Photonic compressed sensing nyquist folding receiver

Abstract

The use of integrated optical components and how they can be used to implement a compressed sensing microwave photonic receiver are investigated in this thesis. The scope of this research covers the design, simulation, and hardware build of a photonic compressed sensing Nyquist folding receiver that is able to directly undersample wideband RF signals and detect the original Nyquist zone and frequency information. This is achieved by generating a frequency modulated optical impulse train for directly undersampling the RF environment at the antenna. The impulse train undersamples the signals using an optical modulator configuration at 1550 nm and collects the detected samples in a low pass interpolation filter. Two independent photonic receiver architectures are designed and analyzed over the course of this research. Both receiver designs are simulated in the OPTSIM photonic design suite and are able to successfully extract the undersampled signals. The first receiver design proved more effective at representing the signal environment and was constructed using electro-optical hardware. Using off-the-shelf components in a proof-of-concept hardware prototype, we confirmed the simulation results by correctly identifying input test frequencies up to an order of magnitude higher than the sampling frequency.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2017
Accession Number
AD1046923

Entities

People

  • Richard N. Shmel

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Compressed Sensing
  • Detection
  • Detectors
  • Digital Signal Processing
  • Electrical Engineering
  • Electronic Intelligence
  • Frequency
  • Image Processing
  • Lasers
  • Modulation
  • Modulators
  • Optical Modulators
  • Signal Generators
  • Signal Processing
  • Signals Intelligence
  • Test And Evaluation
  • Waveforms

Fields of Study

  • Engineering

Readers

  • Image Processing and Computer Vision.
  • Integrated Circuit Design and Technology.
  • Radio communications and signal processing.