Sub-Nyquist collocated MIMO radar in time and space

Abstract

Multiple input multiple output (MIMO) radar exhibits several advantages with respect to traditional monostatic radar by exploiting transmit waveform diversity. Achieving high resolution requires a large number of transmit and receive antennas. In addition, the digital processing is performed on samples of the received signal at its Nyquist rate, which can be high. Overcoming the rate bottleneck, sub-Nyquist sampling methods have been proposed that break the link between monostatic radar signal bandwidth and sampling rate. In this work, we extend theses methods to MIMO radar and apply the Xampling framework both in the time and spatial domains, achieving reduction in the number of deployed antennas and the number of samples per receiver, without degrading the time and spatial resolutions.

Cognitive sub-Nyquist hardware prototype of a collocated MIMO radar

“…With the exception of cognitive transmission, the array and signal models of sub-Nyquist MIMO realized by our prototype closely follow that detailed by [9] and, hence, we only summarize them here.…”

“…The performance guarantees of this procedure are provided in [9]. The received signal x q (t) is separated into M channels, aligned and normalized.…”

“…This implementation follows the recommendations of [9] for signal orthogonality, array structure and reconstruction algorithms. The prototype can be configured either as a filled or thinned array, thereby allowing comparison of Nyquist and sub-Nyquist spatial sampling using the same hardware.…”

Sub-Nyquist MIMO radar prototype with Doppler processing

“…In [8], a sub-Nyquist collocated MIMO radar (SUMMeR) was proposed to recover the target range, azimuth and Doppler velocity by simultaneously thinning an antenna array and sampling received signals at sub-Nyquist rates. The recovery algorithm uses the Xampling framework where Fourier coefficients of the received signal are acquired from their low-rate samples (or Xamples) [7,9].…”

“…This implementation follows the recommendations of [11] for signal orthogonality, array structure and reconstruction algorithms. There, only the targets' azimuth and range are recovered, from a single pulse per transmitter.…”