OFDM-Based ISAC Imaging of Extended Targets via Inverse Virtual Aperture Processing

Fuente: arXiv
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Hauptverfasser: Negosanti, Michael, Pucci, Lorenzo, Giorgetti, Andrea
Format: Preprint
Veröffentlicht: 2026
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author Negosanti, Michael
Pucci, Lorenzo
Giorgetti, Andrea
author_facet Negosanti, Michael
Pucci, Lorenzo
Giorgetti, Andrea
contents This work investigates the performance of an integrated sensing and communication (ISAC) system exploiting inverse virtual aperture (IVA) for imaging moving extended targets in vehicular scenarios. A base station (BS) operates as a monostatic sensor using MIMO-OFDM waveforms. Echoes reflected by the target are processed through motion-compensation techniques to form an IVA range-Doppler (cross-range) image. A case study considers a 5G NR waveform in the upper mid-band, with the target model defined in 3GPP Release 19, representing a vehicle as a set of spatially distributed scatterers. Performance is evaluated in terms of image contrast (IC) and the root mean squared error (RMSE) of the estimated target-centroid range. Finally, the trade-off between sensing accuracy and communication efficiency is examined by varying the subcarrier allocation for IVA imaging. The results provide insights for designing effective sensing strategies in next-generation radio networks.
format Preprint
id arxiv_https___arxiv_org_abs_2601_16664
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle OFDM-Based ISAC Imaging of Extended Targets via Inverse Virtual Aperture Processing
Negosanti, Michael
Pucci, Lorenzo
Giorgetti, Andrea
Signal Processing
Image and Video Processing
This work investigates the performance of an integrated sensing and communication (ISAC) system exploiting inverse virtual aperture (IVA) for imaging moving extended targets in vehicular scenarios. A base station (BS) operates as a monostatic sensor using MIMO-OFDM waveforms. Echoes reflected by the target are processed through motion-compensation techniques to form an IVA range-Doppler (cross-range) image. A case study considers a 5G NR waveform in the upper mid-band, with the target model defined in 3GPP Release 19, representing a vehicle as a set of spatially distributed scatterers. Performance is evaluated in terms of image contrast (IC) and the root mean squared error (RMSE) of the estimated target-centroid range. Finally, the trade-off between sensing accuracy and communication efficiency is examined by varying the subcarrier allocation for IVA imaging. The results provide insights for designing effective sensing strategies in next-generation radio networks.
title OFDM-Based ISAC Imaging of Extended Targets via Inverse Virtual Aperture Processing
topic Signal Processing
Image and Video Processing
url https://arxiv.org/abs/2601.16664