Tiled Beamspace MVDR for 1024-element Wideband Radar

TL;DR

This paper introduces a tiled beamspace MVDR architecture for wideband massive MIMO radar, enabling efficient digital beamforming with dimension reduction and coordinated training across tiles, demonstrating significant performance improvements over single-tile methods.

Contribution

The paper proposes a novel tiled beamspace MVDR approach that reduces computational complexity and enhances performance for large-scale wideband radar systems.

Findings

Significant performance improvement over single-tile beamforming.

Effective dimension reduction via beamspace and tile coordination.

Feasible implementation for 1024-element airborne radar.

Abstract

We present a tiled architecture for computationally efficient digital beamforming for wideband massive MIMO radar, using beamspace dimension reduction for each tile, and coordinated training of reduced-dimension MVDR beamformers across tiles. We illustrate the efficacy of our approach for a setting in which a 1024-element airborne radar platform beamforms towards airborne targets while suppressing strong interference from ground transmitters. The array is organized into eight 128-element tiles, each a 2D array with 4 (vertical) x 32 (horizontal) elements. Each tile applies a 2D spatial DFT to achieve energy concentration in beamspace, and a 1D temporal FFT to channelize the wideband signal into subbands for which narrowband array models apply. A small tile-level beamspace window is selected for each target (depending on its angle of arrival) in each subband, and coordinated training across tiles is used to compute reduced-dimension MVDR beamformers per-target, per-subband. While full-dimensional MVDR processing is infeasible for the system under consideration, we show that our proposed approach significantly outperforms beamspace MVDR beamforming for a single 128-element tile, where we set the dimensions of the spatial filter (and hence the complexity of MVDR training) to be equal in both systems.