Photonic-Assisted Adaptive Wideband Self-Interference Cancellation Based on Self-Mixing for FMCW Radar

An adaptive photonic-assisted wideband self-interference cancellation (SIC) scheme based on self-mixing for frequency-modulated continuous-wave (FMCW) radar is proposed. The signals are modulated onto the optical carrier using a dual-polarization quadrature phase shift keying (DP-QPSK) modulator. After adjusting the delay and amplitude of the reference signal in the optical domain, the self-interference (SI) signal is eliminated through a balanced photodetector (BPD). The output signal from the BPD and the reference signal are mixed and then downconverted to zero intermediate frequency. By checking the delay difference between the signal of interest (SOI) and the SI signal, the two signals are distinguished. The Hooke-Jeeves (HJs) algorithm takes the power of the SI signal after self-mixing as the objective function, adaptively optimizing the delay and amplitude of the reference signal until the objective function is minimized. Experimental results show that the scheme can successfully recover the SOI, with the SI signal being eliminated more than 30 dB. The scheme achieved cancellation depths of 33.2 and 31.9 dB for broadband signals in Ku-band with bandwidths of 500 MHz and 1 GHz, respectively. Additionally, we demonstrated the cancellation of signals within the 4–40 GHz range, with a bandwidth of 100 MHz, achieving a cancellation depth >30 dB.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Microwave Theory and Techniques
Published
2024-12-11
DOI
https://doi.org/10.1109/tmtt.2024.3505987
Citations
2
Primary Topic
Advanced Photonic Communication Systems
Type
article
Field-Weighted Citation Impact
0.42

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Photonic-Assisted Adaptive Wideband Self-Interference Cancellation Based on Self-Mixing for FMCW Radar

Ming Peng, Aijun Wen, Yizhe Fan, Chongbo Zhao et al.
2 citations
IEEE Transactions on Microwave Theory and Techniques
Advanced Photonic Communication Systems
0.42
article

Photonic-Assisted Adaptive Wideband Self-Interference Cancellation Based on Self-Mixing for FMCW Radar

Ming Peng, Aijun Wen, Yizhe Fan, Chongbo Zhao, He Wang
article en
2 citations

Abstract

An adaptive photonic-assisted wideband self-interference cancellation (SIC) scheme based on self-mixing for frequency-modulated continuous-wave (FMCW) radar is proposed. The signals are modulated onto the optical carrier using a dual-polarization quadrature phase shift keying (DP-QPSK) modulator. After adjusting the delay and amplitude of the reference signal in the optical domain, the self-interference (SI) signal is eliminated through a balanced photodetector (BPD). The output signal from the BPD and the reference signal are mixed and then downconverted to zero intermediate frequency. By checking the delay difference between the signal of interest (SOI) and the SI signal, the two signals are distinguished. The Hooke-Jeeves (HJs) algorithm takes the power of the SI signal after self-mixing as the objective function, adaptively optimizing the delay and amplitude of the reference signal until the objective function is minimized. Experimental results show that the scheme can successfully recover the SOI, with the SI signal being eliminated more than 30 dB. The scheme achieved cancellation depths of 33.2 and 31.9 dB for broadband signals in Ku-band with bandwidths of 500 MHz and 1 GHz, respectively. Additionally, we demonstrated the cancellation of signals within the 4–40 GHz range, with a bandwidth of 100 MHz, achieving a cancellation depth >30 dB.

IEEE Transactions on Microwave Theory and TechniquesVol. 73(7)
Xidian University (CN)
Fundamental Research Funds for the Central Universities
Climate action
Openalex Percentile: Top 36%
Advanced Photonic Communication Systems
0.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.