By 2050, food consumption and agricultural water use will increase as a result of a global population that is projected to reach 9 billion people. To address this food and water security challenge, there has been increased attention towards the concept of sustainable agriculture, which has a broad aim of securing food and water resources while preserving the environment for future generations. An element of this is the use of precision agriculture, which is designed to provide the right inputs, at the right time and in the right place. In order to optimize nutrient application, water intakes, and the profitability of agricultural areas, it is necessary to improve our understating and predictability of agricultural systems at high spatio-temporal scales. The underlying goal of the research presented herein is to advance the monitoring of croplands and crop yield through high-resolution satellite data. In addressing this, we explore the utility of daily CubeSat imagery to produce the highest spatial resolution (3 m) estimates of leaf area index and crop water use ever retrieved from space, providing an enhanced capacity to provide new insights into precision agriculture. The novel insights on crop health and conditions derived from CubeSat data are combined with the predictive ability of crop models, with the aim of improving crop yield predictions. To explore the latter, a sensitivity analysis-linked Bayesian inference framework was developed, offering a tool for calibrating crop models while simultaneously quantifying the uncertainty in input parameters. The effect of integrating higher spatio-temporal resolution data in crop models was tested by developing an approach that assimilates CubeSat imagery into a crop model for early season yield prediction at the within-field scale. In addition to satellite data, the utility of even higher spatial resolution products from unmanned aerial vehicles was also examined in the last section of the thesis, where future research avenues are outlined. Here, an assessment of crop height is presented, which is linked to field biomass through the use of structure from motion techniques. These results offer further insights into small-scale field variabilities from an on-demand basis, and represent the cutting-edge of precision agricultural advances.

With the evolution of spacecraft systems, we see the growing need for smaller, more affordable, and robust spacecrafts that can be jettisoned with ease and sent to sites to perform a myriad of operations that a larger craft would prohibit, or that can be quickly manipulated from performing one task into another. The developing requirements have led to the creation of Nano-Satellites, or CubeSats. The question then remains, how to navigate the expanse of space with such a minute spacecraft? A solution to this is using the stars themselves as a means of navigation. This can be accomplished by measuring the distance between stars in a camera image and determining the stars' identities. Once identified, the spacecraft can obtain its position and facing. A series of star identification algorithms called Lost in Space Algorithms (LISAs) are used to recognize the stars in an image and assess the accuracy and error associated with each algorithm. This is done by creating various images from a simulated camera, using a program called MATLAB, along with images of actual stars with uncompensated errors. It is shown how suitable these algorithms are for use in space navigation, what constraints and impediments each have, and if low quality cameras using these algorithms can solve the Lost in Space problem.

The single bus voltage distributed architecture is the mainstay architecture for small satellite spacecraft. Even large satellites follow this architecture. While they may have more than one voltage that is distributed, such as a high voltage bus and a low voltage bus, within a subsystem, there is usually one bus voltage. Each subsystem component is responsible for further regulation or point-of-load regulation. The Nano-satellite class, and more particularly the cubesat, have broken away from this norm and overwhelmingly implement a centralized architecture. With the advances of small, highly efficient monolithic dc-dc converters, this thesis researches the possibilities of implementing the distributed architecture at the cubesat scale. The Goal is to create a very efficient electrical power system design that has a high degree of utility, allowing it to be used for multiple missions, without having to redesign the system every time.

Low-earth orbit (LEO) contains plasma which can impact satellite charging and radio frequency (RF) communications. Quantifying both the composition and movement of ions in LEO can improve efficiency of the forecasting models that predict the impact plasma will have on satellite communications and accuracy of global positioning satellite measurements. Two instruments known as the Retarding Potential Analyzer (RPA) and the Ion Drift Meter (IDM) have been used in tandem to measure ionospheric properties including ion temperature, velocity, and density. These instruments are costly and occupy large areas on a spacecraft. In recent years, space mission budgets have diminished. This change has driven innovation towards creating new instruments which are compatible with smaller and cheaper satellites yet still yield measurements of comparable quality. This thesis presents the design of a new instrument that encompasses the functionality of both the RPA and IDM, known as the Plasma Velocity Vector Instrument for Small Satellites (PVVISS). PVVISS has compact form factor and low power requirements, making it a viable option for smaller, low cost nano-satellite sized missions. Missions utilizing the PVVISS sensor will allow increased exploration of the ionospheric impact on satellite communications.

Variations of gas and plasma density and composition in Earth’s thermosphere and ionosphere are key indicators of interactions between different layers of Earth’s atmosphere. The nature of interactions between neutral and ion species in the upper atmosphere is an active area of study in Heliophysics and there is much to learn about the dynamic relationship between the ionosphere and neutral thermosphere. Mass Spectrometers are among an array of instruments used to explore Earth’s upper atmosphere and other space environments. In the past, data from mass spectrometers flown in low earth orbit has been used to improve atmospheric models and to study the dynamics of the ionosphere and thermosphere. Historically, these instruments are substantial in size and deployed on larger satellite platforms. Data from these larger instruments generally provide information from a specific point in time at a single location. Studies of atmospheric density and composition with multiple locations for each time point could be performed by CubeSat swarms if proper instrumentation were available to fit CubeSat payload restrictions. The proposed miniaturized time-of-flight (TOF) mass spectrometer (MS) will have a mass resolution and range sufficient for measuring the composition of Earth’s thermosphere and ionosphere while operating within the power and space constraints of a CubeSat. The capabilities of this instrument could dramatically reduce the cost of future missions while simultaneously enhancing the science return. The design employs miniaturization of TOF-MS technology, including resolution refinement techniques used for larger instruments and standard concepts for TOF-MS components such as acceleration grids, a Bradbury-Nielsen wire gate, a gridless ion mirror, and microchannel plate detector.

Small satellites, and CubeSats in particular, have quickly become a hot topic in the aerospace industry. Attitude determination is currently one of the most intense areas of development for these miniaturized systems and future Cal Poly satellite missions will depend heavily on magnetometers. In order to utilize magnetometers as a viable source of attitude knowledge, precise calibration is required to ensure the greatest accuracy achievable. This paper outlines a procedure for calibrating and testing magnetometers on the next generation of Cal Poly CubeSates, utilizing a Helmholtz cage to simulate any desired orbital magnetic field that would be experienced by a spacecraft around Earth, as well as investigation of magnetic interference as a result of on-board electrical activity.

A relatively new picosatellite standard, CubeSats have traditionally been used for simple educational missions. As CubeSats become more complex and utilize more complex sensors such as imagers, they gain enhanced credibility as satellite platforms. Imaging systems on CubeSats have the potential to be used for a variety of uses, such as earth and weather monitoring, attitude determination, and remote sensing. However the size and power limitations of CubeSats pose an interesting challenge to the design of a capable, robust imaging system. This thesis outlines the objectives and requirements of CP-3’s imaging system, and describes the development process and methods. Test results from the imaging system are included, as well as lessons learned gleaned from CP-3’s on-orbit operations. This document can serve as a guideline for other teams wishing to develop imaging systems. While other developers may have different requirements or constraints, this roadmap illustrates each of the many considerations that must be taken into account when designing an imaging system.

Cal Poly’s PolySat CubeSat satellites have begun to conduct more complex and scientifically significant experiments. The large data products generated by these missions demonstrate the necessity for higher data rate communication than currently provided by the PolySat UHF radio. This thesis leverages the proliferation of consumer wireless monolithic transceivers to develop a 250kbps to 2000kbps, 2W CubeSat radio operating within the 2.45GHz Industrial, Scientific, and Medical (ISM) radio band. Estimating a link budget for a realistic CubeSat leads to the conclusion that this system will require a large deployable CubeSat antenna, large earth station satellite dish, and a fine-pointing attitude control system. Noise floor measurements of a CubeSat ground station demonstrate that terrestrial ISM interference can be minimized to below the thermal noise floor by carefully choosing the operating frequency. The radio is specifically designed as a daughter board for the PolySat System Board with a direct interface to the embedded Linux microprocessor. A state-of-the-art ZigBee transceiver evaluation board is measured to confirm its suitability for a CubeSat radio. A schematic is developed, which integrates the transceiver, power amplifier, low noise amplifier, amplifier protection circuitry, switching regulators, and RF power measurement into a single printed circuit board assembly (PCBA). The circuitry is then squeezed into a high-density, 1.4” x 3.3” layout. The PCBA is then manufactured, troubleshot, tuned, and characterized.

With the rising popularity of small satellites, such as CubeSats, many smaller institutions previously incapable of developing and deploying a spacecraft have starting to do so. Institutions with a history of space flight, such as NASA JPL, have begun to put projects on CubeSats that would normally fly on much larger satellites. As a result, the institutions with space flight heritage have begun to port spacecraft software that was previously designed for much larger and more complex satellites to the CubeSat platform. Unfortunately for universities, who are the majority of all institutions devel- oping CubeSats, these ported systems are too large and complex to be a practical control solution. Student teams have a high turnover rate due to graduation and when a student becomes an expert on the control system, they graduate; most students get a maximum of two or three years of experience before graduating. This thesis proposes the Generic Decision Making Framework for Autonomous Systems (GDMFAS) as an accessible, easily extensible, component-based executive system architecture. The architecture is designed for Linux distributions, including the custom Linux distribution used by PolySat, and is implemented using C++. The proposed framework provides much of the same functionality as systems designed for larger satellites in a smaller, more straightforward pack- age, which includes both scheduling and executive components. This thesis also provides validation for the prototype implementation and evaluates the system according to six metrics. The metric analysis for this work is then compared with the metric analyses of previous works.

This thesis will focus on the performance of angles only initial orbit determi- nation (IOD) methods on observational data of low Earth orbit (LEO) CubeSats. Using data obtained by Lockheed Martin’s Space Object Tracking (SpOT) facil- ity, four methods: Gauss, Double-R, Gooding and Assumed Circular, will use different amounts of orbital arc to determine which methods perform the best in the short arc regime of less than 10 degrees of orbital arc. Once the best method for estimating the orbit is determined, there will be analysis on whether these IOD methods are accurate enough to predict a secondary observation session. Finally non-linear regression will be performed to determine if the error metrics follow a predictable trend based on how much orbital arc is seen by the observer. It was determined that above a certain amount of orbital arc, angles only IOD methods can reliably predict a secondary observation session to facilitate more observations. Below 4 degrees of orbital arc, which is around 60 seconds of ob- serving time for LEO objects, none of the methods were able to reliably predict a secondary observation session. The Assumed Circular method was the best method for observing LEO CubeSats because it forces the IOD solution to be circular, which limits the error in the shape of the orbit as the amount of orbital arc decreases. Finally, many metrics follow an exponential trend when compared to the orbital arc. Thus, the amount of orbital arc seen is a strong predictor for the accuracy of the angles only IOD solutions.