Abstract
Recent technological advancements have made it possible to produce synthetic aperture radar (SAR) based microwave images in real time by using a variety of microwave imaging (array) systems. However, depending on the imaging array construction and the data collection scheme, the pertinent data of interest may be corrupted by undesired signals resulting from array element mutual coupling and overall poor isolation. Poor isolation associated with array elements may result from imperfect RF switching, internal coupling mechanisms inherent in a measurement system, or imperfect signal tagging schemes (i.e., multiple elements modulating when using the modulated scatterer technique). Images produced from such corrupted data are blurred or have artifacts that tend to mask the desired indications. This paper demonstrates the extension of a well-known correlation canceling technique for the purpose of preprocessing the data to remove such undesired coupling effects. To demonstrate its effectiveness, it is applied to a recently developed 2-D high-resolution and real-time microwave imaging system (camera). This camera is composed of 576 array elements, which are susceptible to the type of signal degradation mentioned above. Three correction estimates of the preprocessor are performed and compared. Two of the correction estimates directly address coupling, and the third, which does not consider coupling, is used for comparison purposes. Simulation results show the efficacy of this method, which is then corroborated by experiments.
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