Orbit and Constellation Design

Wertz, James R.

doi:10.1007/978-94-011-2692-2_7

Cited by 23 publications

(32 citation statements)

References 7 publications

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“…However, gravity gradient torque is cyclical over an RSO orbit [11]. None of the observed spin-period variations showed any evidence of periodic behavior within a single GEO period.…”

Section: Torque Source Evaluationmentioning

confidence: 80%

“…Gravity gradient torque attempts to stabilize an RSO's attitude by aligning it with the Earth's gravity well. SRP torque, primarily due to sunlight, acts on all sunlit parts of the RSO [11].…”

Section: Torque Source Evaluationmentioning

confidence: 99%

“…In contrast with the aerodynamic, gravity gradient, and magnetic torques, the SRP torque will constantly act on an RSO no matter what its orbit altitude, with the exception of eclipses [11]. As the Earth orbits the sun, the RSO's spin axis will change its orientation with respect to the sun, thereby modulating the SRP effect and possibly causing the observed spin period to change with time.…”

Section: Torque Source Evaluationmentioning

confidence: 99%

“…The most significant investigation that studied the long-term (several years or more) apparent spin-period variation of a number of inactive GEO RSOs, mainly Russian Raduga (rainbow) and Gorizont (horizon) types, was conducted by Papushev et al [ GOES 8,9,10,11, and 12. Cognion concluded that the GOES satellites exhibited spin periods ranging from 16 s to 20 min and exhibited different light curves from one another, despite nearly identical satellite designs.…”

Section: Introductionmentioning

confidence: 99%

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Observations of the Spin-Period Variations of Inactive Box-Wing Geosynchronous Satellites

Earl

Wade

2015

Journal of Spacecraft and Rockets

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Ground-based broadband photometric observations of four inactive geosynchronous satellites of "box-wing" design were frequently performed between March 2012 and December 2013 to commence a long-term study of their attitude dynamics. The brightness of the satellites was observed to vary in a periodic fashion, which was interpreted to mean that reflected sunlight was being modulated due to satellite spin. The average observed spin periods inferred from the light curves ranged from 158 to 1548 s. The variation of each satellite's inferred spin period was observed to be small or negligible over hourly timescales but varied significantly (from 15 to 25% of the average) and smoothly (possibly cyclically) over monthly to yearly timescales. The characteristics of the observed spin-period variations, including the amplitudes, timescales, and shapes, differed greatly between satellites and suggest a relationship between the average observed spin period and the variation amplitude. The observed spin-period variations were interpreted as being due to one or more external disturbance torques acting on the spacecraft. The most significant torque was found to be solar radiation pressure acting on the large-area solar panels. The magnitude of this torque produced sufficient angular accelerations to explain the observed spin-period variations. A first-order phenomenological model is proposed to explain the high-level aspects of the observed phenomena. Nomenclature A = amplitude of spin-period variation, s A panel = area of a single solar panel, m 2 a = length of satellite central box (cube) side, m D = residual dipole moment, A · m 2 I = moment of inertia, kg · m 2 l panel = length of a single, fully deployed solar panel, m l tot = total length of a satellite (wingspan), m M = total mass of satellite, kg M Earth = magnetic moment of the Earth, T · m 3 m box = mass of the central satellite box (cube), kg m panel = mass of a single solar panel, kg P rad = average solar radiation pressure at one astronomical unit from the sun, Pa q 1 = reflectivity of a solar panel side q 2= reflectivity of the opposite solar panel side to q 1 R = distance from the center of the Earth, m T = satellite spin period, s T Earth = orbit period of the Earth, days T 1 = observed satellite spin period at one specific epoch, s T 2 = observed satellite spin period at an epoch later than T 1 , s T = average satellite spin period, s t = day of year, days t 0 = reference time that determines the phase parameter, days t 1 = reference time 1, s t 2 = reference time 2 (later than t 1 ), s t 3 = reference time 3 (later than t 2 ), s w panel = width of a single solar panel, m α = equatorial right ascension coordinate, deg of arc α HGS max = maximum observed angular acceleration of HGS-1, μrad · s −1 · day −1 α SRP = angular acceleration due to solar radiation pressure torque, μrad · s −1 · day −1 α SRP max = maximum angular acceleration due to solar radiation pressure torque, μrad · s −1 · day −1 α spin = net spin angular acceleration, μrad · s −1 · day −1 α = angula...

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“…However, gravity gradient torque is cyclical over an RSO orbit [11]. None of the observed spin-period variations showed any evidence of periodic behavior within a single GEO period.…”

Section: Torque Source Evaluationmentioning

confidence: 80%

Section: Torque Source Evaluationmentioning

confidence: 99%

Section: Torque Source Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Observations of the Spin-Period Variations of Inactive Box-Wing Geosynchronous Satellites

Earl

Wade

2015

Journal of Spacecraft and Rockets

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“…The rotating frame rotates with angular velocity ω E about the Z-axis. ω E is the rotational velocity of Earth, which is equal to 7.292115·10 −5 rad/s [69]. If the two frames coincide at the start of the simulation and t is the amount of time that has past since then, the angle between X I and X R is equal to ω E t and the transformation matrix is given by:…”

Section: Rotating Planetocentric To Inertial Planetocentric Referencementioning

confidence: 99%

Application of Taylor Series Integration to Reentry Problems

Bergsma

2016

AIAA Atmospheric Flight Mechanics Conference

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Artificial Neural Networks for Tours of Multiple Asteroids

Viavattene¹,

Ceriotti²

2020

Lecture Notes in Computer Science

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Designing multiple near-Earth asteroid (NEA) rendezvous missions is a complex global optimization problem, which involves the solution of a large combinatorial part to select the sequences of asteroids to visit. Given that more than 22,000 NEAs are known to date, trillions of permutations between asteroids need to be considered. This work develops a method based on Artificial Neural Networks (ANNs) to quickly estimate the cost and duration of low-thrust transfers between asteroids. The capability of the network to map the relationship between the characteristics of the departure and arrival orbits and the transfer cost and duration is studied. To this end, the optimal network architecture and hyper-parameters are identified for this application. An analysis of the type of orbit parametrization used as network inputs for best performance is performed. The ANN is employed within a sequencesearch algorithm based on a tree-search method, which identifies multiple rendezvous sequences and selects those with lowest time of flight and propellant mass needed. To compute the full trajectory and control history, the sequences are subsequently optimized using an optimal control solver based on a pseudospectral method. The performance of the proposed methodology is assessed by investigating NEA sequences of interest. Results show that ANN can estimate the cost or duration of optimal low-thrust transfers with high accuracy, resulting into a mean relative error of less than 4%.

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Orbit and Constellation Design

Cited by 23 publications

References 7 publications

Observations of the Spin-Period Variations of Inactive Box-Wing Geosynchronous Satellites

Observations of the Spin-Period Variations of Inactive Box-Wing Geosynchronous Satellites

Application of Taylor Series Integration to Reentry Problems

Artificial Neural Networks for Tours of Multiple Asteroids

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