Job Description

Currently, fully digital automotive radars face limitations in resolution due to the use of a limited number of antennas and low bandwidth settings, which are aimed at minimizing power consumption. A promising low-power alternative is one that uses low-resolution radar components which operate at high bandwidths. Radar signal processing with such a hardware, however, is extremely challenging due to the stringent constraints imposed by coarse quantization. Furthermore, these hardwares generate massive amount of information that is difficult to process using conventional techniques. To address both these challenges, we seek a talented individual to develop low-complexity radar signal processing techniques capable of effectively operating under coarse quantization effects at the receiver.

As part of this project, you will tackle this challenge by developing cutting-edge solutions that will push low-resolution automotive radars to their limits. Specifically, your focus will be on two key research themes:
a) Designing space-time waveforms that are robust to quantization effects at the receiver.
b) Developing low-complexity sparse recovery algorithms for target detection and interference management.

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