Presentation Title

Optimization of a MIMO-CSAR Array through a Genetic Algorithm

Faculty Mentor

Enson Chang

Start Date

23-11-2019 1:15 PM

End Date

23-11-2019 1:30 PM

Location

Markstein 105

Session

oral 3

Type of Presentation

Oral Talk

Subject Area

engineering_computer_science

Abstract

Traditional millimeter-wave synthetic aperture radar (SAR) and circular SAR (CSAR) are widely used in low resolution imaging of surfaces greater than or equal to one meter away. Prospects of subwavelength resolution have previously been discounted due to problematic sidelobes that develop at subwavelength distances around imaging targets. While the common benefit of SAR imaging is the use of a single sensor, increasing the number of sensors slightly allows for a multiple-input-multiple-output (MIMO) approach that achieves subwavelength resolution. We have developed a 6 sensor MIMO CSAR processor that drastically reduces sidelobe levels, thus enabling subwavelength imaging. The MIMO CSAR processor reduces overall sidelobe levels by production of multiple unique sidelobe emissions. Overlapping of these emissions spreads out the energy contained in each sidelobe and amplifies the energy of the central beam. The unique sidelobe emissions result from application of the polar formatting algorithm in a MIMO situation, specifically, transmission and reception at distinct angular separations produces unique images within the kappa domain. Optimal angular spacings in a 6-transceiver configuration were found through a genetic algorithm. The genetic algorithm was designed with the goal of reducing the peak sidelobe strength. Our MIMO CSAR processor can produce images with a resolution of lambda/2.

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Nov 23rd, 1:15 PM Nov 23rd, 1:30 PM

Optimization of a MIMO-CSAR Array through a Genetic Algorithm

Markstein 105

Traditional millimeter-wave synthetic aperture radar (SAR) and circular SAR (CSAR) are widely used in low resolution imaging of surfaces greater than or equal to one meter away. Prospects of subwavelength resolution have previously been discounted due to problematic sidelobes that develop at subwavelength distances around imaging targets. While the common benefit of SAR imaging is the use of a single sensor, increasing the number of sensors slightly allows for a multiple-input-multiple-output (MIMO) approach that achieves subwavelength resolution. We have developed a 6 sensor MIMO CSAR processor that drastically reduces sidelobe levels, thus enabling subwavelength imaging. The MIMO CSAR processor reduces overall sidelobe levels by production of multiple unique sidelobe emissions. Overlapping of these emissions spreads out the energy contained in each sidelobe and amplifies the energy of the central beam. The unique sidelobe emissions result from application of the polar formatting algorithm in a MIMO situation, specifically, transmission and reception at distinct angular separations produces unique images within the kappa domain. Optimal angular spacings in a 6-transceiver configuration were found through a genetic algorithm. The genetic algorithm was designed with the goal of reducing the peak sidelobe strength. Our MIMO CSAR processor can produce images with a resolution of lambda/2.