Engineering topics
Publications and source records attributed to Heatwole, Scott.
Disussion of the work being done for the suborbital programs at Wallops Flight Facility on star tracker technology. Mainly the development and flight of a low cost system that uses commerical off the shelf products. The rough design is explained along with a presentation of some flight results from recent flights.
On April 18 2017, NASA Goddard Space Flight Center's IceCube 3U CubeSat was launched by an ATLAS V rocket from Cape Canaveral Air Force Station on board a Cygnus resupply spacecraft, as part of NASA's CubeSat Launch Initiative. Onboard IceCube was an 883 GHz radiometer tuned to detecting ice content in clouds, marking the first time such frequency was used from low-Earth orbit. IceCube successfully demonstrated retrieval of ice water path, generating the first ever global cloud ice map at 883 GHz. Its success provides valuable lessons on how to approach a severely resource-limited space mission and provides great insight into how this experience can be applied to future high-risk, "non-class" missions for NASA and others. IceCube marks the first official NASA Earth Science CubeSat technology demonstration mission. The spacecraft was completed in about 2.5 years starting April 2014 through launch provider delivery in December of 2016. The mission was jointly funded by NASA's Earth Science Technology Office, after competitive selection, and by NASA's Earth Science Directorate. IceCube began its technology demonstration mission in June 2017, providing a pathway to advancing the understanding of ice clouds and their role in climate models; quite a tall order for a tiny spacecraft.
The Wallops Star Tracker system provides a means of attitude knowledge during balloon missions based on stars detected in the systems field of view. It was developed as an attitude reference source for the Wallops Arc-Second Pointer (WASP) system, but can be utilized as a stand-alone system to support other requirements. The system, known as the Celestial Attitude Reference and Determination System (CARDS), will be described, and the results of the CARDS test flights and the current development status will be presented.
A new miniature fine Sun sensor has been developed that uses a quadrant photodiode and housing to determine the Sun vector. Its size, mass, and power make it especially suited to small satellite applications, especially nanosatellites. Its accuracy is on the order of one arcminute, and it will enable new science in the area of nanosatellites. The motivation for this innovation was the need for high-performance Sun sensors in the nanosatellite category. The design idea comes out of the LISS (Lockheed Intermediate Sun Sensor) used by the sounding rocket program on their solar pointing ACS (Attitude Control System). This system uses photodiodes and a wall between them. The shadow cast by the Sun is used to determine the Sun angle. The new sensor takes this concept and miniaturizes it. A cruciform shaped housing and a surface-mount quadrant photodiode package allow for a two-axis fine Sun sensor to be packaged into a space approx.1.25xl x0.25 in. (approx.3.2x2.5x0.6 cm). The circuitry to read the photodiodes is a simple trans-impedance operational amplifier. This is much less complex than current small Sun sensors for nanosatellites that rely on photo-arrays and processing of images to determine the Sun center. The simplicity of the circuit allows for a low power draw as well. The sensor consists of housing with a cruciform machined in it. The cruciform walls are 0.5-mm thick and the center of the cruciform is situated over the center of the quadrant photodiode sensor. This allows for shadows to be cast on each of the four photodiodes based on the angle of the Sun. A simple operational amplifier circuit is used to read the output of the photodiodes as a voltage. The voltage output of each photodiode is summed based on rows and columns, and then the values of both rows or both columns are differenced and divided by the sum of the voltages for all four photodiodes. The value of both difference over sums for the rows and columns is compared to a table or a polynomial fit (depending on processor power and accuracy requirements) to determine the angle of the Sun in the sensor frame.
Three documents discuss the Sustainable Objective Valuation and Attainability (SOVA) algorithm and software as used to plan tasks (principally, scientific observations and associated maneuvers) for the Far Ultraviolet Spectroscopic Explorer (FUSE) satellite. SOVA is a means of managing risk in a complex system, based on a concept of computing the expected return value of a candidate ordered set of tasks as a product of pre-assigned task values and assessments of attainability made against qualitatively defined strategic objectives. For the FUSE mission, SOVA autonomously assembles a week-long schedule of target observations and associated maneuvers so as to maximize the expected scientific return value while keeping the satellite stable, managing the angular momentum of spacecraft attitude- control reaction wheels, and striving for other strategic objectives. A six-degree-of-freedom model of the spacecraft is used in simulating the tasks, and the attainability of a task is calculated at each step by use of strategic objectives as defined by use of fuzzy inference systems. SOVA utilizes a variant of a graph-search algorithm known as the A* search algorithm to assemble the tasks into a week-long target schedule, using the expected scientific return value to guide the search.
The feasibility and benefits of various spacecraft servicing concepts are currently being assessed, and all require that the servicer spacecraft perform rendezvous, proximity, and capture operations with the target spacecraft to be serviced. Many high-value spacecraft, which would be logical targets for servicing from an economic point of view, are located in geosynchronous orbit, a regime in which autonomous rendezvous and capture operations are not commonplace. Furthermore, existing GEO spacecraft were not designed to be serviced. Most do not have cooperative relative navigation sensors or docking features, and some servicing applications, such as de-orbiting of a non-functional spacecraft, entail rendezvous and capture with a spacecraft that may be non-functional or un-controlled. Several of these challenges have been explored via the design of a notional mission in which a nonfunctional satellite in geosynchronous orbit is captured by a servicer spacecraft and boosted into super-synchronous orbit for safe disposal. A strategy for autonomous rendezvous, proximity operations, and capture is developed, and the Orbit Determination Toolbox (ODTBX) is used to perform a relative navigation simulation to assess the feasibility of performing the rendezvous using a combination of angles-only and range measurements. Additionally, a method for designing efficient orbital rendezvous sequences for multiple target spacecraft is utilized to examine the capabilities of a servicer spacecraft to service multiple targets during the course of a single mission.
The Autonomous Flight Safety System (AFSS) aims to replace the human element of range safety operations, as well as reduce reliance on expensive, downrange assets for launches of expendable launch vehicles (ELVs). The system consists of multiple navigation sensors and flight computers that provide a highly reliable platform. It is designed to ensure that single-event failures in a flight computer or sensor will not bring down the whole system. The flight computer uses a rules-based structure derived from range safety requirements to make decisions whether or not to destroy the rocket.
The SOVA algorithm was originally developed under the Resilient Systems and Operations Project of the Engineering for Complex Systems Program from NASA s Aerospace Technology Enterprise as a conceptual framework to support real-time autonomous system mission and contingency management. The algorithm and its software implementation were formulated for generic application to autonomous flight vehicle systems, and its efficacy was demonstrated by simulation within the problem domain of Unmanned Aerial Vehicle autonomous flight management. The approach itself is based upon the precept that autonomous decision making for a very complex system can be made tractable by distillation of the system state to a manageable set of strategic objectives (e.g. maintain power margin, maintain mission timeline, and et cetera), which if attended to, will result in a favorable outcome. From any given starting point, the attainability of the end-states resulting from a set of candidate decisions is assessed by propagating a system model forward in time while qualitatively mapping simulated states into margins on strategic objectives using fuzzy inference systems. The expected return value of each candidate decision is evaluated as the product of the assigned value of the end-state with the assessed attainability of the end-state. The candidate decision yielding the highest expected return value is selected for implementation; thus, the approach provides a software framework for intelligent autonomous risk management. The name adopted for the technique incorporates its essential elements: Strategic Objective Valuation and Attainability (SOVA). Maximum value of the approach is realized for systems where human intervention is unavailable in the timeframe within which critical control decisions must be made. The Far Ultraviolet Spectroscopic Explorer (FUSE) satellite, launched in 1999, has been collecting science data for eight years.[1] At its beginning of life, FUSE had six gyros in two IRUs and four reaction wheels. Over time through various failures, the satellite has been left with one reaction wheel on the vehicle skew axis and two gyros. To remain operational, a control scheme has been implemented using the magnetic torque rods and the remaining momentum wheel.[2] As a consequence, there are attitude regions where there is insufficient torque authority to overcome environmental disturbances (e.g. gravity gradient torques). The situation is further complicated by the fact that these attitude regions shift inertially with time as the spacecraft moves through earth s magnetic field during the course of its orbit. Under these conditions, the burden of planning targets and target-to-target slew maneuvers has increased significantly since the beginning of the mission.[3] Individual targets must be selected so that the magnetic field remains roughly aligned with the skew wheel axis to provide enough control authority to the other two orthogonal axes. If the field moves too far away from the skew axis, the lack of control authority allows environmental torques to pull the satellite away from the target and can potentially cause it to tumble. Slew maneuver planning must factor the stability of targets at the beginning and end, and the torque authority at all points along the slew. Due to the time varying magnetic field geometry relative to any two inertial targets, small modifications in slew maneuver timing can make large differences in the achievability of a maneuver.