Search NASA⌕ Search

Engineering topics

Pawloski, James H.

Publications and source records attributed to Pawloski, James H..

6 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Global Precipitation Measurement (GPM) Core Satellite & International Space Station (ISS) Coordination for CubeSat Deployments to Minimize Collision Risk

The Global Precipitation Measurement Mission (GPM) is a joint U.S. and Japan mission to observe global precipitation, extending the Tropical Rainfall Measuring Mission (TRMM) data set, which was launched by H-IIA from Tanegashima in Japan on February 28TH, 2014 directly into its 407km operational orbit. The International Space Station (ISS) is an international human research facility operated jointly by Russia and the USA from NASA's Johnson Space Center (JSC) in Houston Texas. Mission priorities lowered the operating altitude of ISS from 415km to 400km in early 2015, effectively placing both vehicles into the same orbital regime. The ISS has begun a program of deployments of cost effective CubeSats from the ISS that allow testing and validation of new technologies. With a major NASA asset flying at the same effective altitude as the ISS, CubeSat deployments became a serious threat to GPM and therefore a significant indirect threat to the ISS. This presentation describes the specific problem of collision threat to GPM and risk to ISS CubeSat deployment, the process that was implemented to keep both missions safe from collision and maximize their project goals, and the history of the process since implementation.

GPM↗
NASA NTRS2018

Realistic Covariance Generation for the GPM Spacecraft

We present several different methods for generating realistic predictive covariance, including Monte-Carlo simulations and more direct linear methods which require the addition of process noise. The Monte-Carlo simulation starts with an epoch uncertainty sample basis and propagates each trial to a time of interest in the future. The variance-covariance of the state elements as well as other higher order sample statistics can be readily computed from the propagated sample. While this method preserves the nonlinear effects on the propagated uncertainty, it is computationally intensive as a statistically significant sample size must be considered in the propagation process. Moreover, if the epoch covariance is optimistic, this can result in an underestimation of the prediction error. Another method is to propagate a state sensitivity matrix simultaneously with the satellite state, which allows the epoch covariances to be propagated forward in a linear fashion. This method does not preserve the non-linearity of the satellite state uncertainty but is much less computationally intensive. The propagated state covariance is the scaled to represent the realistic level of GPM state uncertainty via a "e-tuning process." The tuning process generates an inflation factor based on the observed error statistics of the predictive satellite trajectories when compared to the definitive ones. Difference tuning strategies are considered and compared via Goodness-of-Fit method testing for the Gaussian properties of the scaled covariance.

prediction error↗
NASA NTRS2018

Realistic Covariance Generation for the GPM Spacecraft

A covariance realism process for NASA's Global Precipitation Measurement (GPM) spacecraft is detailed. The GPM spacecraft is in a low earth orbit, and performs collision avoidance maneuvers few times a year. Currently GPM is below the International Space Station (ISS). So, in addition to cataloged debris objects, GPM must contend with smallsat/cubesat objects that are deployed from the ISS. Both operational scenarios require complete knowledge of the expected GPM prediction errors as a function of time. In this study, we present a method for generating realistic predicted covariance that uses linear propagation of the covariance with the addition of process noise. Further analyses are presented for the process noise ''tuning'' that generates an inflation factor based on the observed error statistics of the predictive satellite trajectories when compared to the definitive ones. Different tuning strategies are considered and compared via a Goodness-of-Fit testing for the Gaussian properties of the scaled covariance. SpaceNav's realistic covariance generation approach takes into account the contribution of predicted maneuver errors in the increased propagation uncertainty. Corresponding maneuver uncertainty is injected into the state uncertainty, and is used within the collision avoidance process to determine the collision risk for close approach events that follow a maneuver. This is a critical step in the maneuver planning process that provides the satellite operator with an accurate quantification of the collision probability for planned maneuvers. Using this information, an informed decision can be made to proceed with a maneuver if the collision risk is acceptable. This approach is validated by Monte-Carlo simulations and results are presented.

spacecraft uncertainty propagation↗
NASA NTRS2016

Global Precipitation Measurement (GPM) and International Space Station (ISS) Coordination for CubeSat Deployments to Minimize Collision Risk

The Global Precipitation Measurement Mission (GPM) is a joint U.S. and Japan mission to observe global precipitation, extending the Tropical Rainfall Measuring Mission (TRMM), which was launched by H-IIA from Tanegashima in Japan on February 28TH, 2014 directly into its 407km operational orbit. The International Space Station (ISS) is an international human research facility operated jointly by Russia and the USA from NASA's Johnson Space Center (JSC) in Houston Texas. Mission priorities lowered the operating altitude of ISS from 415km to 400km in early 2105, effectively placing both vehicles into the same orbital regime. The ISS has begun a program of deployments of cost effective CubeSats from the ISS that allow testing and validation of new technologies. With a major new asset flying at the same effective altitude as the ISS, CubeSat deployments became a serious threat to GPM and therefore a significant indirect threat to the ISS. This paper describes the specific problem of collision threat to GPM and risk to ISS CubeSat deployment and the process that was implemented to keep both missions safe from collision and maximize their project goals.

Pawloski, James H.↗
NASA NTRS2015

Tropical Rainfall Measurement Mission (TRMM) Operation Summary

The Tropical Rainfall Measurement Mission (TRMM) is a joint U.S. and Japan mission to observe tropical rainfall, which was launched by H-II No. 6 from Tanegashima in Japan at 6:27 JST on November 28, 1997. After the two-month commissioning of TRMM satellite and instruments, the original nominal mission lifetime was three years. In fact, the operations has continued for approximately 17.5 years. This paper provides a summary of the long term operations of TRMM.

radiometer↗