Algorithms for Millimeter Wave Imaging and Sensing



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“Millimeter waves” have enabled potential solutions to key problems in the field of security scanning, medical imaging, automotive radars and next generation wireless communication systems. These applications have become possible due to the advancements in semiconductor technology, permitting inexpensive and densely packed millimeter wave circuits. Imaging and locating targets of interest with millimeter and terahertz waves have experienced dramatic performance improvement due to the higher bandwidth and smaller size of antenna elements at millimeter wave frequencies.

This dissertation develops novel signal processing algorithms to improve the performance of millimeter wave imaging and sensing systems. A two dimensional beamforming based millimeter wave imaging technique is formulated, which can reconstruct targets in the near field of an antenna array. The technique shows improved performance over existing switched array imaging. Besides the algorithmic development, a mathematical analysis is performed to investigate the sensitivity of the proposed imaging technique in the presence of phase errors.

The later part of this dissertation concentrates on imaging of targets in the far field of an imaging antenna array. Novel algorithms are designed to localize targets jointly across multiple dimensions using superresolution techniques. For the real time implementation of these algorithms, the emphasis is given on the computational cost reduction.

Finally, the low complexity far field imaging algorithms are validated with electromagnetic simulators as well as with 24 GHz radar testbed built at The University of Texas at Dallas. Details of radar testbed prototyping and antenna design are also presented.



Millimeter wave devices, Signal processing, Imaging systems, Radar


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