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Advances in waveform-agile sensing for tracking

Recent advances in sensor technology and information processing afford a new flexibility in the design of waveforms for agile sensing. Sensors are now developed with the ability to dynamically choose their transmit or receive waveforms in order to optimize an objective cost function. This has expose...

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Bibliographic Details
Main Author: Sira, Sandeep Prasad.
Other Authors: Papandreou-Suppappola, Antonia., Morrell, Darryl.
Format: Electronic
Language:English
Published: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, c2009.
Series:Synthesis lectures on algorithms and software in engineering (Online) ; # 2.
Subjects:
Sensor networks > Mathematical models.
Wave functions > Mathematical models.
Online Access:View fulltext via EzAccess
Table of Contents:
  • Introduction
  • Waveform-agile sensing
  • Waveform adaptation for tracking: a review
  • Organization
  • Waveform-agile target tracking application formulation
  • Filtering overview
  • The particle filter
  • The unscented particle filter
  • Tracking problem formulation
  • Target dynamics
  • Transmitted waveform structure
  • Observations model
  • Measurement noise covariance
  • Waveform selection problem statement
  • Dynamic waveform selection with application to narrowband and wideband environments
  • Prediction of the MSE
  • Stochastic approximation
  • Calculation of the gradient
  • Simultaneous perturbation stochastic approximation
  • Stochastic gradient descent algorithm
  • Drawbacks
  • Unscented transform based approximation
  • Algorithm for waveform selection
  • Narrowband environment
  • Waveform structure
  • CRLB for GFM pulses
  • Simulation
  • Discussion
  • Wideband environment
  • Wideband signal model
  • Waveform structure
  • Simulation
  • Discussion
  • Dynamic waveform selection for tracking in clutter
  • Single target
  • Observations model
  • Clutter model
  • Target tracking with probabilistic data association
  • Waveform selection in the presence of clutter
  • Simulation
  • Discussion
  • Performance under different choices of the weighting matrix
  • Multiple targets
  • Target dynamics
  • Measurement model
  • Clutter model
  • Multiple target tracking with joint probabilistic data association
  • Dynamic waveform selection and configuration
  • Simulation
  • Discussion
  • Conclusions
  • Summary of findings
  • CRLB evaluation for Gaussian Envelope GFM Chirp from the ambiguity function
  • CRLB evaluation from the complex envelope
  • Sample code for a simple particle filter
  • Sample code for an unscented particle filter.

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