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Quantum range-migration-algorithm for synthetic aperture radar applications.

Erik H Waller1, Andreas Keil2,3, Fabian Friederich2

  • 1Fraunhofer-Institute for Industrial Mathematics ITWM, Fraunhofer-Platz 1, 67663, Kaiserslautern, Germany. erik.waller@itwm.fraunhofer.de.

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|July 15, 2023
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Summary
This summary is machine-generated.

We developed a quantum 3D range-migration algorithm (RMA) that offers improved speed over classical methods. This quantum RMA, tested on simulators and IBM

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Area of Science:

  • Quantum Computing
  • Signal Processing
  • Synthetic Aperture Radar (SAR)

Background:

  • Classical 3D range-migration algorithm (RMA) and omega-k algorithm are crucial for synthetic aperture data reconstruction in diverse fields like satellite imaging, seismic exploration, and non-destructive testing.
  • These algorithms rely on Fourier transforms, limiting processing speed for high-resolution data, which is a bottleneck for high-throughput applications.

Purpose of the Study:

  • To develop and implement a quantum version of the 3D range-migration algorithm (RMA).
  • To evaluate the performance and scalability of the quantum RMA compared to its classical counterpart.
  • To assess the feasibility of using quantum computers for real-world synthetic aperture data processing tasks.

Main Methods:

  • Development of a quantum 3D range-migration algorithm (RMA).
  • Comparison of reconstruction results between classical and quantum RMA using simulated and measured data.
  • Execution of the quantum RMA on both a quantum simulator and IBM's Q System One quantum computer.

Main Results:

  • The quantum RMA demonstrates favorable scaling in time-complexity compared to the classical RMA.
  • Reconstruction results from the quantum RMA are comparable to the classical RMA for simulated and measured data.
  • The quantum RMA successfully executed on both quantum simulators and a real quantum hardware.

Conclusions:

  • Quantum computing offers a promising approach to accelerate synthetic aperture data processing.
  • The developed quantum RMA has the potential to significantly benefit real-world applications requiring high-speed, high-resolution data processing.
  • Future quantum computers may enable faster and more efficient solutions for tasks currently limited by classical algorithms.