Sparse frequency waveform design under Riemannian manifold constraint

Zixuan Sun; Kai Huo; Xiangfeng Qiu

doi:10.1117/12.3045690

15 January 2025 Sparse frequency waveform design under Riemannian manifold constraint

Zixuan Sun, Kai Huo, Xiangfeng Qiu

Author Affiliations +

Proceedings Volume 13513, The International Conference Optoelectronic Information and Optical Engineering (OIOE2024); 135132C (2025) https://doi.org/10.1117/12.3045690
Event: The International Conference Optoelectronic Information and Optical Engineering (OIOE2024), 2024, Wuhan, China

Abstract

The problem of spectrum conflicts is becoming increasingly prominent nowadays, and radar waveforms in practical scenarios urgently need to have good anti-interference performance. In response to the low computational efficiency and high complexity of traditional waveform design methods under complex natural environmental conditions, this paper introduces the Riemannian manifold into classical constant modulus constrained waveform design. Our method effectively suppresses arbitrary frequency bands and enables the obtainment of sparse frequency radar waveforms with minimal sidelobe levels. We map the constant modulus constrained space in radar systems to the search space, thereby transforming the constrained optimization problem into an unconstrained one. Simulation results validate the effectiveness of our method, significantly improving the computational efficiency of radar waveform calculations and the overall performance compared to classical methods.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Zixuan Sun, Kai Huo, and Xiangfeng Qiu "Sparse frequency waveform design under Riemannian manifold constraint", Proc. SPIE 13513, The International Conference Optoelectronic Information and Optical Engineering (OIOE2024), 135132C (15 January 2025); https://doi.org/10.1117/12.3045690

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KEYWORDS

Design

Radar

Convex optimization

Spectral density

Autocorrelation

Computer simulations

Defense technologies

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