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At least 433 records · Page 24

Predictive Attitude Estimation Using Global Positioning System Signals

In this paper, a new algorithm is developed for attitude estimation using Global Positioning System (GPS) signals. The new algorithm is based on a predictive filtering scheme designed for spacecraft without rate measuring devices. The major advantage of this new algorithm over traditional Kalman filter approaches is that the model error is not assumed to represented by an unbiased Gaussian noise process with known covariance, but instead is determined during the estimation process. This is achieved by simultaneously solving system optimality conditions and an output error constraint. This approach is well suited for GPS attitude estimation since some error sources that contribute to attitude inaccuracy, such as signal multipath, are known to be non-Gaussian processes. Also, the predictive filter scheme can use either GPS signals or vector observations or a combination of both for attitude estimation, so that performance characteristics can be maintained during periods of GPS attitude sensor outage. The performance of the new algorithm is tested using flight data from the REX-2 spacecraft. Results are shown using the predictive filter to estimate the attitude from both GPS signals and magnetometer measurements, and comparing that solution to a magnetometer-only based solution. Results using the new estimation algorithm indicate that GPS-based solutions are verified to within 2 degrees using the magnetometer cross-check for the REX-2 spacecraft. GPS attitude accuracy of better than 1 degree is expected per axis, but cannot be reliably proven due to inaccuracies in the magnetic field model.

Crassidis, John L.↗

Implementing JEDI into NASA GMAO’s Real Time Production Suite

NASA’s Global Modeling and Assimilation Office (GMAO) has prepared their first production system involving the Joint Effort for Data assimilation Integration (JEDI) framework. In this system the central analysis, that drives the deterministic forecast, will be provided using JEDI. This talk outlines the phased approach to implementing JEDI into production that GMAO has designed, and how this approach will allow for a careful analysis of the system against the existing data assimilation framework (GSI). In the first phase of implementation the existing data assimilation system will perform certain actions that are still under development in JEDI. These include thinning the observations and producing satellite bias correction coefficients. JEDI is hooked up to the existing workflow so a single line switch can activate whether the existing or JEDI-based analysis is cycled. Outside of the monumental effort to construct JEDI that is ongoing at the Joint Center for Satellite Data Assimilation (JCSDA), GMAO have undertaken two areas of considerable effort. The talk will describe these efforts and highlight the main challenges that have been encountered. The first area of work is to implement the background error model from the existing data assimilation system into JEDI. The second is to validate the observing system in JEDI against the one in GSI, which has involved several new features being added to the observation operators in JEDI. While the longer-term plans involve trying to improve on the GSI in these two areas, GMAO is keen to have JEDI start from a trusted baseline. This is also key to implementing JEDI quickly so other priorities, such as increasing the number of model levels, can be easily worked on in parallel. GMAO is actively working on a framework to shepherd in the next generation coupled data assimilation system and model. As JEDI is implemented for the first time the plan is to ambitiously cycle through implementations, frequently bringing JEDI features to production. Details of these plans will be given in the talk and we will highlight key implementation and product milestones that we hope to achieve, as well as touch on the development environment that we will use to support frequent refreshing of the production system.

JEDI↗

The effect of horizontal resolution on systematic errors of the GLA forecast model

Systematic prediction errors of the Goddard Laboratory for Atmospheres (GLA) forecast system are reduced when the higher-resolution (2 x 2.5 deg) model version is used. Based on a budget analysis of the 200-mb eddy streamfunction, the improvement of stationary eddy forecasting is seen to be caused by the following mechanism: by increasing the horizontal spatial resolution of the forecast model, atmospheric diabatic heating over the three tropical continents is changed in a way that intensifies the planetary-scale divergent circulations associated with the three pairs of divergent-convergent centers over these continents. The intensified divergent circulation results in an enhancement of vorticity sources in the Northern Hemisphere. The additional vorticity is advected eastward by a stationary wave train along 30 deg N, thereby reducing systematic errors in the lower-resolution (4 x 5 deg) GLA model.

Chen, Tsing-Chang↗

Navigation analysis for Viking 1979, option B

A parametric study performed for 48 trans-Mars reference missions in support of the Viking program is reported. The launch dates cover several months in the year 1979, and each launch date has multiple arrival dates in 1980. A plot of launch versus arrival dates with case numbers designated for reference purposes is included. The analysis consists of the computation of statistical covariance matrices based on certain assumptions about the ground-based tracking systems. The error model statistics are listed in tables. Tracking systems were assumed at three sites: Goldstone, California; Canberra, Australia; and Madrid, Spain. The tracking data consisted of range and Doppler measurements taken during the tracking intervals starting at E-30(d) and ending at E-10(d) for the control data and ending at E-18(h) for the knowledge data. The control and knowledge covariance matrices were delivered to the Planetary Mission Analysis Branch for inputs into a delta V dispersion analysis.

Mitchell, P. H.↗

Metric analysis of minitrack optical and interferometer data

The network analysis program (NAP-2), which has the capability of simultaneously solving for orbits and tracking station error model terms, was, after several modifications, used in the calibration of minitrack stations using minitrack satellite measurements (self-calibration). Several support programs were written to aid in this task. A simultaneous four-arc solution was obtained. A comparison with optically determined arcs for the same time spans showed rms position differences of 67m, 86m, 124m and 168m for the 4 arcs considered. An apparatus incorporating a diffraction grating was designed and successfully used to measure the drift rate of the Fort Myers MOTS camera drive.

Brown, D. C.↗

A detailed analysis of Mariner nine TV navigation data.

Mariner 9 data analysis showed a good performance of the Mars probe planetary approach navigation systems and a good agreement between measured and predicted probe-approach characteristics. It was found that all operations were completed on time and that the calibration of the instruments and the observation of a greater-than-planned number of stars resulted in a higher-than-expected measurement accuracy. The key instruments of the Mariner were TV cameras taking pictures of Phobos and Deimos against a background of stars, calibrated sun and star sensors, and a scan platform. The error models used for optical navigation system elements, the calibration of the scan platform and of the TV cameras, and the image detection and location techniques are discussed in detail.

Breckenridge, W. G.↗

Adaptive filtering with correlated state noise

An adaptive filter which uses a minimum variance criteria to estimate state noise covariance is presented. It is not necessary to assume white state noise in order to implement the filter. Simulation results are given which demonstrate that the filter tracks a satellite in the presence of modeling errors better than a conventional minimum variance filter with state noise. It is also shown that the propagated convariance matrix of the filter is an accurate indicator of the filter's performance.

Argentiero, P.↗

Adaptive sequential estimation with applications

A sequential estimator is presented and demonstrated which successfully tracks the system state and model errors in the presence of significant and unpredictable system or environmental variations. This adaptive estimation concept is shown to lead to a new and attractive approach to parameter identification problems. Simulation results are presented in an orbit determination problem and in a reentry trajectory estimation problem.

Jazwinski, A. H.↗

The background for Skylab experiment T-002, manual navigation sightings

The background of the NASA-DOD manual navigation experiment (T002) on Skylab A is reviewed with emphasis on NASA's development of an error model for sextant measurements in midcourse navigation and on USAF's development of a low earth orbit manual navigation scheme. Instruments briefly described are a space sextant and space stadimeter, both of which are used by USAF in orbit navigation, the sextant by NASA in midcourse sightings. The rationale, data requirements, and data reduction procedures are discussed in terms of the goals of the agencies.

Randle, R. J.↗

Skylab S-193 altimeter experiment performance, results and applications

A description of the Skylab altimeter instrument system along with the appropriate system error model is presented. The data processing flow, orbit computation, and topographic recovery techniques are discussed. Some data analysis results are presented which indicate excellent correlation with underwater topographic features. In addition, results are shown which indicate that the instrument performance was as expected.

Mcgoogan, J. T.↗

In-flight calibration of the high-gain antenna pointing for the Mariner Venus-Mercury 1973 spacecraft

The methods used to in-flight calibrate the pointing direction of the Mariner Venus-Mercury 1973 spacecraft high gain antenna and the achieved antenna pointing accuracy are described. The overall pointing calibration was accomplished by performing calibration sequences at a number of points along the spacecraft trajectory. Each of these consisted of articulating the antenna about the expected spacecraft-earth vector to determine systematic pointing errors. The high gain antenna pointing system, the error model used in the calibration, and the calibration and pointing strategy and results are discussed.

Hardman, J. M.↗

LACIE performance predictor FOC users manual

The LACIE Performance Predictor (LPP) is a computer simulation of the LACIE process for predicting worldwide wheat production. The simulation provides for the introduction of various errors into the system and provides estimates based on these errors, thus allowing the user to determine the impact of selected error sources. The FOC LPP simulates the acquisition of the sample segment data by the LANDSAT Satellite (DAPTS), the classification of the agricultural area within the sample segment (CAMS), the estimation of the wheat yield (YES), and the production estimation and aggregation (CAS). These elements include data acquisition characteristics, environmental conditions, classification algorithms, the LACIE aggregation and data adjustment procedures. The operational structure for simulating these elements consists of the following key programs: (1) LACIE Utility Maintenance Process, (2) System Error Executive, (3) Ephemeris Generator, (4) Access Generator, (5) Acquisition Selector, (6) LACIE Error Model (LEM), and (7) Post Processor.

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