Media propagation noises are amongst the main error sources of radiometric observables for deep space missions, with fluctuations of the tropospheric excess path length representing a relevant contributor to the Doppler noise budget. Microwave radiometers currently represent the most accurate instruments for the estimation of the tropospheric delay and delay rate along a slant direction. A prototype of a tropospheric delay calibration system (TDCS), using a 14 channel Ka/V band microwave radiometer, has been developed under a European Space Agency contract and installed at the deep space ground station in Malargüe, Argentina, in February 2019. After its commissioning, the TDCS has been involved in an extensive testbed campaign by recording a total of 44 tracking passes of the Gaia spacecraft, which were used to perform an orbit determination analysis. This work presents the first statistical characterization of the end-to-end performance of the TDCS prototype in an operational scenario. The results show that using TDCS-based calibrations instead of the standard GNSS-based calibrations leads to a significant reduction of the residual Doppler noise and instability.
Radio environment map (REM) is an efficient enabler for practical cognitive radio networks by sensing the electromagnetic information within regions of interest dynamically. Most of works on Kriging-based method have proven that separate estimation for pathloss and shadowing can obtain more accurate REM construction. But these methods have some shortcomings that prior information is required for construction or disability for multiple transmitters scenario. In order to overcome the problems of urban REM construction mentioned above, this paper propose a residual Kriging algorithm based on generalized regression neural network (GRNN-RK) for that. The performance of proposed algorithm has been evaluated by the analysis of simulation results, and experiments show that GRNN is capable of improving Kriging in accuracy. Additionally, the influence of spread on REM construction is also experimented.
The Demonstration and Science Experiments (DSX) mission operated in medium Earth orbit from 25 June 2019 until 31 May 2021. During this time it conducted experiments that actively injected very low frequency waves into the inner magnetosphere to study wave generation, wave propagation, and wave-particle interactions. Experiment planning used cold plasma ray tracing to predict conjunctions for space-to-space transmissions, and the same technique supports post-mission analysis of both monostatic and bistatic signal receptions. Modifications for warm plasma may also be required for extremely oblique waves. In addition, evaluations of amplitude thresholds for triggered emissions provide bounds on DSX signal amplitudes useful for constraining the antenna performance. This report describes both of these analytical tools in the context of mission planning and data analysis. Ongoing analysis using these techniques will be reported in future publications.
This study aims to present the morphology of GPS L-band scintillations at the equatorial anomaly station Bahir Dar (11030’N, 37030’E) using GPS-SCINDA data in the descending high solar activity period between January 2014 to December 2014. In studying low-latitude scintillation, we have used millions of data recorded every minute of one year by 32 GPS satellite and it is found that intense scintillation occurred during the day time with a small frequency and very frequent occurrences of relatively moderate scintillation during the night time. In the period of observation, the variation of scintillations with local time and season are analyzed and it is found that occurrence of scintillation is minimum in summer months and maximum in equinox months with highest values observed in the months of March and September. Pre-midnight and post-midnight occurrence of scintillation is also studied and Pre-midnight scintillation was found to be maximum in equinox whereas it is minimum in winter months. Generally, it is found that most of scintillations are weak (s4<0.1) and intense scintillations with s4>0.3 are rare.
By difference treatment of the rate of change of the radial distance, the interchange relationship between the Doppler shift and the path difference is obtained, so that the Doppler shift can be used to obtain the path difference in an equivalent way. On this basis, by using the linear solution of the double-base linear array and constructing a virtual double-base array, a Doppler direction finding method using only the single-base array is obtained. Because the transformation method based on frequency shift and path difference avoids the direct comparison of phase, and the equivalence of transformation is mainly related to the accuracy of frequency shift measurement, the new method is likely to lay a theoretical foundation for the application of Doppler direction finding method in higher frequency bands.
In this paper, THz channel propagation characterization and modeling for a desktop environment is presented. Path loss and PDPs measured on the motherboard in both free-space and desktop resemble metal cavity are compared. To characterize the large scale fading of the channel, mean path loss model as a function of antenna height is proposed by treating the motherboard desktop environment as a partially dielectric filled resonant cavity. Good match between the measured and modeled path loss proves the model validity. For the shadowing across the frequency, Gamma-mixture model is applied to characterize the oscillations of in-cavity measured path loss. Results show that with proper choice of the number of mixed Gamma distributions $k$, the goodness of fit between the model and the probability density function (PDF) of path loss oscillations can reach more than 97\%. Multipath components are characterized by cluster-based channel modeling. Modifications were made on the conventional S-V model to accurately characterize the channel by rewriting the cluster power decay with step-wise functions and each sub-function is expressed exponentially in dB, and the ray power decay with power law approach. A good agreement can be observed between the model and the measurements.
We investigate the Spectral Kurtosis (SK) statistical signature of a signal observed with the Robert C. Byrd Green Bank Telescope Breakthrough Listen back-end that was transmitted by the Voyager 1 spacecraft, which is up to date the only known artificial signal originating from outside our solar system, and we demonstrate the ability of the SK estimator to perform real-time detection and discrimination against natural astronomical transients of deep-space Voyager 1-like technological signatures of alien origin. We use the same approach to investigate the yet controversial nature of the FRB 180301 signal detected during the Breakthrough Listen observations with the Parkes telescope.
A radio transmitter which is accelerating with a non-zero radial component with respect to a receiver will produce a signal that appears to change in frequency over time. This effect, commonly produced in astrophysical situations where orbital and rotational motions are ubiquitous, is called a drift rate. In radio SETI (Search for Extraterrestrial Intelligence) research, it is unknown a priori which frequency a signal is being sent at, or even if there will be any drift rate at all besides motions in the solar system. Therefore a range of potential drift rates need to be individually searched, and a maximum drift rate needs to be chosen. The middle of this range is zero, indicating no acceleration, but the absolute value for the limits remains unconstrained. A balance must be struck between computational time and the possibility of excluding a signal from ETI. In this work, we examine physical considerations that constrain a maximum drift rate and highlight the importance of this problem in any narrowband SETI search. We determine that a normalized drift rate of 200 nHz (e.g. 200 Hz/s at 1 GHz) is a generous, physically motivated guideline for the maximum drift rate that should be applied to future narrowband SETI projects if computational capabilities permit.
We study the properties of dust in disks to constrain models of planet formation. We measure and analyze the spectral index for the dust continuum emission at millimeter wavelengths for a sample of 24 young disks in the Upper Sco star-forming region. We do this by combining data taken with the ALMA telescope at wavelengths of 2.87 mm and 0.88 mm. Since the age of this region is ∼ 5 - 10 Myr, these results can constrain the properties of small solids in disks at the end of their lifetime. We examine whether dust trapping, which is key to the formation of planetesimals, happens only in much younger disks or if it is efficient all the way towards the end of the disk life cycle. Our results indicate that dust traps are present also in the relatively old disks in our sample, indicating that protoplanetary disks have the potential to form planetesimals during their entire lifetime. Our analysis also quantifies the effects of scattering by dust of the disk emission, a mechanism that has been recently proposed as potentially important to determine the fluxes of protoplanetary disks even at sub-mm/mm wavelengths. From preliminary results, based on the state-of-the-art radiative transfer code RADMC-3d, we infer that scattering is not effective for optically thin disk models, but could potentially play a significant role for optically thick models.
Millisecond Pulsars (MSPs) are likely to be or to become a timing, navigation, and metadata communication standard across the galaxy. Regarding timing, they provide a parallel clock to terrestrial ones, are based on macroscopic neutron stars behavior instead of quantum processes, and they will remain ticking longer than any clock we can construct on Earth. Regarding navigation, X-ray MSPs provide all the necessary ingredients for a Pulsar Positioning System that has many similarities with GPS. In astronautics, X-ray pulsar-based navigation (XNAV) uses a time-of-arrival navigation method comparable to GPS, accurate down to about 100 meters. Regarding metadata communication, MSPs would be a natural metadata coding choice for any galactic communication effort. On Earth, any letter or email contains metadata information about where it comes from, where it goes, and when it was written. We can expect that similar conventions exist for any potential galactic communication. Most messages are likely to be galacto-tagged and pulsar-time-stamped by reference to MSPs. This simple remark opens a simplified SETI search. Given any suspicious message we want to decode, the first step becomes to attempt to decode not the message itself, but its metadata (Vidal 2017). GPS is a technological breakthrough that enables many others: one needs only to think about all the location-based services (LBS) that it has unlocked in our modern societies. The realm of potential galactic LBS is an area totally unexplored, and may well be a key to find technosignatures of many kinds. Is GPS a technology? The answer is an obvious yes. Now imagine that we would find around an exoplanet’s orbit well-distributed timekeeping devices with an accuracy comparable with atomic clocks, beaming timing information that can be used as a positioning system, just like GPS. Would not we be compelled to check if it is a technosignature? This is exactly the current situation with MSPs, but on a galactic scale. This is why I have proposed ways to test whether the pulsar positioning system is actually an instance of galactic engineering (Vidal 2019). Seeking such a galactic technosignature proof is actually searching for a distributed signal, instead of searching for a localized signal around one particular star or planet. If the search program succeeds, it would lead to the discovery of extraterrestrial intelligence, through their engineered timing and navigation system. References: Vidal, C. 2017. “Millisecond Pulsars as Standards: Timing, Positioning and Communication.” Proceedings of the International Astronomical Union 13 (S337): 418–19. doi:10.1017/S1743921317008596. https://arxiv.org/abs/1711.06036. (where this poster was first presented) Vidal, C. 2019. “Pulsar Positioning System: A Quest for Evidence of Extraterrestrial Engineering.” International Journal of Astrobiology 18 (3): 213–34. doi:10.1017/S147355041700043X. https://arxiv.org/abs/1704.03316.
Ka-band (32 GHz) communications links utilized by the National Aeronautics and Space Administration (NASA) flight missions for science downlink are susceptible to degradation due to weather. In this study, a customized real-time forecast system has been developed to predict zenith atmospheric noise temperature (Tatm) at the Deep Space Network (DSN) tracking sites using machine learning (ML). A random forest model is trained with the Global Forecast System (GFS) forecast and analysis datasets in addition to the Tatm measurements derived from on-site advanced water vapor radiometers (AWVR). The real-time forecast uncertainty is quantified for different error regimes using the Self-Organizing Map method. The results show that the Root Mean Square Error (RMSE) of the 24-hour Tatm prediction at Goldstone, CA increases with the increase of Tatm. Ninety percent of the forecasts have RMSE (bias) of less than 3.50 K (0.22 K) for fair-weather conditions with Tatm < 17 K. In comparison to the current approach in designing Ka-band communications links, application of weather forecasts can increase data return to the downlink for 80% of the time. A downlink gain of up to 1.61 dB (45% more data) can be realized at 20 elevation angle when Tatm = 9 K.
Pure metallic reflectarray antennas have good power efficiency and low fabrication cost, which were limited to single band operation. A dual-band reflectarray antenna is developed for two directional beams by two feeds. The reflecting elements are metal waveguides, and have novel properties of both resonant and non-resonant modes at the two frequency bands. The low and high frequency bands can be easily separated by the cutoff frequency of waveguide modes. The phase changing mechanisms via ray optics and fundamental waveguide modes, respectively provide simple formulations for elemental structure design of directional beams. Radiation characteristics of the linear and circular polarizations are cross-examined with good performance by full-wave simulations using HFSS, FEKO and CST at 28 and 60 GHz bands for 5G front-haul network applications.
Infrared spectra of evolved stars have a rise in signal between the 7.0 μm and 8.0 μm wavelengths; the antisymmetric Si−O stretches of small silicon oxide clusters fall in this range and have large intensities. Hence, this quantum chemical analysis provides data for such molecules that may be of significance for astrochemical classification and could play a role in the formation or degradation of mineral nanocrystals from or into their constituent atoms. Both explicitly computed anharmonic fundamental vibrational frequencies and those determined from scaled harmonic frequencies agree well with known experimental data, and spectroscopic constants are provided herein such that astronomical rotational spectral characterization may also be possible for the C2v SiO3 and Si2O3 molecules.
Using the magnetic field observed by Galileo during two flybys of Callisto, Khurana et al. (1998) demonstrated that Callisto generates a strong induction response to the time-varying primary field, indicative of the presence of a subsurface ocean. In contrast, Hartkorn and Saur (2017) modeled the atmosphere and ionosphere of Callisto and suggested that the ionosphere could be responsible for a significant part of the observed magnetic fields. Thus, they concluded that the water ocean might be located much deeper than previously thought or might not exist at all. While Khurana et al. (1998) did not account for the induction within a conductive ionosphere, Hartkorn and Saur (2017) overestimated the conductivity of the ionosphere by using Cowling conductivity which is not applicable for the situation at Callisto. In this paper, we re-analyzed the S-band open-loop one-way Doppler data of the Galileo spacecraft with the aim to derive the electron density (ED) and neutral density (ND) profiles of Callisto and address its implication in terms of moon’s conductivities and interiors. Using modern orbit determination software, MONTE, and the most up-to-date information on the Jovian system, we reconstructed the Galileo orbit with a full dynamical approach. The estimated rms values of the Doppler residuals for baseline measurement vary from 0.01-0.08 Hz, well within the expected noises of the radio signals. We used these residuals to derive the ED profiles using the technique discussed in Verma et al., (2019). We found an appreciable ionosphere for C22 and C23 Ingress occultations with peak densities of 15600±900 cm-3 and 17700±600 cm-3, respectively. For other cases, the detections do not exceed the 3-σ level. While the general features of the EDs are consistent with Kliore et al. (2002), our estimated 1-σ formal uncertainties are 2-3 times better presumably because of the constrained Galileo’s orbit. Assuming O2 as the major component of the Callisto’s atmosphere, the estimated ND (weighted mean) at the surface is 2.0±0.33 x10-10 cm-3 which corresponds to a column density of 3.9±0.35 x10-16 cm-2 (see Figure). Finally, we will use these density profiles to constrain the ionospheric conductivities and address their implications in terms of the presence of a subsurface ocean.
The importance of measurement and modelling of the coronal magnetic fields has been appreciated for a long time, and in view of the fact that magnetic fields of Coronal Mass Ejections (CMEs) play a crucial role in determining their geo-effectiveness, this also has considerable societal impact. The coronal magnetic fields are, however, very hard to measure directly. Unlike those at play in X-ray, EUV and optical regimes, radio emission mechanisms are sensitive to the local magnetic fields and hence can potentially lead to their measurements. In practise, however, this potential has been hard to realize. To the best of our knowledge, in the past eighteen years, there have been only three published instances of radio detection of CME like structures. Only for two of these instances, it was possible to estimate coronal magnetic fields by fitting the measured spectra with gyrosynchrotron models. Using data from the Murchison Widefield Array (MWA), for two CMEs we have detected radio structures resembling the CME morphology. These structures are cospatial and cotemporal with the white light coronagraph images of the CME and we can convincingly demonstrate that this is not plasma emission. The maximum heliocentric distance where we can detect such emission is 4.74 solar radii, and the flux densities we measure are among the lowest reported. We note that these detections have been enabled by the confluence of the availability of data from the modern arrays like the MWA; and an automated interferometric solar radio imaging which we have developed. The MWA provides unprecedentedly dense sampling of Fourier (uv) plane, an essential pre-requisite for high imaging fidelity; and the imaging pipeline is tuned to extract the best imaging performance from these data. We present the hypothesis that gyrosynchrotron emission from CMEs intrinsically is not rare, it only appeared so because the dynamic range and imaging fidelity of available solar radio images was typically insufficient to convincingly detect this emission. If true, this then provides an exciting opportunity for routine estimation of the CME magnetic fields at coronal heights and a host of other coronal diagnostics, uniquely associated with gyrosynchrotron emissions.
The observations from the Juno spacecraft in polar orbit of Jupiter provide for the first time a complete view of Jupiter’s radio emissions from all latitudes. Characterizing the latitudinal distribution of radio emissions’ occurrence and intensity is a useful step for elucidating their origin. Here we analyze for that purpose the first 3 years of observations from the Waves experiment on the Juno spacecraft (mid-2016 to mid-2019). Two prerequisites for the construction of the latitudinal distribution of intensities for each Jovian radio component are (i) to work with absolute flux densities, and (ii) to be able to associate each radio measurement with a specific radio component. Accordingly, we develop a method to convert the Juno/Waves data in flux densities and then we build a catalog of all Jovian radio components over the first 3 years of Juno’s orbital mission. From these, we derive occurrence and intensity distributions versus observer’s latitude and frequency for each component; these will be the basis for future detailed studies and interpretations of each component’s characteristics and origin.
Real-time forecasting of anomalies in the Ionosphere TEC is attempted using machine learning models such as Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM). The Performances of both models were demonstrated on three Earthquakes (EQs), i.e. Mw 6.8, 2020 Indonesia, Mw 8.0, 2019 Peru and Mw 7.8, 2015 Nepal EQs. In this study, GNSS-derived TEC values from the CODE server have been utilized and the statistical boundary limits have been defined with 95% confidence level for anomaly detection in daily TEC variations. The training and test TEC dataset was divided into 8:2 ratio. After the data processing the hyper model parameters were optimized for the training dataset following which the TEC anomalies were validated by comparing the forecasted and actual TEC values on the test dataset. For ARIMA analysis, we start with the ADF test to check for stationarity of TEC data and after observing the test-statistics critical values and p-value we reject the null hypothesis. On calculating the ACF and PACF plots we select model parameters values in accordance with the lowest AIC value. While, for the LSTM model, we start with standardizing the training data to have zero mean and unit variance. The model is fit using the ‘Adam’ version of stochastic gradient descent, optimized using the ‘mse’ loss-function and run through 250 epochs using the rectified linear activation-function (ReLU) for better performance. Both the models were successfully able to detect and predict significant evidence for pre-seismic ionospheric TEC anomalies on 01 May 2020, 20 May 2019 and 11 April 2015 respectively before the occurrences of Indonesia, Peru and Nepal EQs. The time series analysis of forecasted TEC data revealed that the RMSE and MAPE error on the anomalous day was found to be significantly higher than the preceding non-anomalous day error and the overall forecasted error. Both ARIMA and LSTM models performed well for Indonesia and Peru EQs, forecasting TEC anomalies accurately within the 5-6 day window before the EQ, but the LSTM model outshined the former in long term TEC forecasting for the Nepal EQ performing well in the 11 day window before the EQ. Overall, the LSTM model was found to be more precise especially in long term forecasting and was also able to detect the weaker TEC anomalies which went unnoticed in the ARIMA model.