Abstract

In this work, a waveform agile sensing method for the target tracking problem has been described. By dynamically selecting the transmitted waveform from a generalized FM chirp signal library with different phase functions and chirp parameters, the tracker can improve the performance dramatically. The waveform design algorithm is based on the myopic optimization of a cost function, which is the predicted mean squared error. The cost function is approximated using the CRLB combined with unscented transformation. Then the generalized FM phase function and the corresponding parameters are configured according to a grid search over all the phase function candidates and allowable parameter values. Due to the nonlinearity of the measurement model in the tracking system, particle filtering is applied to track the state of the target. This approach was demonstrated by tracking a target moving in a 2-D cluttered environment with two active sensors. The simulation results showed that the mean squared error of the tracking was dramatically reduced by adaptively adjusting the transmitted signal.

Original languageEnglish (US)
Title of host publicationPrinciples of Waveform Diversity and Design
PublisherInstitution of Engineering and Technology
Pages394-418
Number of pages25
ISBN (Electronic)9781613531501
ISBN (Print)9781891121951
DOIs
StatePublished - Jan 1 2011

Keywords

  • 2D cluttered environment
  • Active sensors
  • Chirp modulation
  • Chirp parameters
  • Cost function
  • Cost function approximation
  • CRLB
  • Dynamically configured sensor systems
  • Generalized fm chirp signal library
  • Generalized fm phase function
  • Mean square error methods
  • Mean squared error
  • Mean squared error prediction
  • Measurement model
  • Measurement systems
  • Moving target tracking
  • Myopic optimization-based waveform design algorithm
  • Optimisation
  • Particle filtering
  • Particle filtering (numerical methods)
  • Radar clutter
  • Radar signal processing
  • Sensors
  • Signal transmission
  • Target tracking
  • Target tracking problem
  • Time-frequency analysis
  • Unscented transformation
  • Waveform agile sensing method
  • Waveform time-frequency characterization
  • Waveform transmission

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Li, Y., Sira, S. P., Papandreou-Suppappola, A., & Morrell, D. (2011). Waveform time-frequency characterization for dynamically configured sensor systems. In Principles of Waveform Diversity and Design (pp. 394-418). Institution of Engineering and Technology. https://doi.org/10.1049/SBRA023E_ch21