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Active Reconfigurable Intelligent Surface Empowered Synthetic Aperture Radar Imaging

Yifan Sun, Rang Liu, Zhiping Lu, Honghao Luo, Ming Li, Qian Liu

TL;DR

The paper tackles enabling high-resolution SAR imaging with a stationary radar by leveraging a UAV-mounted ARIS to create a virtual LoS and an extended synthetic aperture. It introduces a range-Doppler imaging pipeline tailored to ARIS-reflected paths and an FP-MM-based optimization to maximize the receiver SNR under ARIS power and per-element gain constraints $P_{ m ARIS}$ and $a_{ m max}$. Key contributions include a detailed ARIS-enabled system model, a modified RD imaging chain, and an efficient FP-MM ARIS design algorithm with convex subproblems solved via CVX, all validated by simulations showing significant SNR gains and improved imaging over PRIS. The work demonstrates a practical, lightweight approach to upgrade stationary radar sensing with mobile ARIS platforms, enabling high-resolution SAR imaging in scenarios where deploying conventional active radar apertures is impractical.

Abstract

Synthetic Aperture Radar (SAR) utilizes the movement of the radar antenna over a specific area of interest to achieve higher spatial resolution imaging. In this paper, we aim to investigate the realization of SAR imaging for a stationary radar system with the assistance of active reconfigurable intelligent surface (ARIS) mounted on an unmanned aerial vehicle (UAV). As the UAV moves along the stationary trajectory, the ARIS can not only build a high-quality virtual line-of-sight (LoS) propagation path, but its mobility can also effectively create a much larger virtual aperture, which can be utilized to realize a SAR system. In this paper, we first present a range-Doppler (RD) imaging algorithm to obtain imaging results for the proposed ARIS-empowered SAR system. Then, to further improve the SAR imaging performance, we attempt to optimize the reflection coefficients of ARIS to maximize the signal-to-noise ratio (SNR) at the stationary radar receiver under the constraints of ARIS maximum power and amplification factor. An effective algorithm based on fractional programming (FP) and majorization minimization (MM) methods is developed to solve the resulting non-convex problem. Simulation results validate the effectiveness of ARIS-assisted SAR imaging and our proposed RD imaging and ARIS optimization algorithms.

Active Reconfigurable Intelligent Surface Empowered Synthetic Aperture Radar Imaging

TL;DR

The paper tackles enabling high-resolution SAR imaging with a stationary radar by leveraging a UAV-mounted ARIS to create a virtual LoS and an extended synthetic aperture. It introduces a range-Doppler imaging pipeline tailored to ARIS-reflected paths and an FP-MM-based optimization to maximize the receiver SNR under ARIS power and per-element gain constraints and . Key contributions include a detailed ARIS-enabled system model, a modified RD imaging chain, and an efficient FP-MM ARIS design algorithm with convex subproblems solved via CVX, all validated by simulations showing significant SNR gains and improved imaging over PRIS. The work demonstrates a practical, lightweight approach to upgrade stationary radar sensing with mobile ARIS platforms, enabling high-resolution SAR imaging in scenarios where deploying conventional active radar apertures is impractical.

Abstract

Synthetic Aperture Radar (SAR) utilizes the movement of the radar antenna over a specific area of interest to achieve higher spatial resolution imaging. In this paper, we aim to investigate the realization of SAR imaging for a stationary radar system with the assistance of active reconfigurable intelligent surface (ARIS) mounted on an unmanned aerial vehicle (UAV). As the UAV moves along the stationary trajectory, the ARIS can not only build a high-quality virtual line-of-sight (LoS) propagation path, but its mobility can also effectively create a much larger virtual aperture, which can be utilized to realize a SAR system. In this paper, we first present a range-Doppler (RD) imaging algorithm to obtain imaging results for the proposed ARIS-empowered SAR system. Then, to further improve the SAR imaging performance, we attempt to optimize the reflection coefficients of ARIS to maximize the signal-to-noise ratio (SNR) at the stationary radar receiver under the constraints of ARIS maximum power and amplification factor. An effective algorithm based on fractional programming (FP) and majorization minimization (MM) methods is developed to solve the resulting non-convex problem. Simulation results validate the effectiveness of ARIS-assisted SAR imaging and our proposed RD imaging and ARIS optimization algorithms.
Paper Structure (6 sections, 27 equations, 6 figures)

This paper contains 6 sections, 27 equations, 6 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Rang-Doppler Imaging Algorithm
  4. ARIS Design Algorithm
  5. Simulation Results
  6. Conclusion

Figures (6)

  • Figure 1: An ARIS-assisted SAR imaging system.
  • Figure 2: Radar SNR versus time slot.
  • Figure 3: Radar SNR versus numbers of RIS elements.
  • Figure 4: Radar SNR versus transmitted power.
  • Figure 5: (a) House original picture. (b) House imaging with ARIS ($a_{\rm max}=20$). (c) House imaging with ARIS ($a_{\rm max}=5$). (d) House imaging with PRIS.
  • ...and 1 more figures