A surface-layer representation of the lunar gravitational field

Wong, L.; Buechler, G.; Downs, W.; Sjogren, W. L.; Muller, P. M.; Gottlieb, Peter A.

doi:10.1029/jb076i026p06220

Cited by 54 publications

(46 citation statements)

References 8 publications

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“…From these data as well as tracking data from the Apollo Command Service Modules (CSM), many additional line-of-sight analyses were performed (e.g., Phillips et al (1972) on the Serenitatis mascon) in addition to surface mass distribution models by Wong et al (1971) and Ananda (1977).…”

Section: Introductionmentioning

confidence: 99%

Recent Gravity Models as a Result of the Lunar Prospector Mission

Konopliv

Asmar

Carranza

et al. 2001

Icarus

328

256

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Section: Introductionmentioning

confidence: 99%

Recent Gravity Models as a Result of the Lunar Prospector Mission

Konopliv

Asmar

Carranza

et al. 2001

Icarus

328

256

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“…The second set used the analysis derived by Wong. 7 The third set came from a study performed by Ferrari and Bills in 1979 8 that aimed at determining only low-degree terms. The fourth used a set of normal equations.…”

Section: Accuracy and History Of The Various Lunar Gravity Modelsmentioning

confidence: 99%

Influence of suboptimal navigation filter design on lunar landing navigation accuracy

Tuckness

1995

Journal of Spacecraft and Rockets

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Most onboard guidance, navigation, and control computers will be programmed using suboptimal filter design in an effort to reduce software size and computation speed. Reduction in the order of the gravity-field model of the moon is one method that can be used to reduce the number of calculations the onboard filter must perform, thus increasing the speed of computation. A result of that reduction is an increase in navigation error, which in turn directly influences the accuracy of the guidance commands. This paper investigates two prevalent lunar gravity-field models-the Ferrari 79 and the Sagitov model. A brief history of their origins and a comparison of the models are given. Particular emphasis is placed on studying their effect on guidance and navigation accuracy as the order of the onboard navigation filter model is reduced, resulting in a suboptimal filter design. NomenclatureAT, A N = truth and navigation state gradient matrices Alt. = altitude, m q, = semimajor axis, m Cnn = gravitational model constants CR = crossrange, m DR = downrange, m e = eccentricity vector G -sensor model measurements, m Hj, H N = truth and navigation observation update matrices h = angular momentum vector, m 2 /s 2 K F= navigation state Kalman-filter gain P r , P N = truth and navigation covariance matrices before navigation update PT, PN = truth and navigation covariance matrices after navigation update Q = unknown state noise matrix R = navigation measurement noise matrix r -inertial radial vector, m r p = radius of periapsis, m v -velocity magnitude, m/s 2 WT , WN = truth and navigation weighting matrices (identity matrix for this study) XT, X N = truth and navigation state vectors, m // = gravitational parameter, m 2 /s 3 4> r , & N = truth and navigation state transition matrices x = vector cross product

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“…Gravity models of this type include the lunar frontside gravity representations of Gottlieb (1970) Wong et al (1971), and and the Venus gravity models of Reasenberg et al (1981Reasenberg et al ( , 1982 and Esposito et al (1982). Again, the resolution of even the most detailed these models is too low (on the order of 200 km) for local geophysical analysis.…”

Section: Introductionmentioning

confidence: 99%

Local harmonic analysis of planetary Doppler gravity data

Kunze

1985

Earth Moon Planet

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Planetary gravity fields represented in terms of spherical harmonics or surface mass distributions do not have the necessary resolution to permit gravity analysis of local features. Doppler gravity maps representing residual line-of-sight (LOS) accelerations have much greater resolution but cannot be used for conventional geophysical analysis due to the geometric distortions inherent in LOS gravity patterns and lack of normalization of LOS data. However, LOS gravity data may be converted to vertical gravity anomalies by expressing the anomalous local gravitational potential over small rectangular areas in terms of a modified double Fourier series constrained by local Doppler gravity data. The vertical derivative of the resulting potential yields the vertical gravity components at desired altitudes. The resolution of the resulting normalized free air anomaly maps is limited only by that of the original Doppler gravity data. Extended gravity maps may be constructed this way using a moving window approach. It is anticipated that much of the lunar frontside can be mapped at resolutions ranging from 1 to 4 deg of arc.

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A surface-layer representation of the lunar gravitational field

Cited by 54 publications

References 8 publications

Recent Gravity Models as a Result of the Lunar Prospector Mission

Recent Gravity Models as a Result of the Lunar Prospector Mission

Influence of suboptimal navigation filter design on lunar landing navigation accuracy

Local harmonic analysis of planetary Doppler gravity data

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