Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 41,
  • Issue 18,
  • pp. 5895-5901
  • (2023)

Precise Multiple Frequency Identification Based on Frequency-to-Time Mapping and Cross-Correlation

Not Accessible

Your library or personal account may give you access

Abstract

We propose and demonstrate a microwave frequency identification system based on frequency-to-time mapping (FTTM) and cross-correlation. The unknown microwave signals and the bidirectional chirped microwave probe signal are mixed by using a dual-drive Mach-Zehnder modulator. The mixing products are equivalently selected by a dispersion induced photonic filter and converted into electrical pulses in time domain. The unknown frequency is measured by calculating the time interval of the pulses. Moreover, a scheme based on cross-correlation is proposed to eliminate the noise interference for the pulse position acquisition. Experimentally, single and multiple frequency identification from 2–14 GHz is successfully demonstrated, and the measured frequency errors are less than ±3 MHz.

PDF Article
More Like This
Photonics-assisted microwave pulse detection and frequency measurement based on pulse replication and frequency-to-time mapping

Pengcheng Zuo, Dong Ma, Qingbo Liu, Lizhong Jiang, and Yang Chen
Appl. Opt. 61(7) 1639-1645 (2022)

Photonic arbitrary waveform generation based on crossed frequency to time mapping

H.-Y. Jiang, L.-S. Yan, Y.-F. Sun, J. Ye, W. Pan, B. Luo, and X.-H. Zou
Opt. Express 21(5) 6488-6496 (2013)

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 Optica member, or as an authorized user of your institution.

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

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.