Microwave tomography of lossy objects from monostatic measurements

This paper addresses the problem of microwave tomographic imaging from far- field monostatic measurements. In the first-order Born approximation, a sim ple Fourier relationship exists between the measured data and dielectric co ntrast of the object under test. For a lossy object, the contrast function depends on frequency, and this prevents monostatic data from being used dir ectly since multifrequency probing radiation must be used to get sufficient information. To overcome this difficulty, we propose a data preprocessing strategy that eliminates frequency from the function to be reconstructed. T he Fourier data obtained through preprocessing could be immediately inverte d to give a bandpass estimate of the unknown function. Despite the drawback s inherent in this approach, in small-scale tomographic applications, the s pace region occupied by the object under test, as well as the sign of the u nknown function, are normally known. This extra information allows us to ap ply a projected Landweber algorithm to uniquely reconstruct the unknown, th us avoiding the above-mentioned drawbacks, We outline the preprocessing and reconstruction techniques adopted, and show some preliminary results from experimental and simulated data.