Bibcode
Muinonen, Karri; Torppa, Johanna; Virtanen, Jenni; Näränen, Jyri; Niemel, Jarkko; Granvik, Mikael; Laakso, Teemu; Parviainen, Hannu; Aksnes, Kaare; Dai, Zhang; Ingvar Lagerkvist, Claes; Rickman, Hans; Karlsson, Ola; Hahn, Gerhard; Michelsen, René; Grav, Tommy; Pravec, Petr; Jørgensen, Uffe Grâe
Referencia bibliográfica
Near Earth Objects, our Celestial Neighbors: Opportunity and Risk, Proceedings if IAU Symposium 236. Edited by G.B. Valsecchi and D. Vokrouhlický, and A. Milani. Cambridge: Cambridge University Press, 2007., pp.309-320
Fecha de publicación:
0
2007
Número de citas
1
Número de citas referidas
1
Descripción
The Nordic Near-Earth Object Network (Nordic NEON) observing program was
established to obtain knowledge of the physical and dynamical properties
of near-Earth objects (NEOs). Photometric and astrometric observations
have been carried out at the Nordic Optical Telescope since June 2004.
By collaborating with other observing programs and applying for
observing time from other telescopes (e.g. European Southern
Observatory), we aim at significantly increasing the knowledge of the
physical and dynamical properties of NEOs by using novel inverse
methods. For many targets with previously published spin solutions we
cannot, in reality, get a single solution based on existing data, but
there exist a large number of possible solutions none of which can be
given priority over the others. Currently, distributions of possible
pole directions and shapes have been derived for four new asteroids
(2002 FF12, 2003 MS2, 2003 RX7, 2004 HW) as well as for 1685 Toro and
1981 Midas. For 1862 Apollo, we have obtained an unambiguous spin and
shape solution. Following the so-called statistical inversion theory and
focussing on 2004 AS1 that once posed an imminent impact hazard some 48
hours after discovery, we illustrate the challenges in assessing the
collision probabilities of NEOs with exiguous observational data.
Finally, we describe an orbit computation method utilizing the full
six-dimensional phase-space volume of variation for objects with
moderate observational data, underscoring its future prospects in
collision probability computations.