Engineering topics
Publications and source records attributed to Sedlak, Joseph.
The MMS spacecraft are highly instrumented (accelerometers, star cameras, Sun sensors, science experiments for plasmas etc.). This presentation will discuss how data from these systems has allowed two micrometeoroid/orbital debris events to be studied: the Feb. 2, 2016 impact with an MMS4 shunt resistor, and the June 12, 2016 impact with an MMS4 wire boom.
Extensive flight data is being collected throughout the MMS mission that includes quantities that are of interest for attitude dynamics studies such as spin rate, spin axis orientation nutation rate, etc. One example of such data is the long-term evolution of the spin rates of the four spacecraft. Spikes in these rates are observed that are separated by the MMS orbital period (just under 24 hr) and occur around perigee due to gravity-gradient torque. Periodic discontinuities in spin rate are caused by the controller resetting the spin rate approximately to the nominal 3.1 RPM value at the time of each maneuver. In between, a slow decay in spin rate can be seen to occur. The paper will discuss various disturbance torque mechanisms that could potentially be responsible for this behavior: these include magnetic hysteresis, eddy currents, solar radiation pressure, and a possible interaction between gravity-gradient and wire boom flexibility effects. One additional disturbance mechanism is produced by the Active Spacecraft Potential Control (ASPOC) devices: these emit positive indium ions to keep the MMS spacecraft electrically neutral, so as not to corrupt the electric field observations that are made by some of the on-board instruments. The spin rate decays that could be produced by these various mechanisms will be quantified in the paper, and their signatures described. Comparing these with the observations from flight data then allow the most likely candidate to be determined.
This paper presents an iterative method for three-axis magnetometer (TAM) calibration that makes use of three existing utilities recently incorporated into the attitude ground support system used at NASA's Goddard Space Flight Center. The method combines attitude-independent and attitude-dependent calibration algorithms with a new spinning spacecraft Kalman filter to solve for biases, scale factors, nonorthogonal corrections to the alignment, and the orthogonal sensor alignment. The method is particularly well-suited to spin-stabilized spacecraft, but may also be useful for three-axis stabilized missions given sufficient data to provide observability.
An algorithm has been developed that converts penetration angles reported by Static Earth Sensors (SESs) into Earth observation vectors. This algorithm allows compensation for variation in the horizon height including that caused by Earth oblateness. It also allows pitch and roll to be computed using any number (greater than 1) of simultaneous sensor penetration angles simplifying processing during periods of Sun and Moon interference. The algorithm computes body frame unit vectors through each SES cluster. It also computes GCI vectors from the spacecraft to the position on the Earth's limb where each cluster detects the Earth's limb. These body frame vectors are used as sensor observation vectors and the GCI vectors are used as reference vectors in an attitude solution. The attitude, with the unobservable yaw discarded, is iteratively refined to provide the Earth observation vector solution.
This paper describes ongoing work a NASA/Goddard Space Flight Center to improve the quality of spacecraft attitude sensor calibration and reduce costs by automating parts of the calibration process. The new calibration software can autonomously preview data quality over a given time span, select a subset of the data for processing, perform the requested calibration, and output a report. This level of automation is currently being implemented for two specific applications: inertial reference unit (IRU) calibration and sensor alignment calibration. The IRU calibration utility makes use of a sequential version of the Davenport algorithm. This utility has been successfully tested with simulated and actual flight data. The alignment calibration is still in the early testing stage. Both utilities will be incorporated into the institutional attitude ground support system.
Analysis of attitude sensor data from the Aqua mission showed small but systematic differences between batch least-squares and extended Kalman filter attitudes. These differences were also found to be correlated with star tracker residuals, gyro bias estimates, and star tracker baseplate temperatures. This paper describes the analysis that shows that these correlations are all consistent with a single cause: time-dependent thermal deformation of star tracker alignments. These varying alignments can be separated into relative and common components. The relative misalignments can be determined and compensated for. The common misalignments can only be determined in special cases.
With a view towards reducing cost and complexity for spacecraft early mission support at the NASA Goddard Space Flight Center (GSFC), efforts are being made to automate the attitude sensor calibration process. This paper addresses one of the major components needed by such a system. The beneficiaries of an improved calibration process are missions that demand moderate to high precision attitude knowledge or that need to perform accurate attitude slews. Improved slew accuracy reduces the time needed for re-acquisition of fine-pointing after each attitude maneuver, Rapid target acquisition can be very important for astronomical targeting or for off-nadir surface feature targeting by Earth-oriented spacecraft. The normal sequence of on-orbit calibration starts with alignment calibration of the star trackers and possibly the Sun sensor. Their relative alignment needs to be determined using a sufficiently large data set so their fields of view are adequately sampled. Next, the inertial reference unit (IRU) is calibrated for corrections to its alignment and scale factors. The IRU biases are estimated continuously by the onboard attitude control system, but the IRU alignment and scale factors are usually determined on the ground using a batch-processing method on a data set that includes several slews sufficient to give full observability of all the IRU calibration parameters. Finally, magnetometer biases, alignment, and its coupling to the magnetic torquers are determined in order io improve momentum management and occasionally for use in the attitude determination system. The detailed approach used for automating calibrations will depend on whether the automated system resides on the ground or on the spacecraft with an ultimate goal of autonomous calibration. Current efforts focus on a ground-based system driving subsystems that could run either on the ground or onboard. The distinction is that onboard calibration should process the data sequentially rather than in a single large batch since onboard computer data storage is limited. Very good batch- processing calibration utilities have been developed and used extensively at NASA/GSFC for mission support but no sequential calibration utilities are available. To meet this need, this paper presents the mathematical description of a sequential IRU calibration system. The system has been tested using flight data from the Rossi X-ray Timing Explorer (RXTE) during a series of attitude slews. The paper also discusses the current state of the overall automated system and describes plans for adding sequential alignment calibration and other additions that will reduce the amount of analyst time and input.
This work presents results from the study of a large volume of spacecraft flight data pertaining to gyroscope performance. We have examined long and short term trends of gyroscope biase of first, an exact solution for the time-dependence of the attitude part of the state error covariance, averaged over the three spacecraft axes, is given. This solution is more complete than the usual cubic polynomial for the variance in that it includes coupling among the three gyroscope axes and includes an important term arising from the initial correlations. Second, several continuous 24-hour spans of gyroscope data are examined to verify the short-term statistical model. This analysis demonstrates that in-flight data can be used to determine the strength of the white noise driving the random walk of the gyroscope bias. This may be useful for postlaunch improvement to the noise model and for diagnosing the health of the gyroscope. Third, the long-term trends in gyroscope biases show a nearly linear systematic variation over time scales of years. This has been found on three different missions. While the random walk model is adequate as a basis for onboard Kalman filters or for state estimation using relatively short time spans, these trends indicate that some applications could benefit by accounting for the secular changes in the biases. One example is a new gyroscope calibration method that is under development that allows for multi-epoch bias solutions.
In order to maneuver satellites accurately from one attitude to another, onboard rate sensing gyroscopes usually must be calibrated after launch. Several algorithms have been used to determine gyro biases, misalignments, and scale factors. This paper describes algorithms that have been used in the past, discusses their advantages and limitations, and describes a new algorithm and the gyro calibration results obtained using this new algorithm. The new algorithm has significant operational advantages in addition to being at least as accurate as other algorithms.
Spacecraft attitude estimation by means of an extended Kalman filter requires a reasonably true model of the inherent noise of each sensor. For some sensors, the largest uncorrected noise comes not from the sensor itself, but from errors in the model for the predicted observations. This is certainly the case for Earth horizon sensors. The Earth horizon as seen from low Earth orbit is nearly a circle whose radius depends primarily on altitude. A straightforward latitude-dependent correction is added to this to account for the oblateness of the Earth. There also are both seasonal and stochastic variations in the horizon height. The seasonal variations can be predicted to some limited degree based on models de(ived from historical data. The stochastic component characteristically shows variations that are correlated both in time and space but which are unpredictable over long time spans. This work investigates whether Earth horizon sensor performance can be improved by solving for its systematic error as an augmentation of an attitude Kalman filter. It is found that using only Earth and Sun sensors, the augmented state is not fully observable. Even when magnetometer data is included, only the pitch axis component of the error can be improved; the roll component is unobservable.
A major limitation on the use of infrared horizon sensors for attitude determination is the variability of the height of the infrared Earth horizon. This variation includes a climatological component and a stochastic component of approximately equal importance. The climatological component shows regular variation with season and latitude. Models based on historical measurements have been used to compensate for these systematic changes. The stochastic component is analogous to tropospheric weather. It can cause extreme, localized changes that for a period of days, overwhelm the climatological variation. An algorithm has been developed to compensate partially for the climatological variation of horizon height and at least to mitigate the stochastic variation. This method uses attitude and horizon sensor data from spacecraft to update a horizon height history as a function of latitude. For spacecraft that depend on horizon sensors for their attitudes (such as the Total Ozone Mapping Spectrometer-Earth Probe-TOMS-EP) a batch least squares attitude determination system is used. It is assumed that minimizing the average sensor residual throughout a full orbit of data results in attitudes that are nearly independent of local horizon height variations. The method depends on the additional assumption that the mean horizon height over all latitudes is approximately independent of season. Using these assumptions, the method yields the latitude dependent portion of local horizon height variations. This paper describes the algorithm used to generate an empirical horizon height. Ideally, an international horizon height database could be established that would rapidly merge data from various spacecraft to provide timely corrections that could be used by all.
Analysis of flight data from previous missions indicates that anomalous Sun sensor readings could be caused by Earth albedo interference. A previous Sun sensor study presented a detailed mathematical model of this effect. The model can be used to study the effect of both diffusive and specular reflections and to improve Sun angle determination based on perturbed Sun sensor measurements, satellite position, and an approximate knowledge of attitude. The model predicts that diffuse reflected light can cause errors of up to 10 degrees in Coarse Sun Sensor (CSS) measurements and 5 to 10 arc sec in Fine Sun Sensor (FSS) measurements, depending on spacecraft orbit and attitude. The accuracy of these sensors is affected as long as part of the illuminated Earth surface is present in the sensor field of view. Digital Sun Sensors (DSS) respond in a different manner to the Earth albedo interference. Most of the time DSS measurements are not affected, but for brief periods of time the Earth albedo can cause errors which are a multiple of the sensor least significant bit and may exceed one degree. This paper compares model predictions with Tropical Rainfall Measuring Mission (TRMM) CSS measurements in order to validate and refine the model. Methods of reducing and mitigating the impact of Earth albedo are discussed. ne CSS sensor errors are roughly proportional to the Earth albedo coefficient. Photocells that are sensitive only to ultraviolet emissions would reduce the effective Earth albedo by up to a thousand times, virtually eliminating all errors caused by Earth albedo interference.
There are a number of approaches one can take to modeling the dynamics of a flexible body. While one can attempt to capture the full dynamical behavior subject to disturbances from actuators and environmental torques, such a detailed description often is unnecessary. Simplification is possible either by limiting the amplitude of motion to permit linearization of the dynamics equations or by restricting the types of allowed motion. In this work, we study the nonlinear dynamics of bending deformations of wire booms on spinning spacecraft. The theory allows for large amplitude excursions from equilibrium while enforcing constraints on the dynamics to prohibit those modes that are physically less relevant or are expected to damp out fast. These constraints explicitly remove the acoustic modes (i.e., longitudinal sound waves and shear waves) while allowing for arbitrary bending and twisting, motions which typically are of lower frequency. As a test case, a spin axis reorientation maneuver by the Polar Plasma Laboratory (POLAR) spacecraft has been simulated. POLAR was chosen as a representative spacecraft because it has flexible wire antennas that extend to a length of 65 meters. Bending deformations in these antennas could be quite large and have a significant effect on the attitude dynamics of the spacecraft body. Summary results from the simulation are presented along, with a comparison with POLAR flight data.