A Quantum Range-Doppler Algorithm for Synthetic Aperture Radar Image Formation

• URL: http://arxiv.org/abs/2504.20811v1
• Date: Tue, 29 Apr 2025 14:24:23 GMT
• Title: A Quantum Range-Doppler Algorithm for Synthetic Aperture Radar Image Formation
• Authors: Alessandro Giovagnoli, Sigurd Huber, Gerhard Krieger,
• Abstract summary: We show how in general reference functions, a key element in many SAR focusing algorithms, can be mapped to quantum gates.<n>We find that the core of the quantum range-Doppler algorithm has a computational complexity $O(N)$, less than its classical counterpart.
• Score: 48.123217909844946
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Synthetic aperture radar (SAR) is a well established technology in the field of Earth remote sensing. Over the years, the resolution of SAR images has been steadily improving and the pixel count increasing as a result of advances in the sensor technology, and so have the computational resources required to process the raw data to a focused image. Because they are a necessary step in the study of the retrieved data, new high-resolution and low-complexity focusing algorithms are constantly explored in the SAR literature. The theory of quantum computing proposes a new computational framework that might allow to process a vast amount of data in a more efficient way. Relevant to our case is the advantage proven for the quantum Fourier transform (QFT), the quantum counterpart of a fundamental element of many SAR focusing algorithms. Motivated by this, in this work we propose a quantum version of the range-Doppler algorithm. We show how in general reference functions, a key element in many SAR focusing algorithms, can be mapped to quantum gates; we present the quantum circuit performing the SAR raw data focusing and we discuss in detail its computational complexity. We find that the core of the quantum range-Doppler algorithm has a computational complexity, namely the number of single- and two-qubit gates, of $O(N)$, less than its classical counterpart with computational complexity $O(N \log N)$.

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