On generation of an assembly of images in ionospheric tomography

Radio tomography experiments have demonstrated the promising potential of a pplying tomographic methods in imaging various ionospheric structures. In a ctual implementation of image reconstructions one is faced with many choice s, which include the following: whether to use the total phase, relative ph ase, or Doppler as the projection data, how to approximate the projection o perator, what inversion algorithm to employ, and the choice of how to inclu de the ancillary data and constraints on the constructed image. Each choice results in an image compatible with the given or measured projection data, yet each choice results in an image different from that of the others, wit h its own attendant artifacts and distortions. Collectively, the images pro duced by all the possible choices comprise an assembly of images. In this s imulation study of one ionospheric model, 113 members of such an assembly a re generated. All images look similar in gross features with a root-mean-sq uare deviation not more than 29% from the mean. As expected, the largest de viation occurs near the region of highest gradients. By averaging all of th e images in the assembly we show that the mean image is superior because of its smallest root-mean-square deviation from the true image. This conclusi on, drawn on the simulation study of one model, may in fact have a general applicability, and we discuss why this may be so.