Ultralow-Error and Multifrequency Microwave Photonic Frequency Measurement Based on a Programmable Photonic Processor

Microwave photonic frequency measurement is essential for satellite communication, radar, and electronic warfare systems, providing ultrawide bandwidth and high-precision signal processing. Its superior performance over traditional electronic methods enhances signal detection, antijamming capabilities, and system reliability. However, traditional techniques, including frequency-to-time mapping, photonic-assisted channelization, and frequency-to-power mapping, face limitations in measurement error, complexity, and handling multifrequency signals. Here we introduce a programmable photonic processor for microwave frequency measurement, featuring a large-scale chip with 25 hexagonal cells and 102 programmable units. Our approach uses a two-stage process: Mach–Zehnder interferometers (MZIs) for coarse frequency localization, followed by microring resonators (MRRs) for high-resolution measurement, achieve a root-mean-square error (RMSE) of 9 MHz across 0∼20 GHz. Moreover, an innovative high-dimensional frequency-to-power mapping technique enables the precise measurement of multifrequency signals, effectively overcoming the limitations of traditional methods. These results demonstrate the significant potential of programmable photonic processor to enhance microwave photonic frequency measurement, offering improved performance, flexibility, and scalability for future microwave photonic systems.

Authors

Institutions

Publication Details

Journal
ACS Photonics
Published
2026-02-11
DOI
https://doi.org/10.1021/acsphotonics.6c00085
Primary Topic
Advanced Photonic Communication Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ultralow-Error and Multifrequency Microwave Photonic Frequency Measurement Based on a Programmable Photonic Processor

Naidi Cui, Guanyu Chen, Junbo Feng, Yuxin Liang et al.
ACS Photonics
Advanced Photonic Communication Systems
article

Ultralow-Error and Multifrequency Microwave Photonic Frequency Measurement Based on a Programmable Photonic Processor

Naidi Cui, Guanyu Chen, Junbo Feng, Yuxin Liang, Hanmeng Li, Shijia Fan, Zhihui Li, Ziyao Zhang, Yushan Liu, Tao Zhu
article en

Abstract

Microwave photonic frequency measurement is essential for satellite communication, radar, and electronic warfare systems, providing ultrawide bandwidth and high-precision signal processing. Its superior performance over traditional electronic methods enhances signal detection, antijamming capabilities, and system reliability. However, traditional techniques, including frequency-to-time mapping, photonic-assisted channelization, and frequency-to-power mapping, face limitations in measurement error, complexity, and handling multifrequency signals. Here we introduce a programmable photonic processor for microwave frequency measurement, featuring a large-scale chip with 25 hexagonal cells and 102 programmable units. Our approach uses a two-stage process: Mach–Zehnder interferometers (MZIs) for coarse frequency localization, followed by microring resonators (MRRs) for high-resolution measurement, achieve a root-mean-square error (RMSE) of 9 MHz across 0∼20 GHz. Moreover, an innovative high-dimensional frequency-to-power mapping technique enables the precise measurement of multifrequency signals, effectively overcoming the limitations of traditional methods. These results demonstrate the significant potential of programmable photonic processor to enhance microwave photonic frequency measurement, offering improved performance, flexibility, and scalability for future microwave photonic systems.

ACS PhotonicsVol. 13(5)
Chongqing University (CN), Integrated Optoelectronics (Norway) (NO), Center for Interdisciplinary Studies (IN), United Microelectronics (United States) (US)
Openalex Percentile: Top 58%
Advanced Photonic Communication Systems
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.