ARTI: One New Adaptive Elliptical Weighting Model Combining with the Tikhonov-ℓ_p-norm for Image Reconstruction

To reconstruct the target-induced attenuation image keeping consistent with the observed measurement data, this paper explores the use of a new horizontal distance attenuation-based elliptical weighting model in building an attenuation image, where a horizontal distance attenuation factor and a vertical distance attenuation factor are introduced, respectively, which is able to clear the difference of the voxel weightings perpendicular to the line-of-sight (LOS) direction, as well as the difference of the voxel weightings parallel to the LOS direction. Compared with the existing model, the proposed model can additively reflect the occlusion effect of the radio frequency signal when the target is close to the transceiver nodes. Besides, the Tikhonov-ℓ_p-norm regularization is incorporated into the image reconstruction, which makes full use of the sparse ability of the ℓ_p-norm (0 < p < 1) to further reduce the noise interference. The experimental studies on indoor and outdoor scenarios with radio tomographic imaging are presented to validate the effectiveness of the proposed approach.