The AERO and VISTA CubeSat missions were designed to perform LF/HF radio interferometry from Low Earth Orbit (LEO) using Electromagnetic Vector Sensors (EMVSs) to investigate high-latitude aurora. An EMVS, in contrast to a traditional antenna, measures not only the magnitude but also the direction and polarization of incident radio waves, providing critical data for understanding space-based radio frequency interference and natural phenomena. This work extends ground-based radio science by exploring the feasibility of utilizing Ham Science Citizen Investigation (HamSCI)’s global network of citizen science stations to supplement and validate space-based observations. Ray tracing models like PHaRLAP are used to simulate high-frequency (HF) propagation from terrestrial transmitters to a potential LEO satellite orbit. This work presents an exhaustive search of seasonal ionospheric conditions, modeled by the International Reference Ionosphere (IRI)-2020, which has identified specific times when low-frequency HF signals (below 5 MHz) are most likely to penetrate the D-layer and reach LEO altitudes. This prediction is crucial for mission planning and signal acquisition. A key finding from this research is a method for cross-verifying ground-to-space and ground-to-ground links. Specifically, an event on April 7, 2024,  was identified where a ray path, from the KC4USV transmitter in Antarctica to the HamSCI receiver (W2NAF) in Pennsylvania, has a point of commonality with a ray path that would propagate from KC4USV to a LEO satellite. This coincidental propagation path is intended to validate the modeled HF absorption by comparing the received signal strength at the W2NAF ground station to the expected signal strength at the AERO-VISTA satellite’s EMVS. Ongoing work includes expanding this analysis to other high-latitude transmitters, such as CHU in Canada, to broaden this study of polar HF propagation. For future system enhancements, the utilization of GNU Radio modules is proposed, specificallygr-leoan open-source channel simulator of the Earth-Satellite system operation, developed by the Libre Space Foundation with European Space Agency funding, to explore the possible failures that may occur in space channel telecommunication, and gr-satnogs for real-world satellite data reception via the SatNOGS global network of ground stations. This would enable the development of Software Defined Radio (SDR) techniques to improve data fidelity and link budgets.Acknowledgements Sincere gratitude is extended to Dr. Nathaniel A. Frissell (W2NAF), lead of the Ham Radio Science Citizen Investigation (HamSCI); Dr. Kuldeep Pandey, and Dr. Gareth Perry, Assistant Professor, Department of Physics, Center for Solar-Terrestrial Research, New Jersey Institute of Technology; Mr. Gary Mikitin (AF8A), Radio Operators Expert; and Mr. Bill Liles (NQ6Z), HamSCI Community Diversity Recruitment Chair; and special thanks to the HamSCI Community, led by The University of Scranton, Department of Physics and Engineering W3USR, in collaboration with Case Western Reserve University W8EDU; the University of Alabama; the New Jersey Institute of Technology, Center for Solar Terrestrial Physics K2MFF; the MIT Haystack Observatory; TAPR; Amateur Radio Digital Communications (ARDC); additional collaborating universities and institutions; and volunteer members of the amateur radio and citizen science communities.

Enhancing the reliability-accuracy tradeoff for Global Navigation Satellite System (GNSS) applications is exponentially important, especially in dealing with the negative effects caused by ionospheric disturbances. This research seeks to put hands-on betterment of GNSS Radio Occultation (GNSS-RO), which is suggested by improving the prediction of the ionospheric Vertical Total Electron Content (VTEC) worst-case scenarios. On the other hand, it is aspired to align with the recent data assimilation and satellite remote sensing approaches. This work focuses on optimizing ionospheric VTEC using the NeQuickG model, driven by Galileo satellite coefficients. NeQuickG, a global ionospheric model that is developed by both the International Center for Theoretical Physics (ICTP) and the University of Graz, provides better spatial and temporal resolution. This work applies Particle Swarm Optimization (PSO) to identify the latitude, longitude, and time of day at which VTEC peaks, which represents the worst-case scenarios for GNSS performance, and hence, addresses such impacts of high VTEC values. This proposed approach utilizes the most available Galileo coefficients from NASA's Archive of Space Geodesy Data (CDDIS), dating back to both 2019 and 2017. As a yield, the proposed optimization process pinpoints the geographical grid that has the highest VTEC values at latitude \(-9.8^o\) and longitude \(-8.8^o\). Compared to other randomly picked grids, the proposed optimization shows an absolute maximum VTEC at all altitudes. Interestingly, the simulated VTEC peak, at Earth altitude of \(300\) kms, shows an order-of-magnitude convergence with that VTEC at a Mars radial distance of \(3500\) kms, which motivates a further planetary and terrestrial comparative analysis approach. Furthermore, the optimized simulated peak VTEC converges with that reported using the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellite data, amid geomagnetic storms in the Mid-Atlantic Ocean, near Saint Helena, Ascension and Tristan da Cunha. In summary, this research put hands-on combining the bio-inspired optimization algorithms with the mathematical parameter-based (Galileo) ionospheric model as NeQuickG. Consequently, in order to improve GNSS-RO data assimilation and signal integrity, more precise forecasting of spatial and temporal VTEC maxima may be possible with the NeQuickG-driven PSO optimization as described in this work. It is hoped that this operational insight can be useful for supporting these immune, space-based navigation and weather services, as well as for furtherly developing atmospheric sounding based on nanosatellites and CubeSats. Further, it is hugely aspired to even beat a harmony with the larger endeavors that enhance GNSS reliability under the dynamic ionospheric variability nature, which in turn resonates with the atmospheric and space weather research community.AcknowledgmentsSpecial thanks to Prof. Nathaniel A. Frissell (W2NAF) - the Ham Radio Science Citizen Investigation (HamSCI) lead; Mr. Gary Mikitin (AF8A) - Radio Operators Expert; and Mr. Bill Liles (NQ6Z) - HamSCI Community (Diversity Recruitment Chair), in collaboration with the University of Scranton. Special thanks for the financial support of the U.S. National Science Foundation Grant AGS-2404997 and Amateur Radio Digital Communications (ARDC). Special thanks to my Dream NASA Space Apps team: Marcin Leśniowski, Dr. Pasumarthi Babu Sree Harsha, Matt Downs, Daniel Metcalfé, and Sıla Kardelen Karabulut.

Ground-based navigation systems are indispensable in modern multidisciplinary applications, ranging from emergency response to precision agriculture. The integration of space weather data with these systems not only improves their accuracy and reliability but also aligns perfectly with the transition from theoretical models to operational services. This research explores the implementation of navigation location estimation using data from the Weak Signal Propagation Reporter Network (WSPRnet). The WSPRnet database, part of the Ham Radio Science Citizen Investigation (HamSCI), offers extensive spatial coverage through voluntarily provided data. This dataset includes key parameters such as transmitter-receiver operation timestamps, frequency bands, grid locations, separating distances, callsigns, transmitter Signal-to-Noise Ratio (SNR), drift, power, and receiver azimuth and mode. By utilizing the robust IntlWSPR transmitting beacon structure, which features approximately 40 active beacons globally distributed and continuously operating, we obtain a resilient, real-time dataset. These beacons transmit very low noise-buried signals around 23 dBm, allowing for reliable non-interfering location estimation functionality. We evaluate the performance of our localization system by generating a test dataset through ideal calculations using the free space path loss propagation model. Our findings indicate that the HamSCI-based localization system achieves an acceptable error margin, with a worst-case scenario error of just 10 meters per grid. Future work will involve the application of Artificial Neural Networks (ANNs) to incorporate additional ionospheric parameters, enhancing the precision of received power measurements for user location grids.Acknowledgements: Special thanks to the Ham Radio Science Citizen Investigation (HamSCI), Mr. Gary Mikitin (AF8A), Radio Operators Expert, and Mr. Bill Liles (NQ6Z), HamSCI Community Diversity Recruitment Chair, and Case Western Reserve University, in collaboration with the University of Scranton, for their invaluable contributions. Special thanks for the financial support of the U.S. National Science Foundation Grant AGS-2404997 and Amateur Radio Digital Communications (ARDC).

Accurate weather prediction and understanding of space weather phenomena are critical for safeguarding society and infrastructure against the impacts of severe atmospheric events. Doppler radar systems serve as essential tools for terrestrial weather forecasting and space weather monitoring, providing crucial insights into precipitation, wind patterns, and ionospheric disturbances. This study focuses on advancements in local oscillator design tailored for Doppler radar applications, with implications for both terrestrial weather forecasting and space weather monitoring. Leveraging the UMC65 process technology with a supply voltage of 1.4 V, our design targets an oscillation frequency of 13 GHz to capture detailed atmospheric dynamics and ionospheric disturbances. Critical to the design is the control of phase noise, with stringent specifications of less than -100 dBc/Hz at a frequency offset of 1 MHz. This ensures minimal signal distortion and high sensitivity in detecting Doppler shifts and ionospheric irregularities. Additionally, power efficiency and signal integrity are prioritized, aiming for a peak differential output swing of more than 1 V and a maximum current consumption of less than 5 mA. These design considerations are essential for sustainable operation in remote or mobile radar installations, crucial for both terrestrial and space weather monitoring applications. Furthermore, the design incorporates multi-finger transistor configurations, optimizing current-carrying capacity and stability while adapting to varying environmental conditions. By pushing the boundaries of local oscillator performance, our research contributes to advancing the capabilities of Doppler radar technology in understanding atmospheric dynamics and monitoring space weather phenomena. In summary, the design approach to local oscillator design bridges the gap between terrestrial weather forecasting and space weather monitoring, facilitating more accurate predictions and enhancing our understanding of atmospheric and ionospheric processes. AcknowledgementSpecial thanks to the Center of Nanoelectronics and Devices (CND), The American University in Cairo, under the supervision of Prof. Yehea Ismail, for granting the Nanodegree in Analog RF and IC Design by providing the necessary labs and tools to conduct this research.