Jing, Ning, Mididoddi, Chaitanya K, Wang, Chao (2020) Compressive Sensing Detection of RF Signals by All-Optically Generated Binary Random Patterns. In: 2019 IEEE 2nd British and Irish Conference on Optics and Photonics (BICOP). . IEEE ISBN 978-1-7281-4948-6. (doi:10.1109/BICOP48819.2019.9059595) (KAR id:81975)
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| Official URL: https://dx.doi.org/10.1109/BICOP48819.2019.9059595 |
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Abstract
High-speed random bit sequences are crucially important in temporal compressive sensing applications. In this work, we propose a new all-optical binary random patterns generation method for compressive sensing, completely eliminating the use of high-speed electronic circuits. This approach uses photonic time stretched optical pulses as the optical carrier. Spectrum slicing using a tunable ring resonator produces a train of uniformly spaced optical pulses (bits) due to spectrum-to-time mapping in photonic time stretch. Two cascaded dispersive devices with particularly designed nonlinear dispersion profiles are employed to introduce random time delays among optical pulses, leading to a quasi-random binary sequence. The random sampling pulse sequence can be updated by changing the free-spectral range of the ring resonator. The proposed method is verified by numerical simulations. The photonic generated random pulse sequences are used in compressive sensing detection of high-frequency RF signals. In a proof-of-concept demonstration, one-tone and multi-tone microwave signals are successfully reconstructed from four-time compressed measurement data.
| Item Type: | Conference or workshop item (Proceeding) |
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| DOI/Identification number: | 10.1109/BICOP48819.2019.9059595 |
| Uncontrolled keywords: | RF signal detection; compressive sensing; random sequence generation |
| Subjects: | T Technology |
| Institutional Unit: | Schools > School of Engineering, Mathematics and Physics > Engineering |
| Former Institutional Unit: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
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| Depositing User: | Chao Wang |
| Date Deposited: | 03 Jul 2020 10:35 UTC |
| Last Modified: | 22 Jul 2025 09:02 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/81975 (The current URI for this page, for reference purposes) |
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https://orcid.org/0000-0002-0454-8079
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