Abstract
Due to the highly controllable mobility and deployment flexibility, unmanned aerial vehicles (UAVs) can simultaneously provide efficient communication and high-precision sensing based on synthetic aperture radar (SAR). In this paper, we investigate joint user scheduling, beamforming, and trajectory design in a joint SAR and communication (JSARC) multipleinput multiple-output (MIMO) UAV system. By utilizing the mobility of UAV to synthesize a large-aperture antenna, the system’s sensing accuracy is enhanced. We formulate a throughput maximization problem subject to UAV mobility and SAR sensing constraints. To address the resulting non-convex optimization problem, we develop a successive convex approximation (SCA) based joint user scheduling, UAV trajectory, and beamforming design (JUTBD) algorithm, which alternately optimizes each variable to obtain an effective solution. Furthermore, we study single-view and multi-view imaging with orthogonal frequency division multiplexing (OFDM) signals, and propose a multiview superposition based imaging algorithm. Simulation results validate the effectiveness of the proposed JUTBD algorithm and the multi-view superposition based imaging algorithm. The impact of various factors on the user throughput is analyzed, and the trade-off between the system’s communication and sensing performance is demonstrated in terms of communication spectral efficiency and the imaging peak signal-to-noise ratio (PSNR).
| Original language | English |
|---|---|
| Journal | IEEE Transactions on Communications |
| DOIs | |
| Publication status | Accepted/In press - 2026 |
| Externally published | Yes |
Keywords
- Integrated sensing and communication
- orthogonal frequency division multiplexing
- synthetic aperture radar
- trajectory design
- unmanned aerial vehicle
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