Tiled Beamspace MVDR for 1024-element Wideband Radar
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866915848145338368 |
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| author | Noroozi, Oveys Delafrooz Han, Jiyoon Tang, Wei Zhang, Zhengya Madhow, Upamanyu |
| author_facet | Noroozi, Oveys Delafrooz Han, Jiyoon Tang, Wei Zhang, Zhengya Madhow, Upamanyu |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_06536 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Tiled Beamspace MVDR for 1024-element Wideband Radar Noroozi, Oveys Delafrooz Han, Jiyoon Tang, Wei Zhang, Zhengya Madhow, Upamanyu Signal Processing 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. |
| title | Tiled Beamspace MVDR for 1024-element Wideband Radar |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2512.06536 |