Coupling radio propagation and weather forecast models to maximize Ka-band channel transmission rate for interplanetary missions

Deep space (DS) missions for interplanetary explorations are aimed at acquiring information about the solar system and its composition. To achieve this result a radio link is established between the space satellite and receiving stations on the Earth. Significant channel capacity must be guaranteed to such spacecraft-to-Earth link considering their large separation distance as well. Terrestrial atmospheric impairments on the space-to-Earth propagating signals are the major responsible for the signal degradation thus reducing the link’s channel temporal availability. Considering the saturation and the limited bandwidth of the conventional systems used working at X-band (around 8.4 GHz), frequencies above Ku-band (12-18 GHz) are being used and currently explored for next future DS missions. For example, the ESA mission EUCLID, planned to be launched in 2020 to reach Sun-Earth Lagrange point L2, will use the K-band (at 25.5-27 GHz). The BepiColombo (BC) ESA mission to Mercury, planned to be launched in 2016, will use Ka-band (at 32-34 GHz) with some modules operating at X-band too. The W-band is also being investigated for space communications (Lucente et al., IEEE Systems J., 2008) as well as near-infrared band for DS links (Luini at al., 3rd IWOW, 2014; Cesarone et al., ICSOS, 2011). If compared with X-band channels, K-band and Ka-band can provide an appealing data rate and signal-to-noise ratio in free space due to the squared-frequency law increase of antenna directivity within the downlink budget (for the same physical antenna size). However, atmospheric path attenuation can be significant for higher frequencies since the major source of transmission outage is not only caused by convective rainfall, as it happens for lower frequencies too, but even non-precipitating clouds and moderate precipitation produced by stratiform rain events are detrimental. This means that accurate channel models are necessary for DS mission data link design at K and Ka band. A physical approach can offer advanced radiopropagation models to take into account the effects due to atmospheric gases, clouds and precipitation. The objective of this work is to couple a weather forecast numerical model with a microphysically- oriented radiopropagation model, providing a description of the atmospheric state and of its effects on a DS downlink. This work is developed in the framework of the RadioMeteorological Operations Planner (RMOP) program, aimed at performing a feasibility study for the BC mission (Biscarini et al., EuCAP 2014). The RMOP chain for the link budget computation is composed by three modules: weather forecast (WFM), radio propagation (RPM) and downlink budget (DBM). WFM is aimed at providing an atmospheric state vector. Among the available weather forecast models, for RMOP purposes we have used the Mesoscale Model 5. The output of the WFM is the input of the RPM for the computation of the atmospheric attenuation and sky-noise temperature at the receiving ground station antenna. RPM makes use of radiative transfer solver based on the Eddington approximations well as accurate scattering models. Time series of attenuation and sky-noise temperature coming from the RPM are converted into probability density functions and then ingested by the DBM to compute the received data volume (DV). Using the BC mission as a reference test case for the Ka-band ground station at Cebreros (Spain), this work will show the advantages of using a coupled WFM-RPM approach with respect to climatological statistics in a link budget optimization procedure. The signal degradation due to atmospheric effects in DS links in terms of received DV will be also investigated not only at Ka band, but also at X, K and W for intercomparison. The quality of the DS downlink will be given in terms of received DV and the results at different frequencies compared showing the respective advantages and drawbacks

Mesoscale high-resolution meteorological and radiative transfer models for satellite downlink budget design at millimeter-wave frequencies

Deep space (DS) missions for interplanetary explorations are aimed at acquiring information about the solar system and its composition. To achieve this result a radio link is established between the space satellite and receiving stations on the Earth. Significant channel capacity must be guaranteed to such spacecraft-to-Earth link considering their large separation distance as well. Terrestrial atmospheric impairments on the space-to-Earth propagating signals are the major responsible for the signal degradation thus reducing the link’s channel temporal availability. Considering the saturation and the limited bandwidth of the conventional systems used working at X-band (around 8.4 GHz), frequencies above Ku-band (12-18 GHz) are being used and currently explored for next future DS missions. For example, the ESA mission EUCLID, planned to be launched in 2020 to reach Sun-Earth Lagrange point L2, will use the K-band (at 25.5-27 GHz). The BepiColombo (BC) ESA mission to Mercury, planned to be launched in 2016, will use Ka-band (at 32-34 GHz) with some modules operating at X-band too. The W-band is also being investigated for space communications (Lucente et al., IEEE Systems J., 2008) as well as near-infrared band for DS links (Luini at al., 3rd IWOW, 2014; Cesarone et al., ICSOS, 2011). If compared with X-band channels, higher frequency bands can provide an appealing data rate and signal-to-noise ratio in free space due to the squared-frequency law increase of antenna directivity within the downlink budget (for the same physical antenna size). In particular, W-band (75–110 GHz) can be one valid alternative to K- and Ka-bands; theoretically, W-band should provide high channel capacities due to the large bandwidth availability and a more robust immunity to signal interference. However, atmospheric path attenuation can be significant for higher frequencies since the major source of transmission outage is not only caused by convective rainfall, as it happens for lower frequencies too, but even non-precipitating clouds and moderate precipitation produced by stratiform rain events are detrimental. This means that accurate channel models are necessary for DS mission data link design. A physical approach can offer advanced radiopropagation models to take into account the effects due to atmospheric gases, clouds and precipitation. The objective of this work is to couple a weather forecast numerical model with a microphysically-oriented radiopropagation model, providing a description of the atmospheric state and of its effects on a DS downlink. This work is the continuation of a study developed in the framework of the RadioMeteorological Operations Planner (RMOP) program, aimed at performing a feasibility study for the BC mission (Biscarini et al., EuCAP 2014). The RMOP chain for the link budget computation is composed by three modules: weather forecast (WFM), radio propagation (RPM) and downlink budget (DBM). WFM is aimed at providing an atmospheric state vector. Among the available weather forecast models, for RMOP purposes we have used the Mesoscale Model 5. The output of the WFM is the input of the RPM for the computation of the atmospheric attenuation and sky-noise temperature at the receiving ground station antenna. RPM makes use of radiative transfer solver, based on the Eddington approximations well as accurate scattering models. Time series of attenuation and sky-noise temperature coming from the RPM are converted into probability density functions and then ingested by the DBM to compute the received data volume (DV). RMOP project was originally aimed at investigating the Ka-band for DS mission focusing the attention on the advantages of using a coupled WFM- RPM approach with respect to climatological statistics in a link budget optimization procedure. In this work we extended the study to the W- and K- band. The signal degradation, due to atmospheric effects in DS links in terms of received DV, is investigated and a comparison among K-, Ka-, W- and the more commonly used X-band is carried out. The quality of the DS downlink will be given in terms of received DV and the results at different frequencies compared showing the respective advantages and drawbacks

Investigating Ka-band science data transfer for BepiColombo mission by using radiometeorological numerical models

Deep space (DS) exploration is aimed at acquiring information about the solar system and its composition, a purpose that can be achieved only if a significant communication capacity can be provided to spacecrafts at very large distances [1]. The Ka-band (at 32-34 GHz) and higher frequency band channels can provide this capacity if compared to the current X-band (around 8.4 GHz) [2]-[4]. Ka-band can offer a striking performance advantage over X-band because of the square-frequency law increase of directivity of the downlink beam for the same physical antenna size. This opens up a possible and useful trade space for Ka-band missions with the same antenna size (and spacecraft constraints) and radio frequency power, since a Ka-band mission can return four times more data than a comparable X–band mission. For the European Space Agency (ESA), the next step in this direction will be the utilisation of Ka-band downlinks both to generate radiometric observables (in combination with X-band uplink) as well as to increase science data transfer [5]. The first satellite mission adopting such frequency operationally will be BepiColombo (BC), the ESA cornerstone mission to Mercury (expected launch in 2015) including the Mercury Orbiter Radio Experiment (MORE) at X-Ka band [6]. The optimal allocation of channel resources above Ku band is limited by the significant impact of radio- meteorological factors which can irremediably degrade the quality of service for fairly high percentage of time [7]. At Ka band, for instance, attenuation due to cloudy and rainy troposphere can be even one order of magnitude larger than at X-band. The major cause of outages at Ka band and above is due to rainfall, as well as non-precipitating clouds. For small carrier-to-noise ratio (CNR), the impact of atmospheric noise temperature can become non-negligible [4]. In order to achieve the optimum data return at Ka-band, a different approach with respect to the link budget computation at lower frequencies (e.g., S or X band) is necessary [2]. Such link analysis is based on the maximization of the expected data return in a probabilistic framework rather than on a specified link statistical availability. Recent methods uses monthly statistics collected at the receiving site with the aim of defining average values of expected received data volume [5] and the exploitation of numerical weather forecasting is also foreseen [3]. This paper introduces the preliminary concept of the RadioMetOP (RadioMeteorological Operations Planner) technique and describes its main modelling components and objectives, limiting the analysis to rainfall effects. Numerical results in terms of received frame data for unconstrained and constrained system scenarios are also described together with a discussion about the possible impact of RadioMetOP methods on BC operations

Monitoring the last Apennine glacier: recent in situ campaigns and modelling of Calderone glacial apparatus

The Calderone glacier is at present the most southern glacier in Europe (42° 28' 15’’ N). The little apparatus (about 20.000 m2 in surface area) has been giving an interesting response both to short- and long-term climatic variations which resulted in a considerable reduction in surface area and volume. The glacial apparatus is split into two ice bodies (glacierets) since 2000. The two glacierets are located in a deep northward valley below the top of the Corno Grande (2912 m asl) in the centre of the Gran Sasso d’Italia mountain range (Central Italy). Such glacial apparatus has been subjected to a strong reduction, with a loss of total surface area of about 50% and thickness of about 65%with respect to the hypothetical size (about 105.00 m2 and 55 m at the Little Ice Age). Since early 90s the Calderone glacier has been subjected to several multidisciplinary field campaigns to monitor and evaluate its role as an environmental indicator in the framework of global warming. Starting from historical series related to more than a century of records, the variability of the different glacier properties has been estimated by using classical geomorphologic methods as well as in situ and remote sensing techniques. In particular, the last field campaigns, in 2015, 2016 and 2019, have been carried out using Ground Penetrating Radar equipped with different antenna frequencies, drone-based survey, snow pit measurements and chemical-physical sampling. The measurement campaigns have been complemented by a regional climate analysis, spanning the last fifty years, and snowpack modelling initialized with microphysical snow data (e.g., snow density, crystal shape and size, hardness). The snowpack chemical analyses include the main and trace elements, soluble inorganic and organic ions, EC/OC and PAH, with different spatial resolution depending on the analytes. We present here the methodological approach used and some preliminary results

Evaluation of high-frequency channels for deep-space data transmission using radiometeorological model forecast

The aim of this paper is to investigate the usability of high-frequency channels for deep-space (DS) transmissions exploiting radiometeorological forecast modeling. A previously developed model chain for DS link-budget optimization, based on numerical weather forecasts (WFs), is adopted. The latter, already tested at Ka-band, exploits the combination of a high-resolution mesoscale forecast model and a radiative transfer model to predict the atmospheric scenario and optimize received data volume (DV) during DS transmissions. To shift available Ka-band results to other frequencies, we apply frequency-scaling laws to extrapolate forecast path attenuation, link parameters, and maximum allowed bit-rate for data transmission. Exploiting the available WF-based methodology, we compute DV return for DS missions operating at X -, K -, Ka-, Q -, and W -bands in order to make a comparative study of the behavior of DS transmission-channels at these frequencies. Results show that, in terms of received DV, an innovative WF-based approach is more convenient than traditional methodologies and exhibits a trend similar to the benchmark (ideal case). Increasing link frequency, received DV increases up to Q -band. From Q - to W -band, despite received DV does not increase significantly, lost data remain under reasonable values, thus making the W -band suitable if coupled with a WF-based technique

REM sleep behavior disorder: mimics and variants

Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia with dream-enactment behaviors occurring during REM sleep and associated with the lack of the physiological REM sleep muscle atonia. It can be isolated and secondary to other neurological or medical conditions. Isolated RBD heralds in most cases a neurodegenerative condition due to an underlying synucleinopathy and consequently its recognition is crucial for prognostic implications. REM sleep without atonia on polysomnography is a mandatory diagnostic criterion. Different conditions may mimic RBD, the most frequent being obstructive sleep apnea during sleep, non-REM parasomnia, and sleep-related hypermotor epilepsy. These diseases might also be comorbid with RBD, challenging the evaluation of disease severity, the treatment choices and the response to treatment evaluation. Video-PSG is the gold standard for a correct diagnosis and will distinguish between different or comorbid sleep disorders. Careful history taking together with actigraphy may give important clues for the differential diagnosis. The extreme boundaries of RBD might also be seen in more severe and complex conditions like status dissociatus or in the sleep disorders' scenario of anti IgLON5 disease, but in the latter both clinical and neurophysiological features will differ. A step-by-step approach is suggested to guide the differential diagnosis

Insulin amyloid structures and their influence on neural cells

Peptide aggregation into oligomers and fibrillar architectures is a hallmark of severe neurodegenerative pathologies, diabetes mellitus or systemic amyloidoses. The polymorphism of amyloid forms and their distribution are both effectors that potentially modulate the disease, thus it is important to understand the molecular basis of protein amyloid disorders through the interaction of the different amyloid forms with neural cells and tissues. Here we explore the effect of amyloid fibrils on the human neuroblastoma (SH-SY5Y) cell line in vitro. We control the kinetic of fibrillization of insulin at low pH and higher temperature. We use a multiscale characterization via fluorescence microscopy and multimodal scanning probe microscopy to correlate the number of cells and their morphology, with the finer details of the insulin deposits. Our results show that insulin aggregates deposited on neuroblastoma cell cultures lead to a progressive modification and decreased number of cells that correlates with the degree of fibrillization. SPM unravels that the aggregates strongly interact with the cell membrane, forming a stiff encase that possibly leads to an increased cell membrane stiffness and deficit in the metabolic exchanges between the cells and their environment. The presence of fibrils does not affect the number of cells at 24 h whereas drop down to 60% is observed after 48 h of incubation

Neural cell alignment by patterning gradients of the extracellular matrix protein laminin

Anisotropic orientation and accurate positioning of neural cells is achieved by patterning stripes of the extracellular matrix protein laminin on the surface of polystyrene tissue culture dishes by micromoulding in capillaries (MIMICs). Laminin concentration decreases from the entrance of the channels in contact with the reservoir towards the end. Immunofluorescence analysis of laminin shows a decreasing gradient of concentration along the longitudinal direction of the stripes. The explanation is the superposition of diffusion and convection of the solute, the former dominating at length scales near the entrance (characteristic length around 50 μm), the latter further away (length scale in excess of 900 μm). These length scales are independent of the channel width explored from about 15 to 45 μm. Neural cells are randomly seeded and selectively adhere to the pattern, leaving the unpatterned areas depleted even upon 6 days of incubation. Cell alignment was assessed by the orientation of the long axis of the 4',6-diamidino-2-phenylindole-stained nuclei. Samples on patterned the laminin area exhibit a large orientational order parameter. As control, cells on the unpatterned laminin film exhibit no preferential orientation. This implies that the anisotropy of laminin stripes is an effective chemical stimulus for cell recruiting and alignment

EXPLOITING SUN-TRACKING MICROWAVE RADIOMETERS FOR TESTING RADIATIVE TRANSFER MODELS OF PRECIPITATING CLOUDS

The effects of the scattering troposphere on propagating signals are important for several microwave applications such as remote sensing and telecommunication. In particular, passive remote sensing exploits ground-based radiometers to retrieve profile information of the atmosphere. On the other hand, telecommunication applications (e.g., satellite communications) require an accurate estimation of the atmospheric effects to minimize the outage probability of the link. Within this context, atmospheric effects can be described through the joint knowledge of the radiopropagation parameters: atmospheric brightness temperature TB and total path attenuation At (also referred to as atmospheric extinction). These two quantities can be described by the radiative transfer theory that formalizes the spatial evolution of the atmospheric radiance and is implemented trough radiative transfer models (RTM). For successfully testing and validating RTM, measurements of both TB and At are needed. A typical approach to get these two quantities is to exploit combined measurements of satellite-beacon receivers (which provide measurements of At) and ground-based radiometers (which measures the TB). The disadvantage of this approach is that At and TB would be affected by different errors because they are derived using two distinct measuring instruments, each of them with different calibration and accuracy. Moreover, radiometers and beacon receivers typically work at different frequencies. This would imply that a frequency scaling approach would be required before using At and TB pairs for quantitative analysis. Actually, most of microwave radiometers are able to provide attenuation products as result of retrievals approaches based on forward models. However, such retrievals can suffer of large uncertainties in rainy conditions due to poor modeling of scattering. The only instruments able to provide simultaneous measurements of At and TB in all-weather conditions are ground based Sun-tracking radiometers (STR) that exploit the Sun as a stable radiance source. STR performs the retrieval of At exploiting two nearly simultaneous measurements of TB at the same elevation. This is accomplished by alternatively pointing the receiving antenna toward-the-Sun and off-the-Sun during the Sun tracking. The aim of this work is to exploit STR measurements to test and validate RTM simulations in cloudy and rainy conditions. We have considered two different models. First, a Sky Noise Eddington Model (SNEM): a 1D-model that gives an analytical approximation of the solution of the radiative transfer equation. SNEM simulations provide a synthetic clouds dataset through random generation of seasonal-dependent and time-decorrelated meteorological variables with statistics driven by radiosounding profiles. Second: a pseudo-3D radiative transfer model based on the Goddard Satellite Data Simulator Unit (G-SDSU, Matsui et al. JGR 2014) that is able to produce synthetic radiances and path attenuation as measured by ground-based microwave radiometers at several elevation angles and frequencies. In this work we use G-SDSU to convert 3D temporal profiles of meteorological variables, produced by Numerical Weather Forecasts, into predicted TB and At. RTMs are tested exploiting measurements from a STR installed at the Air Force Research Laboratory in Rome, NY, USA. The STR has four receiving channels at K (23.8 GHz), Ka (31.4 GHz), V (72.5 GHz) and W (82.5 GHz) band providing measurements for the years 2015-2016 at elevation angles varying between 20° and 70° (due to the antenna pointing-switching for the Sun tracking). The agreement between measurements and models highlights the reliability of the produced radiation database that can be exploited to develop and update parametric prediction models of attenuation. The use of RTM simulations driven by numerical weather forecasts paves the way to new approaches based on the prediction of radio-propagation parameters for specific target areas and temporal periods (as opposed to common prediction schemes based on stationary path attenuation models statistics)