Date of Award

3-2023

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Julie A. Jackson, PhD

Abstract

Compressed Sensing (CS) is a mathematical technique that can be applied to sparse data sets to allow for sub-Nyquist sampling. DCPCS is a CS technique that recovers the signal from unmeasured polarisation channels due to antenna crosstalk coupling the information onto the remaining channels. DCPCS reduces data storage/transmission and receiver hardware requirements. This thesis examines the robustness of DCPCS to calibration errors on the antenna crosstalk matrix. Although the antenna design problem is relaxed to a large region of acceptable crosstalk values, very accurate calibration may be required in a monostatic radar. This thesis also looks at the importance of properly setting the BPDN threshold ϵ in accordance with the expected clutter and calibration error levels, showing that without any model mismatches it is possible to accurately set ϵ using the estimated scene clutter. Finally, the validity of using a simplified Point Spread Function (PSF) imaging operator to reduce the computational complexity of simulations is shown.

AFIT Designator

AFIT-ENG-MS-23-M-049

Comments

A 12-month embargo was observed.

Approved for public release. Case number on file.

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