All Sky Survey Mission Observing Scenario Strategy

This paper develops a general observing strategy for missions performing all-sky surveys, where a single spacecraft maps the celestial sphere subject to realistic constraints. The strategy is flexible such that targeted observations and variable coverage requirements can be achieved. This paper focuses on missions operating in Low Earth Orbit, where the thermal and stray-light constraints due to the Sun, Earth, and Moon result in interacting and dynamic constraints. The approach is applicable to broader mission classes, such as those that operate in different orbits or that survey the Earth. First, the instrument and spacecraft configuration is optimized to enable visibility of the targeted observations throughout the year. Second, a constraint-based high-level strategy is presented for scheduling throughout the year subject to a simplified subset of the constraints. Third, a heuristic-based scheduling algorithm is developed to assign the all-sky observations over short planning horizons. The constraint-based approach guarantees solution feasibility. The approach is applied to the proposed SPHEREx mission, which includes coverage of the North and South Celestial Poles, Galactic plane, and a uniform coverage all-sky survey, and the ability to achieve science requirements demonstrated and visualized. Visualizations demonstrate the how the all-sky survey achieves its objectives

Modeling and Optimizing Space Networks for Improved Communication Capacity.

There are a growing number of individual and constellation small-satellite missions seeking to download large quantities of science, observation, and surveillance data. The existing ground station infrastructure to support these missions constrains the potential data throughput because the stations are low-cost, are not always available because they are independently owned and operated, and their ability to collect data is often inefficient. The constraints of the small satellite form factor (e.g. mass, size, power) coupled with the ground network limitations lead to significant operational and communication scheduling challenges. Faced with these challenges, our goal is to maximize capacity, defined as the amount of data that is successfully downloaded from space to ground communication nodes. In this thesis, we develop models, tools, and optimization algorithms for spacecraft and ground network operations. First, we develop an analytical modeling framework and a high-fidelity simulation environment that capture the interaction of on-board satellite energy and data dynamics, ground stations, and the external space environment. Second, we perform capacity-based assessments to identify excess and deficient resources for comparison to mission-specific requirements. Third, we formulate and solve communication scheduling problems that maximize communication capacity for a satellite downloading to a network of globally and functionally heterogeneous ground stations. Numeric examples demonstrate the applicability of the models and tools to assess and optimize real-world existing and upcoming small satellite mission scenarios that communicate to global ground station networks as well as generic communication scheduling problem instances. We study properties of optimal satellite communication schedules and sensitivity of communication capacity to various deterministic and stochastic satellite vehicle and network parameters. The models, tools, and optimization techniques we develop lay the ground work for our larger goals: optimal satellite vehicle design and autonomous real-time operational scheduling of heterogeneous satellite missions and ground station networks.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/97912/1/saracs_1.pd

Design and Implementation of the GPS Subsystem for the Radio Aurora Explorer

Abstract This paper presents the design and implementation of the Global Positioning System (GPS) subsystem for the Radio Aurora eXplorer (RAX) CubeSat. The GPS subsystem provides accurate temporal and spatial information necessary to satisfy the science objectives of the RAX mission. There are many challenges in the successful design and implementation of a GPS subsystem for a CubeSat-based mission, including power, size, mass, and financial constraints. This paper presents an approach for selecting and testing the individual and integrated GPS subsystem components, including the receiver, antenna, low noise amplifier, and supporting circuitry. The procedures to numerically evaluate the GPS link budget and test the subsystem components at various stages of system integration are described. Performance results for simulated tests in the terrestrial and orbital environments are provided, including start-up times, carrier-to-noise ratios, and orbital position accuracy. Preliminary on-orbit GPS results from the RAX-1 and RAX-2 spacecraft are presented to validate the design process and pre-flight simulations. Overall, this paper provides a systematic approach to aid future satellite designers in implementing and verifying GPS subsystems for resourceconstrained small satellites

Characterization of Entry to Solar System Atmospheres for Chip-Sized Spacecraft

No abstract availabl

Model Based Systems Engineering (MBSE) Applied to Radio Aurora Explorer (RAX) CubeSat Mission Operational Scenarios

Abstract—Small spacecraft are more highly resource-constrained by mass, power, volume, delivery timelines, and financial cost relative to their larger counterparts. Small spacecraft are operationally challenging because subsystem functions are coupled and constrained by the limited available commodities (e.g. data, energy, and access times to ground resources). Furthermore, additional operational complexities arise because small spacecraft components are physically integrated, which may yield thermal or radio frequency interference. In this paper, we extend our initial Model Based Systems Engineering (MBSE) framework developed for a small spacecraft mission by demonstrating the ability to model different behaviors and scenarios. We integrate several simulation tools to execute SysML-based behavior models, including subsystem functions and interna

Jet Propulsion

in modeling and systems engineering. MBSE uses Systems Modeling Language (SysML) as its modeling language. SysML is a domain-specific modeling language for systems engineering used to specify, analyze, design, optimize, and verify systems