Kuo, Sen M. (Sen-Maw)
M.S. (Master of Science)
Department of Electrical Engineering
Radar; Polarization (Electricity); Electromagnetic waves--Polarization
When an electromagnetic signal emitting from a radar transmitter strikes a target, current is induced on the target and the electromagnetic signal is scattered in all directions. As a result, the polarization of the scattered signal is different than that of the incident signal. This information is contained in a 2x2 complex matrix known as a scattering matrix of the target and can provide useful information for classification and identification of radar targets. Research is currently under way to determine how to extract information about the target from the given scattering matrix. Previous studies have developed the characteristic polarization theory for the monostatic reciprocal case, in which the same polarization of the transmitter and receiver was used. The characteristic polarizations corresponding to the maximum and minimum power received in the co-polarized and cross-polarized receiving channels were calculated, and their relation to the target properties was established. This research considers the non-reciprocal case, in which variable polarizations of both the transmitter and receiver are considered separately. Results are presented to show that for general targets, the maximum received power can be extracted from a target by changing both the transmitter and receiver polarizations. There exists in this case four characteristic polarization states that identify the maxima and minima in the co-polarized and cross-polarized radar channels. Two general targets are used, one reciprocal and one non-reciprocal, to identify the characteristic polarization states. Power spectrum plots of the two channels’ received power for given channel polarizations are included, as well as the FORTRAN programs written to perform the calculations for different targets and radar configurations.
Evans, Brian L., "Development of optimal polarization theory for radar target classification and identification" (1993). Graduate Research Theses & Dissertations. 2195.
viii, 36 pages
Northern Illinois University
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