Testing of Wideband Small Satellite Receivers in Complex Radio Frequency Environments Using Synthetic Spectrum Generation Techniques

As spacecraft technology improves, smaller cost-effective spacecraft become capable of increasingly sophisticated Earth observation missions, including wideband Radio Frequency (RF) sensing. Current methods available for validating the RF payloads on-board these missions, such as on-orbit payload validation using a pathfinder mission, are expensive, time consuming, and difficult. The challenge of modelling the RF environment of an orbital receiver is increased by path characteristics that become nontrivial at orbital velocities and distances, as well as unique modelling challenges such as ionospheric delay and multiple transmitters. A fast, inexpensive method for validating RF sensing payloads on the ground is presented in this paper. This method makes use of custom-made synthetic spectrum generation software, where the transmitter-receiver system is modelled in high fidelity and digital signal processing tools are used to simulate the RF environment at the orbital receiver. This modelling is performed using a set of modules to simulate factors affecting signals received by the spacecraft. Path loss, Doppler shift, and other channel-effect modules are used to create a realistic RF environment at the receiver. Representative networks of transmitters are simulated in this system, with nodes adhering to rules defined in network modules. Modules can be added to alter the overall transmitter network, receiver, and path models as required. To perform end-to-end payload testing, a Software Defined Radio transmitter generates representative RF spectrum, which is injected into the payload under test either over the air or via cable. Testing components along the RF chain is accomplished by modelling components up the chain, then injecting synthetic RF spectrum at the component of interest. The test system presented in this paper can also simulate the data output of Software Defined Radio payload receivers, such that data analysis methods and software processes can be validated without requiring access to physical payload components. End users of orbital RE spectrum can simulate scenarios to determine what data will be most useful to them, and modelling the RF stages up to the analog-to-digital converter ensures representative inputs for signal processing validation. The ability to accurately, quickly and cost-effectively test RF payloads at the component level or end-to-end makes this system a powerful tool for small satellite developers

Echinacea for Cut Flower Production in Utah

Echinacea, commonly known as coneflower, is an easy-to-grow, low-maintenance cut flower crop. As a perennial, plants can be expected to last up to 5 years in production before replacement is needed. Known for delicately arching petals and strong stems, echinacea comes in a wide range of colors that lend a wildflower look to floral design. Seed heads are also popular and can be harvested for their rust-orange cone shape

Reducing Food Waste at Home

As food is discarded, resources such as money and water are wasted by producing food that will not be eaten and then transporting it to landfills. There are many solutions for reducing food loss. This fact sheet reviews ways you can build successful habits to address food waste

Coping With Loneliness (Part 2): Look Outward

Experiencing loneliness sometimes is part of the human experience. However, when experienced long-term, loneliness can lead to detrimental impacts on physical, mental, and emotional health. In a series of four fact sheets, Utah State University (USU) Extension faculty compiled some of the most effective ways to enhance connectedness. This second fact sheet suggests simple ways of looking outward to experience greater connectedness. These include increasing social group memberships, connecting through art and laughter, spending time in nature, strengthening friendships, and providing service

Interpreting Neural Networks for Particle Tracing in Fluid Simulation Ensembles: An Interactive Visualization Framework

Understanding the internal mechanisms of neural networks, particularly Multi-Layer Perceptrons (MLP), is essential for their effective application in a variety of scientific domains. In particular, in the scientific visualization domain their adoption has recently shown to be a promising tool to predict particle trajectories in fluid dynamics simulation and aid the interactive visualization of flows. This research addresses the critical challenge of interpretability of such models. While interpretability has been extensively explored in fields like computer vision and natural language processing, its application to time series data, particularly for particle tracing (or prediction of trajectories), has not garnered sufficient attention. The overarching objective of this thesis is to augment the interpretability of MLP networks through interactive and comparative visualization of model ensembles. We aim to contribute to address the challenges associated with the ”black-box” nature of neural networks in this specific context. Our primary contribution lies in the development of a comprehensive visualization tool that integrates multiple linked views, including gradient visualization, particle trajectories, layer-wise activation, and weights visualization. This tool facilitates a more profound understanding of the intricate relationships between model components and model predictions. In particular, the proposed framework provides a user-friendly interface for comparing different models trained to predict particle trajectories in fluid dynamics simulation ensembles. This tool not only aids in understanding the MLP network behaviour, but also serves as a practical resource for researchers and practitioners wanting to analyze and use similar models. Finally, we test our framework using a variety of different 2D flows with different degrees of complexity. This helps understanding the effectiveness of the tool in providing insights about which components of the model affects a particular prediction and also what the network is learning at different training epochs

Optimizing Mobility on Demand Systems: Multiagent Reinforcement Learning Approaches to Order Assignment and Vehicle Guidance

This dissertation explores ways to improve Mobility on Demand (MoD) systems, which are services like ride-sharing and autonomous taxi systems. The main goal is to make these services more efficient and reliable, benefiting both passengers and drivers by better matching the number of available vehicles with the number of people needing rides. For ride-sharing services, a new method called T-Balance helps match riders with drivers and guides empty taxis to areas where more people need rides. This reduces wait times for passengers and increases earnings for drivers. Another method, called GRL-HM, looks at how riders and drivers behave to further improve the system’s efficiency and fairness. For autonomous taxi services, the dissertation introduces an advanced technique called Pr-DDQN to better plan routes for empty vehicles. This technique performs better than traditional methods, leading to higher customer satisfaction and shorter times for vehicles to get to passengers. A new framework is also proposed to improve how data is processed and how the system learns, making autonomous taxi services more efficient and scalable. Overall, this research develops smarter ways to manage rides and vehicles in MoD systems, helping create more sustainable and user-friendly urban transportation solutions

Characterizing a Chip Scale Atomic Clock in Low Earth Orbit

The University of Colorado Boulder has developed an experiment to characterize the behavior of a chip-scale atomic clock (CSAC) in space, conducted on the MAXWELL CubeSat mission. This experiment integrates a CSAC as an external oscillator to the onboard GPS receiver, enabling clock characterization through real-time estimates of clock bias, GPS pseudorange, and carrier phase measurements. These data will demonstrate the CSAC\u27s short and long-term stability and its sensitivity to the space environment. This paper evaluates the observation of CSAC performance using GPS within the constraints of the MAXWELL mission. The results, derived from tests with realistic orbit and spacecraft pointing scenarios modeled with an RF signal simulator and ground-based live-sky test data, show that poor GPS visibility limits CSAC observation accuracy and can result in data gaps. We demonstrate a gap-filling algorithm to effectively address these gaps. To mitigate the effects from poor visibility, GPS measurements from live-sky tests are processed with the GipsyX software suite to achieve the most accurate clock stability information. Since the MAXWELL receiver operates at a single frequency and is susceptible to ionospheric effects, we apply the Group and Phase Ionospheric Correction (GRAPHIC) technique to mitigate first-order ionospheric effects for GPS-based clock characterization in Low Earth Orbit (LEO)

Unscripted Journeys: An Exploration of Music Therapy Practitioner Perspectives on Improvisation Within and Beyond Clinical Application

Improvisation is a phenomenon used often in music settings, clinical settings, and in life in general. Within music therapy settings, clinical improvisation is one of the most common and useful skills music therapy practitioners use to help clients achieve their therapeutic goals. Proper acquisition and implementation of this skill is therefore crucial to the aspiring music therapist’s education. While many approaches to clinical improvisation are outlined within current literature, less literature exists regarding how the background and lifestyle of a music therapy practitioner may affect their development and implementation of clinical improvisation in session. Through qualitative data collection via seven interviews with current music therapy practitioners, information regarding the impact of practitioners’ personal, musical, and clinical background was gathered and analyzed to determine how and if said backgrounds influenced their development and usage of clinical improvisation. Through content and thematic analysis, this research concluded that those with more experience tended to gravitate toward spontaneity in general and clinical contexts, though the concept of spontaneity was valued by all. Accordingly, most pre-professionals tended to gravitate more toward the concept of structure. Additionally, it appeared that those with a more strict music background and education tended to gravitate more heavily toward structure in general and musical settings but not necessarily clinical settings. With these understandings, educators may gain a better understanding of how to help future music therapy students better develop clinical improvisation with the understanding that certain aspects of one’s background may affect their preference or aversion toward spontaneity

Variable Drought Impacts on Stream Habitat Across the Northwestern United States

The Western United States has been in an extended drought since 2002 which can drive negative impacts on stream habitats supporting native fish and aquatic species. Stream quality, specifically in the context of fish habitat, depends on many variables, including vegetation quality. Drought conditions affect vegetation conditions; however it is unclear how drought conditions impact stream habitat quality for fish. This study examines how stream habitat quality relates to drought across the National Forests of the Northwestern US, as well as exploring whether drought increases have had a significant impact on riparian vegetation over the past 20 years. Using a long-term stream habitat monitoring dataset from the PacFish/InFish Biological Opinion Monitoring Program and satellite-imagery derived Normalized Differential Vegetation Index (NDVI) data, we are able to examine the long term trends in greeness, and the relationship between riparian vegetation condition and stream habitat quality. I found no linear trend of drought impacting riparian vegetation conditions from 2000-2020 in Idaho, Montana, or Oregon National Forests. Linear regression analyses revealed positive relationships between NDVI and stream habitat quality in many, but not all years. Only one National Forest, Beaverhead-Deerlodge in Montana, had an entirely significant relationship with increasing drought causing a decrease in habitat quality. All other National Forests showed some overlap with zero. Riparian vegetation has thus far not been negatively impacted by drought, and stream habitat is largely positively related to riparian vegetation conditions. Further analysis of this data with a greater area of combined NDVI values, as well as the use of more specific NDVI data could provide greater insights into drought patterns across the Northwestern United States, as well as the effect of potential drought on streams or watersheds as a whole