract—Wet antenna attenuation during rain events is examined through carrying out simulated rain experiments. These were conducted on the receiving antenna located at Penang, Malaysia. The findings from these experime
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  Progress In Electromagnetics Research Letters, Vol. 9, 49–57, 2009  ANALYSIS EFFECT OF WATER ON A KA-BANDANTENNAJ. S. Mandeep Jabatan Kejuruteraan Elektrik, Elektronik, and SistemFakuliti Kejuruteraan dan Alam BinaUniversiti Kebangsaan Malaysia43600 UKM Bangi, Malaysia Abstract —Wet antenna attenuation during rain events is examinedthrough carrying out simulated rain experiments. These wereconducted on the receiving antenna located at Penang, Malaysia. Thefindings from these experiments are used to estimate rain attenuationdata for that path by adjusting the collected data for wet antennaattenuation. This was done for the 1-year period of March 2007to February 2008 and includes average and worst month cumulativedistribution functions. The results of the measurement indicatedthat the wet antenna effect is a significant attenuator, and shouldbe included in a link budget. The measured attenuation values were4dB for the wet feed window and total reflector plus feed windowattenuation value of 6.3dB at 20.2GHz, at a rain rate of 100mm/h. 1. INTRODUCTION The performance of millimeter-wave and centimeter-wave antennasis degraded during wet weather. In particular, if radomes are usedto protect the antenna system, layers of liquid form and modify thewave-fronts through absorption, reflection, refraction, and scattering.Similarly, liquid on a perfect reflector produces undesirable effects, buta given thickness of liquid is not nearly as serious on a reflector as ona radome [1]. The receiving antennas of the advanced communicationstechnology satellite (ACTS) propagation experiment have been shownto introduce attenuation of their own when their surfaces becomewet [2,3]. This attenuation is in addition to the rain-inducedattenuation along the propagation paths. The magnitude and nature Corresponding author: J. S. Mandeep (mandeep s75@yahoo.com).  50 Mandeep of the wet-antenna attenuation has been the subject of numerousinvestigations [3–5]. The main findings of these investigations are theantenna attenuation due to surface wetting could reach values of 10dBat Ka-band and the antenna attenuation during rain at any instant of time is essentially related to the amount of water accumulated on theantenna surfaces at that instant. It is, however, largely independent of the instantaneous rain rate. In general, wet radome surfaces result inmuch higher attenuation than that due to wet reflectors.In general these results showed that feed wetness are the maincontributor to the system losses, with reflector wetness being a lesserfactor. The water in the feed aperture distorts the electric field’sdistribution of the feed creating a high perturbation on the feedstanding wave ratio (SWR). The reflector losses can be explained byadditional scattering losses due to rain drop’s size at the surface of the reflector. This creates a distorted reflector surface that reducesthe antenna gain by several dB’s in the worst case. Frequency scalingmay not seem to hold when the antenna is saturated with water, afactor that need’s to be considered in a system design that employsfade compensation and frequency scaling [6].It may not be possible to extract the true instantaneous pathattenuation data from the measured data, but it would be useful tohave reasonable estimates of the path attenuation, estimates that couldbe used with a measure of confidence in system design and in modelingand frequency scaling [7]. The key to separating path and antennaattenuation lies in estimating the latter through simulated-rainexperiments. Using the information obtained from these experiments,suitable models can be developed for estimating attenuation along thepath. These experiments were conducted on the Ka-Band receivingantenna at Universiti Sains Malaysia (USM), under conditions similarto those prevalent during rain events. The preliminary analyses of these measured data, together with the corresponding predicted rainattenuation, are discussed. The results strongly suggest that water onthe radome has a significant consequence on the received signal level. 2. METHODOLOGY The main station for the experiment was located at University SainsMalaysia (USM) (Lat.: 5.17 ◦ N and Long.: 100.4 ◦ E) in Nibong Tebal,Penang and is about 7km from the sea and about 57m above mean-sea-level. The transmitted EIRP of the antenna is 17.0dBW with aRight Handed Circular Polarization and a modulation of PCM thatuses a horn type of antenna. The antenna is a 1.2m parabolic dishwith off-axis feed horn. With the elevation angle of 60 ◦ , both dish  Progress In Electromagnetics Research Letters, Vol. 9, 2009 51 and feed horn face upwards. The experiments were performed on cleardays when there was no rain activity along the propagation path. Theexperimental setup consisted of a system of 7 elevated sprinklers, whichresulted in high rain rates above 100mm/h (2m above the antenna),adjustable to produce sprays of a wide range of drop size and intensity,ranging from heavy showers to mist-like precipitation. The sprays fromthe sprinklers were directed upwards. A pump in the water line feedingthe sprinklers forced sprays to rise in the air more than 2m furtherbefore falling on the antenna in a simulated rain fashion. Figures 1 Rain SimulatorReflector/DishFeed Figure 1. Experimental setup. Antenna and ODUPersonalDataLoggingSystemBeaconIDUComputerLevelMonitor Figure 2. Beacon measurement setup.  52 Mandeep and 2 shows the experimental and beacon measurement setup. Thereceiver setup for measurement is shown in Figure 2. It consists of an antenna, an outdoor unit (ODU), and indoor unit (IDU), a beaconlevel monitor, data logging system and a personal computer for userinterface. The ODU houses the waveguide and low noise amplifier(LNA) and is mounted at the focal point of the parabolic dish. Itdownconverts the Ka-band beacon signal frequency to an intermediatefrequency (IF) of 955MHz. The ODU is connected to the IDU usinga coaxial cable. The IDU which houses the power supply unit isalso used for setting the data transmission mode, transmitting andreceiving frequency, transmission output power and transmission rate.The beacon level monitor is connected to the IDU and placed indoor.To account for any variation in the satellite signal strength dueto orbital variations, the average clear day signal strengths on the dayprior to and after the rainy day(s) were used in computing the rainattenuation. Calibration of equipments are done for every 6 months.For average attenuation computation, the output signal of thereceiver antenna, at the dish, was connected to a spectrum analyser,which was interfaced to a computer via a labVIEW-interfacing card.The labVIEW was programmed to record the peaks of sixty successivesamples each of 1ms duration. The software then calculates the meanof these sixty peak values. These recordings were then repeated every10s giving six averaged peak values in a minute.The rain rate was measured using a Casella tipping bucketarrangement of diameter 20cm. The large diameter of the tippingbucket rain gauge was selected so that a more accurate measurementof the rain rate can be made. The rain gauge had its own programmabledata logger. The clock of this was regularly synchronized with that of the computer and the lag in time observed was 4s in one week. Therain rate was computed from the frequency of the tips of the tippingbucket rain gauge. The standard tipping bucket used had a calibrationof 0.2mm/tip. The tip times were recorded on the built in data loggerof the rain gauge. The average rain rate was calculated using the timeelapsed between successive tips.The uncertainties in the beacon measurements, the uncertainty inthe rain rate estimates and the variations due to wind are all consideredto be independent zero mean random processes. Table 1 showsestimated upper bounds for the standard deviation in the attenuationdue to each individual effect and the total standard deviation wascalculated by adding the variances as follows[7], σ 2 total = σ 2 beaconmeasurement + σ 2 rainrate + σ 2 wind (1)For the error budget in Table 1, the standard deviation which is the
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