SUMMeR: Sub-Nyquist MIMO Radar
David Cohen, Deborah Cohen, Yonina C. Eldar, Alexander M. Haimovich

TL;DR
SUMMeR introduces a sub-Nyquist MIMO radar system that reduces hardware and sampling requirements while maintaining high resolution, by exploiting target sparsity in a compressed sensing framework.
Contribution
This work extends sub-Nyquist sampling techniques to MIMO radar, enabling reduced antenna count and sampling rates without sacrificing resolution.
Findings
Detection performance is preserved at various compression levels.
Both time and spatial resolutions are maintained compared to traditional Nyquist MIMO.
Design parameter impacts are analyzed and guidelines are provided.
Abstract
Multiple input multiple output (MIMO) radar exhibits several advantages with respect to traditional radar array systems in terms of flexibility and performance. However, MIMO radar poses new challenges for both hardware design and digital processing. In particular, achieving high azimuth resolution requires a large number of transmit and receive antennas. In addition, the digital processing is performed on samples of the received signal, from each transmitter to each receiver, at its Nyquist rate, which can be prohibitively large when high resolution is needed. Overcoming the rate bottleneck, sub-Nyquist sampling methods have been proposed that break the link between radar signal bandwidth and sampling rate. In this work, we extend these methods to MIMO configurations and propose a sub-Nyquist MIMO radar (SUMMeR) system that performs both time and spatial compression. We present a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
