Bayesian Approach to Light Curve Inversion of 2020 SO

Campbell, Tanner; Furfaro, Roberto; Reddy, V.; Battle, Adam; Birtwhistle, P.; Linder, T.; Tucker, Stewart; Pearson, N.

doi:10.1007/s40295-021-00301-z

Cited by 3 publications

(11 citation statements)

References 15 publications

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“…This COM-COF offset can cause perturbations such as SRP or gravity gradient torque to have a larger destabilizing effect, giving rise to more complicated motion than just simple spin (i.e., precession, nutation, complex tumble, etc. ; Takahashi et al 2013), which is one possible explanation of the results seen in Campbell et al (2022). However, we see no such evidence for perturbations in the spin of the Chang'e 5-T1 R/B, implying that the COM-COF offset may be smaller than expected.…”

Section: Bayesian Analysis and Resultscontrasting

confidence: 61%

“…With these parameters and a previously selected shape, the model generates an associated light curve. An in-depth discussion of the model used is given in Campbell et al (2022), and a summary of this model is given in Section 6.1, while a description of our Bayesian inversion methodology is given in Section 6.2.…”

Section: Bayesian Inversion Methodologymentioning

confidence: 99%

“…There have been few attempts in the literature to apply these methods to a (partially) known object to assess the performance of a modelbased approach with a comparison to real data. One such example is by Campbell et al (2022), where they use this technique to look at cislunar object 2020 SO and recover several dynamical and physical properties. Originally discovered by Pan-STARRS1 and thought to be a natural object, it was later shown that 2020 SO was actually the Centaur upper stage from the Surveyor 2 mission.…”

Section: Photometric Analysismentioning

confidence: 99%

“…There is the attitude model, which handles the orientation of the body; the translational model, which handles the location of the body; and the reflective model, which handles the apparent brightness of the body. A complete description of each of these sections is given in Campbell et al (2022), but the relevant equations are given below without derivation.…”

Section: Dynamical Modelmentioning

confidence: 99%

See 3 more Smart Citations

Physical Characterization of Moon Impactor WE0913A

Campbell,

Battle,

Gray

et al. 2023

Planet. Sci. J.

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On 2022 March 4, the object known as WE0913A crashed into the Moon after several close flybys of the Earth and the Moon in the previous three months. Leading up to impact, the identity of the lunar impactor was up for debate, with two possibilities: the Falcon 9 from the DSCOVR mission or the Long March 3C from the Chang’e 5-T1 mission. In this paper, we present a trajectory and spectroscopic analysis using ground-based telescope observations to show conclusively that WE0913A is the Long March 3C rocket body (R/B) from the Chang’e 5-T1 mission. Analysis of photometric light curves collected before impact give a spin period of 185.221 ± 6.540 s before the first close Earth flyby on 2022 January 20 and a period of 177.754 ± 0.779 s, both at a 1σ confidence level, before the second close Earth flyby on 2022 February 8. Using Markov Chain Monte Carlo sampling and a predictive light curve simulation based on an anisotropic Phong reflection model, we estimate both physical and dynamical properties of the Chang’e 5-T1 R/B at the start of an observation epoch. The results from the Bayesian analysis imply that there may have been additional mass on the front of the rocket body. Using our predicted impact location, the Lunar Reconnaissance Orbiter was able to image the crater site approximately 7.5 km from the prediction. Comparing the pre- and post-impact images of the location shows two distinct craters that were made, supporting the hypothesis that there was additional mass on the rocket body.

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Section: Bayesian Analysis and Resultscontrasting

confidence: 61%

Section: Bayesian Inversion Methodologymentioning

confidence: 99%

Section: Photometric Analysismentioning

confidence: 99%

Section: Dynamical Modelmentioning

confidence: 99%

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Physical Characterization of Moon Impactor WE0913A

Campbell,

Battle,

Gray

et al. 2023

Planet. Sci. J.

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“…During this time, 2020 SO became bright enough for characterization with multiple techniques and instruments to study the object. The first manuscript to characterize the lightcurve of 2020 SO was published by Campbell et al (2022) and determined the object's spin state and used photometric data to find a rotation rate, estimated to be 9.328 ± 0.275 s at a 2σ confidence level. Bondarenko & Marshalov (2022) measured a radar albedo for 2020 SO of 0.95, a rotation rate of ∼9.5 s, estimated the object's size as approximately 10 m long and 3 m wide, and estimated a circular polarization ratio of ∼0.31, consistent with surface irregularities at centimeter sizes.…”

Section: Introductionmentioning

confidence: 99%

Challenges in Identifying Artificial Objects in the Near-Earth Object Population: Spectral Characterization of 2020 SO

Battle,

Reddy,

Sanchez

et al. 2024

Planet. Sci. J.

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Since the dawn of the Space Age, hundreds of payloads have been launched into heliocentric space. As near-Earth object (NEO) surveys search deeper for small asteroids, more artificial objects in heliocentric orbits are being discovered. We now face a challenge to identify the true nature of these objects and avoid contaminating the NEO catalog. Here, we present the methods used to characterize one such object. 2020 SO was discovered by the Pan-STARRS1 survey on 2020 September 17. Originally classified as a NEO, the object’s artificial nature became evident due to its low velocity relative to Earth and solar radiation pressure affecting its orbit about the Sun. Based on a backward propagation of its orbit, 2020 SO is thought to be a Centaur rocket body (R/B) from the launch of the Surveyor 2 mission to the Moon. We characterized 2020 SO using a range of ground-based optical and near-infrared telescopes to constrain its true nature. We find that its reflectance spectrum is consistent with that of other Centaur R/B launched during a similar time frame, and we identify 1.4, 1.7, and 2.3 μm absorption bands consistent with polyvinyl fluoride used on the aft bulkhead radiation shield exterior of Centaur-D R/B at the time.

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Stingray Sensor System for Persistent Survey of the GEO Belt

Campbell,

Battle,

Gray

et al. 2024

Sensors

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The Stingray sensor system is a 15-camera optical array dedicated to the nightly astrometric and photometric survey of the geosynchronous Earth orbit (GEO) belt visible above Tucson, Arizona. The primary scientific goal is to characterize GEO and near-GEO satellites based on their observable properties. This system is completely autonomous in both data acquisition and processing, with human oversight reserved for data quality assurance and system maintenance. The 15 ZWO ASI1600MM Pro cameras are mated to Sigma 135 mm f/1.8 lenses and are controlled simultaneously by four separate computers. Each camera is fixed in position and observes a 7.6-by-5.8-degree portion of the GEO belt, for a total of a 114-by-5.8-degree field of regard. The GAIA DR2 star catalog is used for image astrometric plate solution and photometric calibration to GAIA G magnitudes. There are approximately 200 near-GEO satellites on any given night that fall within the Stingray field of regard, and all those with a GAIA G magnitude brighter than approximately 15.5 are measured by the automated data reduction pipeline. Results from an initial one-month survey show an aggregate photometric uncertainty of 0.062 ± 0.008 magnitudes and astrometric accuracy consistent with theoretical sub-pixel centroid limits. Provided in this work is a discussion of the design and function of the system, along with verification of the initial survey results.

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Bayesian Approach to Light Curve Inversion of 2020 SO

Cited by 3 publications

References 15 publications

Physical Characterization of Moon Impactor WE0913A

Physical Characterization of Moon Impactor WE0913A

Challenges in Identifying Artificial Objects in the Near-Earth Object Population: Spectral Characterization of 2020 SO

Stingray Sensor System for Persistent Survey of the GEO Belt

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