IET Radar, Sonar & Navigation (Apr 2022)

Multi‐task tracking and classification with an adaptive radar

  • Peter John‐Baptiste,
  • Aaron Brandewie,
  • Joe Vinci,
  • Kristine Bell,
  • Joel T. Johnson,
  • Christopher F. Neese,
  • Muralidhar Rangaswamy

DOI
https://doi.org/10.1049/rsn2.12213
Journal volume & issue
Vol. 16, no. 4
pp. 692 – 703

Abstract

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Abstract This study investigates the use of adaptive radar waveforms in performing a multi‐task operation involving the tracking and classification of a single target. The work applies a previously reported hierarchical fully adaptive radar framework and considers a situation in which the target tracking function is performed using a transmit waveform having adaptive pulse repetition frequency, pulse width, bandwidth, and coherent processing interval parameters, while the classification function can be performed using only a fixed radar waveform. Two alternate strategies for selecting the next waveform are then described. The first strategy is focussed on maintaining fixed measurement performance goals in terms of target range and velocity and classification entropy, while the second approach varies these performance goals depending on the target state. Both approaches are examined for simulated datasets at W‐band representing a moving human target, as well as for laboratory measurements of this scenario. The results for both simulation and experiment show the benefits of including adaptive waveforms in performing multiple radar tasks.