Detection of a faint fast-moving near-Earth asteroid using the synthetic tracking technique
- Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States)
We report a detection of a faint near-Earth asteroid (NEA) using our synthetic tracking technique and the CHIMERA instrument on the Palomar 200 inch telescope. With an apparent magnitude of 23 (H = 29, assuming detection at 20 lunar distances), the asteroid was moving at 6.°32 day{sup –1} and was detected at a signal-to-noise ratio (S/N) of 15 using 30 s of data taken at a 16.7 Hz frame rate. The detection was confirmed by a second observation 77 minutes later at the same S/N. Because of its high proper motion, the NEA moved 7 arcsec over the 30 s of observation. Synthetic tracking avoided image degradation due to trailing loss that affects conventional techniques relying on 30 s exposures; the trailing loss would have degraded the surface brightness of the NEA image on the CCD down to an approximate magnitude of 25 making the object undetectable. This detection was a result of our 12 hr blind search conducted on the Palomar 200 inch telescope over two nights, scanning twice over six (5.°3 × 0.°046) fields. Detecting only one asteroid is consistent with Harris's estimates for the distribution of the asteroid population, which was used to predict a detection of 1.2 NEAs in the H-magnitude range 28-31 for the two nights. The experimental design, data analysis methods, and algorithms are presented. We also demonstrate milliarcsecond-level astrometry using observations of two known bright asteroids on the same system with synthetic tracking. We conclude by discussing strategies for scheduling observations to detect and characterize small and fast-moving NEAs using the new technique.
- OSTI ID:
- 22365194
- Journal Information:
- Astrophysical Journal, Vol. 792, Issue 1; Other Information: Country of input: International Atomic Energy Agency (IAEA); ISSN 0004-637X
- Country of Publication:
- United States
- Language:
- English
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