# Low-Cost _Ka_-Band Satellite Receiver Data Preprocessing for Tropospheric Propagation Studies
Thus, Global Navigation Satellite System (GNSS)-derived measurements provide an excellent means of predicting water vapor attenuation, hence helping define the reference level [13]. Another option would be using numerical weather data (prediction/reanalysis) particularized for the tropospheric volume around the Earth station [14]. The latter technique is quite effective in determining water vapor attenuation [15; 16], even in tropical areas [17]; however, the \(A_{c}\) estimation is not so reliable, at least on an event-by-event basis. In our case, faced with the impossibility of using a radiometer to remove cloud and gas attenuation directly [12; 13], we relied on the fact that the attenuation variations caused by rain are much faster than those due to, on the one hand, the combined effect of a likely small mispointing of the antenna together with the movement of the satellite and, on the other, to gases, clouds, and the daily thermal cycle on the LNB electronics. We can subject the acquired time series to a high-pass filtering process to remove these effects, thus retaining the faster ones, namely \(A_{r}\) and \(A_{s}\). The specific procedure involves subtracting a stable, reliable set of reference levels (template) from the raw received beacon levels. The template is mostly extracted from observations during non-rainy periods. Note that this operation removes all slowly varying effects. The result of this procedure is the excess attenuation that contains \(A_{r}\) and \(A_{s}\). The excess attenuation is the variation of the raw received beacon signal with respect to the template. Although it has not been installed in our system, it is interesting to note that thermal effects on the unit electronics can be partially compensated for by using Peltier cells attached to the LNB metal enclosure, as in [18]. A good approach to using this technique is to keep the LNB at a constant temperature of, for example, 50 \({}^{\circ}\)C. In the referenced case, this was easier because their receiver was totally located indoors looking at AlphaSAT through a millimeter wave transparent window, while our Radio-Frequency (RF) unit was outdoors (Section 2.1.1). Moreover, looking into the work reported by others, in [8], the authors discussed that the level fluctuations they observed were due to antenna strut thermal expansion. Their setup (4.2 m dish, \(\approx\)56.5 dBi gain, \(\approx\)0.25\({}^{\circ}\) beamwidth) included a very large dish and a temperature-stable receiver. However, our antenna (65 cm dish, \(\approx\)40.5 dBi gain, \(\approx\)1.6\({}^{\circ}\) beamwidth) was significantly smaller and the radiation pattern sufficiently wide so that thermal, mechanical expansion was not an issue. Finally, to separate \(A_{r}\) from \(A_{s}\) in the excess attenuation, low-pass filtering is often used to remove the fast-varying attenuation due to scintillation, which has spectral components up to about 3 Hz, while rain is much slower [19]. Typical cut-off frequencies to remove \(A_{s}\) are on the order of 0.02-0.04 Hz [19; 20]. This is normally done with a running mean filter with a duration of between 1 min and 2 min [10; 21]. Sometimes, more sophisticated filters, e.g., a Butterworth of fifth order, as in [19], or a squared-cosine, as in [22; 23; 24], can be used. In this paper, we concentrated on the preprocessing phase indicating \"conditioning\" of the row data. Further, actual identification of rain events and extraction of monthly, seasonal, or yearly statistics of first order (CDFs, cumulative distributions) or second order (time dependent) such as event durations, slopes, etc., need to be carried out, but are outside of the scope of this paper. For a detailed description of these tasks, refer, for example, to [2; 3]. This paper is organized as follows. Section 2.1 presents the experimental setup, including the beacon receiver and the available local meteorological data. The template extraction methodology is described in Section 2.2. Section 3 shows several templates extracted on non-rainy days.