P41C-3911:
Reconstructing the Surface Permittivity Distribution from Data Measured by the CONSERT Instrument aboard Rosetta: Method and Simulations

Thursday, 18 December 2014
Dirk Plettemeier1, Christoph Statz1, Sebastian Hegler1, Alain Herique2 and Wlodek W Kofman2, (1)Dresden University of Technology, Dresden, Germany, (2)University Joseph Fourier Grenoble, Grenboble, France
Abstract:
One of the main scientific objectives of the Comet Nucleus Sounding Experiment by Radiowave Transmission (CONSERT) aboard Rosetta is to perform a dielectric characterization of comet 67P/Chuyurmov-Gerasimenko’s nucleus by means of a bi-static sounding between the lander Philae launched onto the comet’s surface and the orbiter Rosetta. For the sounding, the lander part of CONSERT will receive and process the radio signal emitted by the orbiter part of the instrument and transmit a signal to the orbiter to be received by CONSERT.

CONSERT will also be operated as bi-static RADAR during the descent of the lander Philae onto the comet's surface. From data measured during the descent, we aim at reconstructing a surface permittivity map of the comet at the landing site and along the path below the descent trajectory. This surface permittivity map will give information on the bulk material right below and around the landing site and the surface roughness in areas covered by the instrument along the descent.

The proposed method to estimate the surface permittivity distribution is based on a least-squares based inversion approach in frequency domain. The direct problem of simulating the wave-propagation between lander and orbiter at line-of-sight and the signal reflected on the comet's surface is modelled using a dielectric physical optics approximation.

Restrictions on the measurement positions by the descent orbitography and limitations on the instrument dynamic range will be dealt with by application of a regularization technique where the surface permittivity distribution and the gradient with regard to the permittivity is projected in a domain defined by a viable model of the spatial material and roughness distribution. The least-squares optimization step of the reconstruction is performed in such domain on a reduced set of parameters yielding stable results.

The viability of the proposed method is demonstrated by reconstruction results based on simulated data.