Abstract

A microwave instantaneous frequency measurement system with a photonic scanning receiver is proposed in which deep neural network (DNN)-assisted frequency estimation is used to deal with the system defects and improve the accuracy. The system performs frequency-to-time mapping by optical-domain frequency scanning and electrical-domain intermediate frequency envelop detection. Thanks to the optical frequency multiplication, the system can measure high frequency signals in a large spectral range. The DNN establishes an accurate mapping between the digital samples and real frequencies, based on which high-accuracy measurement is achieved. The measurement of signals from 43 to 52 GHz is experimentally demonstrated. Compared with the direct measurements, the DNN-assisted method achieves obviously reduced average errors of about 3.2 MHz.

© 2020 Optical Society of America

Full Article  |  PDF Article

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (5)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (7)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription