Optimization of Waveform Parameters for Multiple Target Tracking Systems in Cognitive Radars

Taylan Denizcan Caha, Lutfiye Durak Ata

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In this study, cognitive radar (CR) applications including radar waveform parameters and track update interval selection are investigated in order to balance the time resource cost and increase the accuracy performance of multiple target tracking systems. For the target tracking part, the unscented Kalman filter (UKF) is applied together with the joint probabilistic data association (JPDA) and the interacting multiple models (IMM) algorithm, which is used to realize more than one target motion model. The waveform parameters and track update interval are adaptively updated by using the outputs of the radar data processing block including target tracking and classification algorithms. The waveform parameters to be updated, the product of the pulse width and the number of integrated pulses, and the track update interval are selected. In the optimization function, the limit values of the parameter selections are decided by using target class information which is supplied by a random forest classifier. Along with the proposed cost function, track continuity and time resource allocation are tested and system performance is demonstrated depending on the target characteristics. In the simulations part, multiple target scenarios that include targets with different maneuvers and radar cross sections (RCS) have been examined and it is shown that the proposed cost function can be applied in multiple target tracking scenarios.

Original languageEnglish
Title of host publicationRadarConf23 - 2023 IEEE Radar Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665436694
DOIs
Publication statusPublished - 2023
Event2023 IEEE Radar Conference, RadarConf23 - San Antonia, United States
Duration: 1 May 20235 May 2023

Publication series

NameProceedings of the IEEE Radar Conference
Volume2023-May
ISSN (Print)1097-5764
ISSN (Electronic)2375-5318

Conference

Conference2023 IEEE Radar Conference, RadarConf23
Country/TerritoryUnited States
CitySan Antonia
Period1/05/235/05/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • classification
  • cognitive radar
  • multiple target tracking
  • optimization
  • radar resource management
  • waveform parameter

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