Advanced Digital Signal Processing for Hybrid Lidar

Abstract

The technical objective of this project is the development and evaluation of various digital signal processing (DSP) algorithms that will enhance hybrid lidar performance. Practical algorithms must be developed taking into account the underwater propagation channel and the processing requirements for each algorithm. The hardware platforms being considered for lidar signal processing are based on software defined radios (SDRs). NAWC has selected a digital hardware platform based on COMBLOCK software defined radio (SDR) modules. Clarkson has investigated several other SDR approaches which include two open source SDR platforms and one commercial platform. We selected the Signal Hound SDR for . additional characterization since it is commercially available and has a well-supported Application Programmer's Interface or API. The API allows us to configure the SDR and obtain data in a MATLAB programming environment. The primary activity during this reporting period consisted of evaluating the Signal Hound SDR for lidar signal processing. Specifically we developed software that allows us to configure and collect data from the SDR within the MATLAB programming,environment. This will allow us to used MALAB as a DSP development platform.

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Document Details

Document Type
Technical Report
Publication Date
Jan 31, 2012
Accession Number
ADA628174

Entities

People

  • William D. Jemison

Organizations

  • Clarkson University

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Amplitude
  • Analyzers
  • Attenuation
  • Computer Programming
  • Digital Signal Processing
  • Dynamic Range
  • Frequency
  • Generators
  • Graphical User Interface
  • Intermediate Frequencies
  • Local Oscillators
  • Signal Generators
  • Signal Processing
  • Software Defined Radio
  • Spectrum Analyzers
  • Test Equipment

Fields of Study

  • Engineering

Readers

  • Computer Vision.
  • Database Systems and Applications
  • Radio communications and signal processing.