Symmetric Gain Optoelectronic Mixers for LADAR

Abstract

We are developing a symmetric gain optoelectronic mixer for chirped-AM laser detection and ranging systems (LADAR) operating in the "eye-safe" 1.55 micron wavelength range. Signal processing of a chirped-AM LADAR system is simplified if the photodetector in the receiver is used as an optoelectronic mixer (OEM). Adding gain to the optoelectronic mixer allows the following transimpedance amplifier's gain to be reduced, increasing bandwidth and improving the system's noise performance. The symmetric gain optoelectronic mixer is based on a symmetric heterojunction phototransistor. The base layer is In0.53Ga0.47As (InGaAs), and the emitter/ collector layer is In0.48Al0.52As (InAlAs). Two dimensional simulations of the devices were carried out to analyze device performance. Two sample heterostructures were grown using molecular beam epitaxy. We are currently in the prototype development stage. Simulation results and preliminary results from the initial batch of devices are presented. These symmetric gain optoelectronic mixer devices can lead to miniaturized LADAR-on-chip system. Such a system will have many military and civilian applications, such as range finding, terrain mapping, reconnaissance, and face recognition.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2008
Accession Number
ADA506249

Entities

People

  • Justin R. Bickford
  • Neal Bambha
  • Nuri W. Emanetoglu
  • Stephen Drew

Organizations

  • University of Maine

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Bipolar Junction Transistors
  • Detection
  • Detectors
  • Electronics Laboratories
  • Heterojunctions
  • Laser Radar
  • Lasers
  • Molecular Beam Epitaxy
  • Molecular Beams
  • Optical Detection
  • Photodiodes
  • Phototransistors
  • Power Electronics
  • Range Finding
  • Semiconductors
  • Transistors
  • Two Dimensional

Readers

  • Electronics Engineering
  • Image Processing and Computer Vision.
  • Semiconductor Device Technology

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Directed Energy
  • Microelectronics