Engineering topics

Kronenwetter, Jeffrey

Publications and source records attributed to Kronenwetter, Jeffrey.

6 records

NASA NTRS2019

Summary of Space Environment Magnetometer and Particle Replacement Experiment (SEMPRE) Study

As part of the GOES-R series follow on architecture study following the NOAA Satellite Observing System Architecture (NSOSA) study, a study team evaluated the feasibility of accommodating the GOES in-situ instruments (Magnetometer and Particle Detectors) on a dedicated spacecraft with no impact to the overall baseline mission cost assuming two large observatories. The accommodations cost on a primary operational type observatory are non-negligible requiring: a large non-magnetic boom to reduce the impact of the spacecraft interference on the magnetometer; and strict contamination control and magnetic cleanliness to prevent magnetic contamination near the magnetometers. These, along with the additional interface complexities greatly increase the cost of larger spacecraft by extending integration time with a large marching army. By contrast, a dedicated mission provides flexibility in location and refresh rate not afforded when these sensors are launched as secondary payloads. This study performed an informal industry survey of small form-factor instruments currently flying or in process of being developed. The study identified three potential particle detector suites and multiple magnetometers that will satisfy the requirements while having low enough volume and mass to allow accommodation on a rideshare class spacecraft. Using the largest of the identified particle detector suites, the Goddard Space Flight Center Mission Design Lab developed a design for a rideshare spacecraft that will accommodate the particle detector suite and magnetometer. The cost of the spacecraft, based on multiple cost models, is comparable to the cost of accommodating the magnetometer and particle detector suite on two (East and West) larger main observatories.

Todirita, Monica↗

NASA NTRS2019

GOES-17 Magnetometer On-Orbit Calibration Design and Results

The Geostationary Operational Environmental Satellite-R (GOES-R) is a series of four NOAA weather satellites. Each spacecraft flies a Magnetometer instrument which includes two boom mounted fluxgate sensors located 6.3 and 8.5 meters from the spacecraft. Sensor readings are corrupted by both internal (bias and scale factor) and external (spacecraft emitted fields and misalignments) error sources. In order to estimate the bias, an on-orbit calibration is performed, slewing the spacecraft about multiple axes and then performing a fit of the data to determine zero offset and misalignment terms. The first satellite in the series, GOES-16 was launched in November 2016. Its magnetometer calibration maneuver was found to be inadequate providing insufficient rotation about orthogonal axes. The uncertainty in the estimated biases was found to be in the 3-5 nanotesla range, exceeding the magnetometer accuracy requirement of 1.0 nanotesla. Based on lessons learned, the maneuver was redesigned to provide multiple 360 degree rotations about two orthogonal axes, providing optimal visibility into bias and misalignment. Varying ambient fields over the duration of the calibration maneuvers, corrupts the ability to accurately determine parameters of interest. To address this issue, rather than assuming a constant field for the duration of the maneuver, a non-linear least squares filter was employed that uses a series of spline functions to better fit the ambient field. The number of splines can be varied to minimize the least squares filter residuals. Simulations were performed using 360 days of GOES-16 data to bound the uncertainty in the biases for given residuals of the fit to the ambient field. Following the launch of the second satellite in the series, GOES-17 in March 2018, the new calibration maneuver and enhanced bias estimation algorithm were exercised twice. Based on the residuals of the fit, the uncertainty of the estimated zero offset was reduced by an order of magnitude from 3-5 nanotesla to approximately 0.4 nanotesla per axis. This paper provides details of the maneuver design and the innovative algorithm used to estimate the GOES-17 biases and misalignments.

GOES-17↗

NASA NTRS2016

Correcting GOES-R Magnetometer Data for Stray Fields

Time-varying spacecraft magnetic fields, i.e. stray fields, are a problem for magnetometer systems. While constant fields can be removed by calibration, stray fields are difficult to distinguish from ambient field variations. Putting two magnetometers on a long boom and solving for both the ambient and stray fields can help, but this gradiometer solution is more sensitive to noise than a single magnetometer. As shown here for the R-series Geostationary Operational Environmental Satellites (GOES-R), unless the stray fields are larger than the noise, simply averaging the two magnetometer readings gives a more accurate solution. If averaging is used, it may be worthwhile to estimate and remove stray fields explicitly. Models and estimation algorithms to do so are provided for solar array, arcjet and reaction wheel fields.

Magnetometer↗

NASA NTRS2016

Correcting GOES-R Magnetometer Data for Stray Fields

Time-varying spacecraft magnetic fields or stray fields are a problem for magnetometer systems. While constant fields can be removed with zero offset calibration, stray fields are difficult to distinguish from ambient field variations. Putting two magnetometers on a long boom and solving for both the ambient and stray fields can be a good idea, but this gradiometer solution is even more susceptible to noise than a single magnetometer. Unless the stray fields are larger than the magnetometer noise, simply averaging the two measurements is a more accurate approach. If averaging is used, it may be worthwhile to explicitly estimate and remove stray fields. Models and estimation algorithms are provided for solar array, arcjet and reaction wheel fields.

Magnetometers↗

NASA NTRS2016

Assessing and Ensuring GOES-R Magnetometer Accuracy

The GOES-R magnetometer accuracy requirement is 1.7 nanoteslas (nT). During quiet times (100 nT), accuracy is defined as absolute mean plus 3 sigma. During storms (300 nT), accuracy is defined as absolute mean plus 2 sigma. To achieve this, the sensor itself has better than 1 nT accuracy. Because zero offset and scale factor drift over time, it is also necessary to perform annual calibration maneuvers. To predict performance, we used covariance analysis and attempted to corroborate it with simulations. Although not perfect, the two generally agree and show the expected behaviors. With the annual calibration regimen, these predictions suggest that the magnetometers will meet their accuracy requirements.

Magnetometer↗

NASA NTRS2016

Assessing and Ensuring GOES-R Magnetometer Accuracy

The GOES-R magnetometer subsystem accuracy requirement is 1.7 nanoteslas (nT). During quiet times (100 nT), accuracy is defined as absolute mean plus 3 sigma. During storms (300 nT), accuracy is defined as absolute mean plus 2 sigma. Error comes both from outside the magnetometers, e.g. spacecraft fields and misalignments, as well as inside, e.g. zero offset and scale factor errors. Because zero offset and scale factor drift over time, it will be necessary to perform annual calibration maneuvers. To predict performance before launch, we have used Monte Carlo simulations and covariance analysis. Both behave as expected, and their accuracy predictions agree within 30%. With the proposed calibration regimen, both suggest that the GOES-R magnetometer subsystem will meet its accuracy requirements.

Magnetometer↗